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-/tutorial/2b-create-a-project-dbt-cli.md /guides/getting-started/learning-more/getting-started-dbt-core 302 -/tutorial/create-a-project-dbt-cli /guides/getting-started/learning-more/getting-started-dbt-core 302 -/tutorial/2a-create-a-project-dbt-cloud.md /guides/getting-started 302 -/tutorial/create-a-project-dbt-cloud /guides/getting-started 302 +/docs/hooks /docs/building-a-dbt-project/hooks-operations 302 +/docs/init /reference/commands/init 302 +/docs/install-from-source /dbt-cli/installation 302 +/docs/installation /dbt-cli/installation 302 +/docs/invocation_id /docs/writing-code-in-dbt/jinja-context/invocation_id 302 +/docs/jinja-context /docs/writing-code-in-dbt/jinja-context 302 +/docs/license /docs/about/license 302 +/docs/list /reference/commands/list 302 +/docs/log /docs/writing-code-in-dbt/jinja-context/log 302 +/docs/macos /dbt-cli/installation 302 +/docs/macros /docs/building-a-dbt-project/macros 302 +/docs/managing-environments /guides/legacy/managing-environments 302 +/docs/materializations /docs/building-a-dbt-project/building-models/materializations 302 +/docs/model-selection-syntax /reference/node-selection/syntax 302 +/docs/modules /docs/writing-code-in-dbt/jinja-context/modules 302 +/docs/on-run-end-context /docs/writing-code-in-dbt/jinja-context/on-run-end-context 302 +/docs/overview /docs/introduction 302 +/docs/package-management /docs/building-a-dbt-project/package-management 302 +/docs/profile-bigquery /reference/warehouse-profiles/bigquery-profile 302 +/docs/profile-mssql /reference/warehouse-profiles/mssql-profile 302 +/docs/profile-postgres /reference/warehouse-profiles/postgres-profile 302 +/docs/profile-presto /reference/warehouse-profiles/presto-profile 302 +/docs/profile-redshift /reference/warehouse-profiles/redshift-profile 302 +/docs/profile-snowflake /reference/warehouse-profiles/snowflake-profile 302 +/docs/profile-spark /reference/warehouse-profiles/spark-profile 302 +/docs/redshift-configs /reference/resource-configs/redshift-configs 302 +/docs/spark-configs /reference/resource-configs/spark-configs 302 +/docs/redshift-v2 /reference/warehouse-profiles/redshift-profile 302 +/docs/ref /docs/writing-code-in-dbt/jinja-context/ref 302 +/docs/requiring-specific-dbt-versions /docs/building-a-dbt-project/dbt-projects/requiring-specific-dbt-versions 302 +/docs/return /docs/writing-code-in-dbt/jinja-context/return 302 +/docs/rpc /reference/commands/rpc 302 +/docs/run /reference/commands/run 302 +/docs/run-operation /reference/commands/run-operation 302 +/docs/run_query /docs/writing-code-in-dbt/jinja-context/run_query 302 +/docs/run_started_at /docs/writing-code-in-dbt/jinja-context/run_started_at 302 +/docs/running-a-dbt-project/command-line-interface /reference/dbt-commands 302 +/docs/running-a-dbt-project/command-line-interface/clean /reference/commands/clean 302 +/docs/running-a-dbt-project/command-line-interface/cmd-docs /reference/commands/cmd-docs 302 +/docs/running-a-dbt-project/command-line-interface/compile /reference/commands/compile 302 +/docs/running-a-dbt-project/command-line-interface/debug /reference/commands/debug 302 +/docs/running-a-dbt-project/command-line-interface/deps /reference/commands/deps 302 +/docs/running-a-dbt-project/command-line-interface/exit-codes /reference/exit-codes 302 +/docs/running-a-dbt-project/command-line-interface/global-cli-flags /reference/global-cli-flags 302 +/docs/running-a-dbt-project/command-line-interface/init /reference/commands/init 302 +/docs/running-a-dbt-project/command-line-interface/list /reference/commands/list 302 +/docs/running-a-dbt-project/command-line-interface/model-selection-syntax /reference/model-selection-syntax 302 +/docs/running-a-dbt-project/command-line-interface/rpc /reference/commands/rpc 302 +/docs/running-a-dbt-project/command-line-interface/run /reference/commands/run 302 +/docs/running-a-dbt-project/command-line-interface/run-operation /reference/commands/run-operation 302 +/docs/running-a-dbt-project/command-line-interface/seed /reference/commands/seed 302 +/docs/running-a-dbt-project/command-line-interface/snapshot /reference/commands/snapshot 302 +/docs/running-a-dbt-project/command-line-interface/source /reference/commands/source 302 +/docs/running-a-dbt-project/command-line-interface/test /reference/commands/test 302 +/docs/running-a-dbt-project/command-line-interface/version /reference/global-cli-flags#version 302 +/docs/running-a-dbt-project/using-the-command-line-interface /docs/running-a-dbt-project/using-the-cli 302 +/docs/running-a-dbt-project/using-the-command-line-interface/centos /dbt-cli/installation-guides/centos 302 +/docs/running-a-dbt-project/using-the-command-line-interface/configure-your-profile /dbt-cli/configure-your-profile 302 +/docs/running-a-dbt-project/using-the-command-line-interface/install-from-source /dbt-cli/installation-guides/install-from-source 302 +/docs/running-a-dbt-project/using-the-command-line-interface/installation /dbt-cli/installation 302 +/docs/running-a-dbt-project/using-the-command-line-interface/macos /dbt-cli/installation-guides/macos 302 +/docs/running-a-dbt-project/using-the-command-line-interface/ubuntu-debian /dbt-cli/installation-guides/ubuntu-debian 302 +/docs/running-a-dbt-project/using-the-command-line-interface/windows /dbt-cli/installation-guides/windows 302 +/docs/running-dbt-in-production /docs/running-a-dbt-project/running-dbt-in-production 302 +/docs/schema /docs/writing-code-in-dbt/jinja-context/schema 302 +/docs/schemas /docs/writing-code-in-dbt/jinja-context/schemas 302 +/docs/schemayml-files /reference/declaring-properties 302 +/docs/seed /reference/commands/seed 302 +/docs/seeds /docs/building-a-dbt-project/seeds 302 +/docs/setting-up-enterprise-sso-with-azure-active-directory /docs/dbt-cloud/dbt-cloud-enterprise/setting-up-enterprise-sso-with-azure-active-directory 302 +/docs/setting-up-snowflake-sso /docs/dbt-cloud/dbt-cloud-enterprise/setting-up-enterprise-snowflake-oauth 302 +/docs/setting-up-sso-with-google-gsuite /docs/dbt-cloud/dbt-cloud-enterprise/setting-up-sso-with-google-gsuite 302 +/docs/setting-up-sso-with-okta /docs/dbt-cloud/dbt-cloud-enterprise/setting-up-sso-with-okta 302 +/docs/slack-rules-of-the-road /docs/contributing/slack-rules-of-the-road 302 +/docs/snapshot /reference/commands/snapshot 302 +/docs/snapshots /docs/building-a-dbt-project/snapshots 302 +/docs/snowflake-configs /reference/resource-configs/snowflake-configs 302 +/docs/source /reference/commands/source 302 +/docs/statement-blocks /docs/writing-code-in-dbt/jinja-context/statement-blocks 302 +/docs/supported-databases/profile-bigquery /reference/bigquery-profile 302 +/docs/supported-databases/profile-mssql /reference/mssql-profile 302 +/docs/supported-databases/profile-postgres /reference/postgres-profile 302 +/docs/supported-databases/profile-presto /reference/presto-profile 302 +/docs/supported-databases/profile-redshift /reference/redshift-profile 302 +/docs/supported-databases/profile-snowflake /reference/snowflake-profile 302 +/docs/supported-databases/profile-spark /reference/spark-profile 302 +/docs/tags /reference/resource-configs/tags 302 +/docs/target /docs/writing-code-in-dbt/jinja-context/target 302 +/docs/test /reference/commands/test 302 +/docs/testing /docs/building-a-dbt-project/tests 302 +/docs/testing-and-documentation /docs/building-a-dbt-project/tests 302 +/docs/the-dbt-ide /docs/dbt-cloud/cloud-ide/the-dbt-ide 302 +/docs/this /docs/writing-code-in-dbt/jinja-context/this 302 +/docs/tojson /docs/writing-code-in-dbt/jinja-context/tojson 302 +/docs/ubuntu-debian /dbt-cli/installation 302 +/docs/use-an-existing-project /docs/building-a-dbt-project/dbt-projects/use-an-existing-project 302 +/docs/using-custom-aliases /docs/building-a-dbt-project/building-models/using-custom-aliases 302 +/docs/using-custom-database /docs/building-a-dbt-project/building-models/using-custom-databases 302 +/docs/using-custom-schemas /docs/building-a-dbt-project/building-models/using-custom-schemas 302 +/docs/using-dbt-cloud /docs/dbt-cloud/using-dbt-cloud 302 +/docs/using-jinja /guides/getting-started/learning-more/using-jinja 302 +/docs/using-operations /docs/building-a-dbt-project/hooks-operations 302 +/docs/using-sources /docs/building-a-dbt-project/using-sources 302 +/docs/using-sql-headers /reference/resource-configs/sql_header 302 +/docs/using-the-command-line-interface /docs/running-a-dbt-project/using-the-cli 302 +/docs/using-the-dbt-ide /docs/running-a-dbt-project/using-the-dbt-ide 302 +/docs/using-variables /docs/building-a-dbt-project/building-models/using-variables 302 +/docs/var /docs/writing-code-in-dbt/jinja-context/var 302 +/docs/version /reference/global-cli-flags#version 302 +/docs/videos /guides/legacy/videos 302 +/docs/windows /dbt-cli/installation 302 +/docs/writing-code-in-dbt/class-reference /reference/dbt-classes 302 +/docs/writing-code-in-dbt/extending-dbts-programming-environment/creating-new-materializations /guides/legacy/creating-new-materializations 302 +/docs/writing-code-in-dbt/extending-dbts-programming-environment/custom-schema-tests /guides/legacy/writing-custom-schema-tests 302 +/docs/writing-code-in-dbt/getting-started-with-jinja /docs/building-a-dbt-project/jinja-macros 302 +/docs/writing-code-in-dbt/jinja-context/adapter /reference/dbt-jinja-functions/adapter 302 +/docs/writing-code-in-dbt/jinja-context/as_text /reference/dbt-jinja-functions/as_text 302 +/docs/writing-code-in-dbt/jinja-context/builtins /reference/dbt-jinja-functions/builtins 302 +/docs/writing-code-in-dbt/jinja-context/config /reference/dbt-jinja-functions/config 302 +/docs/writing-code-in-dbt/jinja-context/dbt-project-yml-context /reference/dbt-jinja-functions/dbt-project-yml-context 302 +/docs/writing-code-in-dbt/jinja-context/dbt_version /reference/dbt-jinja-functions/dbt_version 302 +/docs/writing-code-in-dbt/jinja-context/debug-method /reference/dbt-jinja-functions/debug-method 302 +/docs/writing-code-in-dbt/jinja-context/doc /reference/dbt-jinja-functions/doc 302 +/docs/writing-code-in-dbt/jinja-context/env_var /reference/dbt-jinja-functions/env_var 302 +/docs/writing-code-in-dbt/jinja-context/exceptions /reference/dbt-jinja-functions/exceptions 302 +/docs/writing-code-in-dbt/jinja-context/execute /reference/dbt-jinja-functions/execute 302 +/docs/writing-code-in-dbt/jinja-context/flags /reference/dbt-jinja-functions/flags 302 +/docs/writing-code-in-dbt/jinja-context/fromjson /reference/dbt-jinja-functions/fromjson 302 +/docs/writing-code-in-dbt/jinja-context/fromyaml /reference/dbt-jinja-functions/fromyaml 302 +/docs/writing-code-in-dbt/jinja-context/graph /reference/dbt-jinja-functions/graph 302 +/docs/writing-code-in-dbt/jinja-context/invocation_id /reference/dbt-jinja-functions/invocation_id 302 +/docs/writing-code-in-dbt/jinja-context/log /reference/dbt-jinja-functions/log 302 +/docs/writing-code-in-dbt/jinja-context/modules /reference/dbt-jinja-functions/modules 302 +/docs/writing-code-in-dbt/jinja-context/on-run-end-context /reference/dbt-jinja-functions/on-run-end-context 302 +/docs/writing-code-in-dbt/jinja-context/profiles-yml-context /reference/dbt-jinja-functions/profiles-yml-context 302 +/docs/writing-code-in-dbt/jinja-context/project_name /reference/dbt-jinja-functions/project_name 302 +/docs/writing-code-in-dbt/jinja-context/ref /reference/dbt-jinja-functions/ref 302 +/docs/writing-code-in-dbt/jinja-context/return /reference/dbt-jinja-functions/return 302 +/docs/writing-code-in-dbt/jinja-context/run_query /reference/dbt-jinja-functions/run_query 302 +/docs/writing-code-in-dbt/jinja-context/run_started_at /reference/dbt-jinja-functions/run_started_at 302 +/docs/writing-code-in-dbt/jinja-context/schema /reference/dbt-jinja-functions/schema 302 +/docs/writing-code-in-dbt/jinja-context/schemas /reference/dbt-jinja-functions/schemas 302 +/docs/writing-code-in-dbt/jinja-context/source /reference/dbt-jinja-functions/source 302 +/docs/writing-code-in-dbt/jinja-context/statement-blocks /reference/dbt-jinja-functions/statement-blocks 302 +/docs/writing-code-in-dbt/jinja-context/target /reference/dbt-jinja-functions/target 302 +/docs/writing-code-in-dbt/jinja-context/this /reference/dbt-jinja-functions/this 302 +/docs/writing-code-in-dbt/jinja-context/tojson /reference/dbt-jinja-functions/tojson 302 +/docs/writing-code-in-dbt/jinja-context/toyaml /reference/dbt-jinja-functions/toyaml 302 +/docs/writing-code-in-dbt/jinja-context/var /reference/dbt-jinja-functions/var 302 +/docs/writing-code-in-dbt/macros /docs/building-a-dbt-project/jinja-macros 302 +/docs/writing-code-in-dbt/using-jinja /guides/getting-started/learning-more/using-jinja 302 +/faqs/getting-help/ /guides/legacy/getting-help 302 +/migration-guide/upgrading-to-0-17-0 /guides/migration/versions 302 +/migration-guide/upgrading-to-0-18-0 /guides/migration/versions 302 +/reference/accounts /dbt-cloud/api 302 +/reference/api /dbt-cloud/api 302 +/reference/connections /dbt-cloud/api 302 +/reference/data-test-configs /reference/test-configs 302 +/reference/declaring-properties /reference/configs-and-properties 302 +/reference/dbt-artifacts /reference/artifacts/dbt-artifacts 302 +/reference/environments /dbt-cloud/api 302 +/reference/events /reference/events-logging 302 +/reference/jobs /dbt-cloud/api 302 +/reference/model-selection-syntax /reference/node-selection/syntax 302 +/reference/project-configs/on-run-end /reference/project-configs/on-run-start-on-run-end 302 +/reference/project-configs/on-run-start /reference/project-configs/on-run-start-on-run-end 302 +/reference/repositories /dbt-cloud/api 302 +/reference/resource-configs/post-hook /reference/resource-configs/pre-hook-post-hook 302 +/reference/resource-configs/pre-hook /reference/resource-configs/pre-hook-post-hook 302 +/reference/resource-properties/tags /reference/resource-configs/tags 302 +/reference/runs /dbt-cloud/api 302 +/reference/using-the-dbt-cloud-api /dbt-cloud/api 302 +https://tutorial.getdbt.com/* https://docs.getdbt.com/:splat 301! +/reference/model-selection-syntax/#test-selection-examples /reference/node-selection/test-selection-examples 302 +/docs/building-a-dbt-project/building-models/using-custom-database /docs/building-a-dbt-project/building-models/using-custom-databases 302 +/dbt-cloud/api /dbt-cloud/api-v2 302 +/reference/project-configs/source-paths /reference/project-configs/model-paths 302 +/reference/project-configs/data-paths /reference/project-configs/seed-paths 302 +/reference/project-configs/modules-paths /reference/project-configs/packages-install-path 302 +/docs/dbt-cloud/using-dbt-cloud/cloud-slack-notifications /docs/dbt-cloud/using-dbt-cloud/cloud-notifications 302 +/reference/warehouse-profiles/presto-profile /reference/profiles.yml 302 +/setting-up /guides/getting-started/getting-set-up/setting-up-bigquery 302 +/tutorial/setting-up /guides/getting-started 302 +/tutorial/test-and-document-your-project /guides/getting-started/building-your-first-project/test-and-document-your-project 302 +/tutorial/build-your-first-models /guides/getting-started/building-your-first-project/build-your-first-models 302 +/tutorial/deploy-your-project /guides/getting-started/building-your-first-project/schedule-a-job 302 +/tutorial/using-jinja /guides/getting-started/learning-more/using-jinja 302 +/tutorial/refactoring-legacy-sql /guides/getting-started/learning-more/refactoring-legacy-sql 302 +/tutorial/2b-create-a-project-dbt-cli.md /guides/getting-started/learning-more/getting-started-dbt-core 302 +/tutorial/create-a-project-dbt-cli /guides/getting-started/learning-more/getting-started-dbt-core 302 +/tutorial/2a-create-a-project-dbt-cloud.md /guides/getting-started 302 +/tutorial/create-a-project-dbt-cloud /guides/getting-started 302 /tutorial/getting-started /guides/getting-started 302 -/docs/dbt-cloud/cloud-changelog /docs/dbt-cloud/release-notes 302 +/docs/dbt-cloud/cloud-changelog /docs/dbt-cloud/release-notes 302 /faqs/all /docs/faqs 301! -/faqs/* /docs/faqs/:splat 301 -/tutorial/learning-more/* /guides/getting-started/learning-more/:splat 301 -/tutorial/getting-set-up/* /guides/getting-started/getting-set-up/:splat 301 -/tutorial/building-your-first-project/* /guides/getting-started/building-your-first-project/:splat 301 -/tutorial/refactoring-legacy-sql /guides/getting-started/learning-more/refactoring-legacy-sql 302 +/faqs/_ /docs/faqs/:splat 301 +/tutorial/learning-more/_ /guides/getting-started/learning-more/:splat 301 +/tutorial/getting-set-up/\_ /guides/getting-started/getting-set-up/:splat 301 +/tutorial/building-your-first-project/\* /guides/getting-started/building-your-first-project/:splat 301 +/tutorial/refactoring-legacy-sql /guides/getting-started/learning-more/refactoring-legacy-sql 302 /blog/change-data-capture-metrics /blog/change-data-capture 301 /blog/model-timing-tab /blog/how-we-shaved-90-minutes-off-model 301 + # supported data platforms page -/docs/profile /docs/supported-data-platforms 302 + +/docs/profile /docs/supported-data-platforms 302 /docs/available-adapters /docs/supported-data-platforms 302 -/docs/supported-databases /docs/supported-data-platforms 302 +/docs/supported-databases /docs/supported-data-platforms 302 + # migration and legacy guides -/docs/guides/migration-guide/upgrading-to-0-14-0 /guides/migration/versions 302 -/docs/guides/migration-guide/upgrading-to-0-15-0 /guides/migration/versions 302 -/docs/guides/migration-guide/upgrading-to-0-16-0 /guides/migration/versions 302 -/docs/guides/migration-guide/upgrading-to-0-17-0 /guides/migration/versions 302 -/docs/guides/migration-guide/upgrading-to-0-18-0 /guides/migration/versions 302 -/docs/guides/migration-guide/upgrading-to-0-19-0 /guides/migration/versions 302 -/docs/guides/migration-guide/upgrading-from-0-10-to-0-11 /guides/migration/versions 302 -/docs/guides/migration-guide/upgrading-to-014 /guides/migration/versions 302 -/docs/upgrading-to-014 /guides/migration/versions 302 -/docs/upgrading-to-0-14-1 /guides/migration/versions 302 -/docs/upgrading-to-0-16-0 /guides/migration/versions 302 -/docs/guides/migration-guide/upgrading-to-0-20-0 /guides/migration/versions/upgrading-to-v0.20 302 -/docs/guides/migration-guide/upgrading-to-0-21-0 /guides/migration/versions/upgrading-to-v0.21 302 -/docs/guides/migration-guide/upgrading-to-1-0-0 /guides/migration/versions/upgrading-to-v1.0 302 -/docs/guides/migration-guide/upgrading-to-v1.0 /guides/migration/versions/upgrading-to-v1.0 302 -/docs/guides/getting-help /guides/legacy/getting-help 302 -/docs/guides/migration-guide/* /guides/migration/versions/:splat 301! -/docs/guides/* /guides/legacy/:splat 301! + +/docs/guides/migration-guide/upgrading-to-0-14-0 /guides/migration/versions 302 +/docs/guides/migration-guide/upgrading-to-0-15-0 /guides/migration/versions 302 +/docs/guides/migration-guide/upgrading-to-0-16-0 /guides/migration/versions 302 +/docs/guides/migration-guide/upgrading-to-0-17-0 /guides/migration/versions 302 +/docs/guides/migration-guide/upgrading-to-0-18-0 /guides/migration/versions 302 +/docs/guides/migration-guide/upgrading-to-0-19-0 /guides/migration/versions 302 +/docs/guides/migration-guide/upgrading-from-0-10-to-0-11 /guides/migration/versions 302 +/docs/guides/migration-guide/upgrading-to-014 /guides/migration/versions 302 +/docs/upgrading-to-014 /guides/migration/versions 302 +/docs/upgrading-to-0-14-1 /guides/migration/versions 302 +/docs/upgrading-to-0-16-0 /guides/migration/versions 302 +/docs/guides/migration-guide/upgrading-to-0-20-0 /guides/migration/versions/upgrading-to-v0.20 302 +/docs/guides/migration-guide/upgrading-to-0-21-0 /guides/migration/versions/upgrading-to-v0.21 302 +/docs/guides/migration-guide/upgrading-to-1-0-0 /guides/migration/versions/upgrading-to-v1.0 302 +/docs/guides/migration-guide/upgrading-to-v1.0 /guides/migration/versions/upgrading-to-v1.0 302 +/docs/guides/getting-help /guides/legacy/getting-help 302 +/docs/guides/migration-guide/_ /guides/migration/versions/:splat 301! +/docs/guides/_ /guides/legacy/:splat 301! docs/contributing/building-a-new-adapter /docs/contributing/adapter-development/3-building-a-new-adapter 302 docs/contributing/testing-a-new-adapter /docs/contributing/adapter-development/4-testing-a-new-adapter 302 docs/contributing/documenting-a-new-adapter /docs/contributing/adapter-development/5-documenting-a-new-adapter 302 -/docs/building-a-new-adapter /docs/contributing/adapter-development/3-building-a-new-adapter 301! +/docs/building-a-new-adapter /docs/contributing/adapter-development/3-building-a-new-adapter 301! /reference/warehouse-profiles/impala-profile /reference/warehouse-setups/impala-setup 302 /reference/warehouse-profiles/exasol-profile /reference/warehouse-setups/exasol-setup 302 /reference/warehouse-profiles/layer-profile /reference/warehouse-setups/layer-setup 302 @@ -377,3 +482,38 @@ docs/contributing/documenting-a-new-adapter /docs/contributing/adapter-developme /reference/warehouse-profiles/firebolt-profile /reference/warehouse-setups/firebolt-setup 302 /reference/warehouse-profiles/mysql-profile /reference/warehouse-setups/mysql-setup 302 /reference/warehouse-profiles/hive-profile /reference/warehouse-setups/hive-setup 302 + +# getting started guide +/guides/getting-started /docs/get-started/getting-started/overview 301 +/guides/getting-started/building-your-first-project /docs/get-started/getting-started/building-your-first-project/build-your-first-models 301 +/guides/getting-started/building-your-first-project/build-your-first-models /docs/get-started/getting-started/building-your-first-project/build-your-first-models 301 +/guides/getting-started/building-your-first-project/schedule-a-job /docs/get-started/getting-started/building-your-first-project/schedule-a-job 301 +/guides/getting-started/building-your-first-project/test-and-document-your-project /docs/get-started/getting-started/building-your-first-project/test-and-document-your-project 301 +/guides/getting-started/create-a-project /docs/get-started/getting-started/create-a-project 301 +/guides/getting-started/getting-set-up /docs/get-started/getting-started/set-up-dbt-cloud 301 +/guides/getting-started/getting-set-up/setting-up-bigquery /docs/get-started/getting-started/getting-set-up/setting-up-bigquery 301 +/guides/getting-started/getting-set-up/setting-up-databricks /docs/get-started/getting-started/getting-set-up/setting-up-databricks 301 +/guides/getting-started/getting-set-up/setting-up-redshift /docs/get-started/getting-started/getting-set-up/setting-up-redshift 301 +/guides/getting-started/getting-set-up/setting-up-snowflake /docs/get-started/getting-started/getting-set-up/setting-up-snowflake 301 +/guides/getting-started/getting-started /docs/get-started/getting-started/set-up-dbt-cloud 301 +/guides/getting-started/learning-more /docs/get-started/getting-started-dbt-core 301 +/guides/getting-started/learning-more/getting-started-dbt-core /docs/get-started/getting-started-dbt-core 301 +/guides/getting-started/learning-more/refactoring-legacy-sql /docs/get-started/learning-more/refactoring-legacy-sql 301 +/guides/getting-started/learning-more/using-jinja /docs/get-started/learning-more/using-jinja 301 +# ide ia redirects +/docs/dbt-cloud/cloud-ide/the-dbt-ide /docs/getting-started/dbt-cloud-features 301! +/docs/dbt-cloud/cloud-ide/handling-merge-conflicts /docs/collaborate/git/resolve-merge-conflicts 301! +/dbt-cloud/cloud-ide/viewing-docs-in-the-ide /docs/getting-started/develop-in-the-cloud 301! +/docs/dbt-cloud/cloud-ide/ide-beta /docs/getting-started/develop-in-the-cloud 301! +/docs/running-a-dbt-project/using-the-dbt-ide /docs/getting-started/develop-in-the-cloud 301! +/dbt-cloud/cloud-ide/the-ide-git-button /docs/collaborate/git/version-control-basics 301! + +# Community docs +/docs/contributing/long-lived-discussions-guidelines /community/resources/forum-guidelines 301 +/docs/guides/legacy/navigating-the-docs.md /community/contribute 301 +/community/writing-on-discourse/ /community/contributing/contributing-online-community 301 +/community/contributing/ /community/contribute 301 +/docs/contributing/contributor-license-agreements /community/resources/contributor-license-agreements 301 +/community/maintaining-a-channel /community/resources/maintaining-a-channel 301 +/docs/contributing/oss-expectations /community/resources/oss-expectations 301 +/docs/contributing/slack-rules-of-the-road /community/resources/slack-rules-of-the-road 301 diff --git a/contributing/adding-page-components.md b/contributing/adding-page-components.md index 1a43cbe8a81..5cbe8a6d471 100644 --- a/contributing/adding-page-components.md +++ b/contributing/adding-page-components.md @@ -1,6 +1,6 @@ ## Using warehouse components -You can use the following components to provide code snippets for each supported warehouse. You can see a real-life example in the docs page, "[Initialize your database](https://docs.getdbt.com/guides/getting-started/getting-set-up/setting-up-databricks#initialize-your-dbt-project)." +You can use the following components to provide code snippets for each supported warehouse. You can see a real-life example in the docs page, "[Initialize your database](/docs/get-started/getting-started/getting-set-up/setting-up-databricks#initialize-your-dbt-project)." Identify code by labeling with the warehouse names: diff --git a/website/blog/2019-05-01-how-we-structure-dbt-projects.md b/website/blog/2019-05-01-how-we-structure-dbt-projects.md index 361373ae9d5..8d3995d5ccc 100644 --- a/website/blog/2019-05-01-how-we-structure-dbt-projects.md +++ b/website/blog/2019-05-01-how-we-structure-dbt-projects.md @@ -106,7 +106,7 @@ Each staging directory contains at a minimum: * A `src_.yml` file which contains: * [Source](/docs/building-a-dbt-project/using-sources) definitions, tests, and documentation * A `stg_.yml` file which contains - * [Tests](/docs/building-a-dbt-project/tests) and [documentation](/docs/building-a-dbt-project/documentation) for models in the same directory + * [Tests](/docs/build/tests) and [documentation](/docs/building-a-dbt-project/documentation) for models in the same directory ``` ├── dbt_project.yml diff --git a/website/blog/2021-09-15-september-21-product-email.md b/website/blog/2021-09-15-september-21-product-email.md index 14985385bc4..9d8f6b76606 100644 --- a/website/blog/2021-09-15-september-21-product-email.md +++ b/website/blog/2021-09-15-september-21-product-email.md @@ -43,7 +43,7 @@ Give Jeremy a win and check out the [blog](http://blog.getdbt.com/getting-ready - Changelog and additional assets located [here.](https://docs.getdbt.com/docs/dbt-cloud/cloud-changelog?utm_campaign=Monthly%20Product%20Updates&utm_source=hs_email&utm_medium=email&_hsenc=p2ANqtz-8nIpohDBSr7SvpXrqY-5ONmnjdIgW0XMiAPkjQTb9Pgwt24nzqAWNX2Xgtj8LA0LrPoHpD)* - [DAG in the IDE](https://blog.getdbt.com/on-dags-hierarchies-and-ides/?utm_campaign=Monthly%20Product%20Updates&utm_source=hs_email&utm_medium=email&_hsenc=p2ANqtz-8nIpohDBSr7SvpXrqY-5ONmnjdIgW0XMiAPkjQTb9Pgwt24nzqAWNX2Xgtj8LA0LrPoHpD): We want users to have a frictionless experience when navigating between code and context. Embedding the DAG within the IDE makes investigating project structure a lot easier ![Screen Shot 2021-09-22 at 4.59.24 PM](https://hs-8698602.f.hubspotemail.net/hub/8698602/hubfs/Screen%20Shot%202021-09-22%20at%204.59.24%20PM.png?upscale=true&width=1120&upscale=true&name=Screen%20Shot%202021-09-22%20at%204.59.24%20PM.png) -- The [Metadata API](https://docs.getdbt.com/docs/dbt-cloud/dbt-cloud-api/metadata/metadata-overview?utm_campaign=Monthly%20Product%20Updates&utm_source=hs_email&utm_medium=email&_hsenc=p2ANqtz-8nIpohDBSr7SvpXrqY-5ONmnjdIgW0XMiAPkjQTb9Pgwt24nzqAWNX2Xgtj8LA0LrPoHpD): Now in GA! Assess data health with the metadata generated by recent dbt job runs +- The [Metadata API](https://docs.getdbt.com/docs/dbt-cloud-apis/metadata-api?utm_campaign=Monthly%20Product%20Updates&utm_source=hs_email&utm_medium=email&_hsenc=p2ANqtz-8nIpohDBSr7SvpXrqY-5ONmnjdIgW0XMiAPkjQTb9Pgwt24nzqAWNX2Xgtj8LA0LrPoHpD): Now in GA! Assess data health with the metadata generated by recent dbt job runs - [Dashboard Status Tiles](https://docs.getdbt.com/docs/dbt-cloud/using-dbt-cloud/cloud-dashboard-status-tiles?utm_campaign=Monthly%20Product%20Updates&utm_source=hs_email&utm_medium=email&_hsenc=p2ANqtz-8nIpohDBSr7SvpXrqY-5ONmnjdIgW0XMiAPkjQTb9Pgwt24nzqAWNX2Xgtj8LA0LrPoHpD): Embed this tile anywhere iFrames live to quickly check data freshness ## New Resources  diff --git a/website/blog/2021-10-15-october-21-product-update-email.md b/website/blog/2021-10-15-october-21-product-update-email.md index b08b6de77e5..f5a54ba3abd 100644 --- a/website/blog/2021-10-15-october-21-product-update-email.md +++ b/website/blog/2021-10-15-october-21-product-update-email.md @@ -64,7 +64,7 @@ The Model Timing tab in dbt Cloud highlights models taking particularly long to ### Things to Try 🛠️ - Nearly *500* dbt Cloud accounts are using CI. Want to know why? (or maybe... *how?*) Julia breaks it down in her [latest blog](https://blog.getdbt.com/adopting-ci-cd-with-dbt-cloud/?utm_campaign=Monthly%20Product%20Updates&utm_source=hs_email&utm_medium=email&_hsenc=p2ANqtz-_wfy8vfjMjwQ7o8TXEOVz-oXI35iVcVP1HtAvriVHfJoAd1IcsP-MCww6vJUDlvAfiuQjZ) and shares how to choose and configure continuous delivery or continuous deployment at your organization. -- Hex just [launched an integration](https://hex.tech/blog/dbt-integration?utm_campaign=Monthly%20Product%20Updates&utm_source=hs_email&utm_medium=email&_hsenc=p2ANqtz-_wfy8vfjMjwQ7o8TXEOVz-oXI35iVcVP1HtAvriVHfJoAd1IcsP-MCww6vJUDlvAfiuQjZ) with dbt! It uses the [dbt Cloud Metadata API](https://docs.getdbt.com/docs/dbt-cloud/dbt-cloud-api/metadata/metadata-overview?utm_campaign=Monthly%20Product%20Updates&utm_source=hs_email&utm_medium=email&_hsenc=p2ANqtz-_wfy8vfjMjwQ7o8TXEOVz-oXI35iVcVP1HtAvriVHfJoAd1IcsP-MCww6vJUDlvAfiuQjZ) to surface metadata from dbt right in Hex, letting you quickly get the context you need on things like data freshness without juggling multiple apps and browser tabs. Get started [here](https://docs.hex.tech/connecting-to-data/configuring-data-connections/dbt-integration?utm_campaign=Monthly%20Product%20Updates&utm_source=hs_email&utm_medium=email&_hsenc=p2ANqtz-_wfy8vfjMjwQ7o8TXEOVz-oXI35iVcVP1HtAvriVHfJoAd1IcsP-MCww6vJUDlvAfiuQjZ). +- Hex just [launched an integration](https://hex.tech/blog/dbt-integration?utm_campaign=Monthly%20Product%20Updates&utm_source=hs_email&utm_medium=email&_hsenc=p2ANqtz-_wfy8vfjMjwQ7o8TXEOVz-oXI35iVcVP1HtAvriVHfJoAd1IcsP-MCww6vJUDlvAfiuQjZ) with dbt! It uses the [dbt Cloud Metadata API](https://docs.getdbt.com/docs/dbt-cloud-apis/metadata-api?utm_campaign=Monthly%20Product%20Updates&utm_source=hs_email&utm_medium=email&_hsenc=p2ANqtz-_wfy8vfjMjwQ7o8TXEOVz-oXI35iVcVP1HtAvriVHfJoAd1IcsP-MCww6vJUDlvAfiuQjZ) to surface metadata from dbt right in Hex, letting you quickly get the context you need on things like data freshness without juggling multiple apps and browser tabs. Get started [here](https://docs.hex.tech/connecting-to-data/configuring-data-connections/dbt-integration?utm_campaign=Monthly%20Product%20Updates&utm_source=hs_email&utm_medium=email&_hsenc=p2ANqtz-_wfy8vfjMjwQ7o8TXEOVz-oXI35iVcVP1HtAvriVHfJoAd1IcsP-MCww6vJUDlvAfiuQjZ). - The [dbt-Rockset adapter](https://github.com/rockset/dbt-rockset?utm_campaign=Monthly%20Product%20Updates&utm_source=hs_email&utm_medium=email&_hsenc=p2ANqtz-_wfy8vfjMjwQ7o8TXEOVz-oXI35iVcVP1HtAvriVHfJoAd1IcsP-MCww6vJUDlvAfiuQjZ) (now in beta) just received a major update. It now supports View, Table, Incremental, and Ephemeral materializations to help you perform real-time data transformations on Rockset. Read more [here.](https://rockset.com/blog/real-time-data-transformations-dbt-rockset?utm_campaign=Monthly%20Product%20Updates&utm_source=hs_email&utm_medium=email&_hsenc=p2ANqtz-_wfy8vfjMjwQ7o8TXEOVz-oXI35iVcVP1HtAvriVHfJoAd1IcsP-MCww6vJUDlvAfiuQjZ). ### Things to Read 📚 diff --git a/website/blog/2021-11-22-dbt-labs-pr-template.md b/website/blog/2021-11-22-dbt-labs-pr-template.md index 7ecec933704..4460b27d494 100644 --- a/website/blog/2021-11-22-dbt-labs-pr-template.md +++ b/website/blog/2021-11-22-dbt-labs-pr-template.md @@ -70,7 +70,7 @@ Checking for things like modularity and 1:1 relationships between sources and st #### Validation of models: -This section should show something to confirm that your model is doing what you intended it to do. This could be a [dbt test](https://docs.getdbt.com/docs/building-a-dbt-project/tests) like uniqueness or not null, or could be an ad-hoc query that you wrote to validate your data. Here is a screenshot from a test run on a local development branch: +This section should show something to confirm that your model is doing what you intended it to do. This could be a [dbt test](/docs/build/tests) like uniqueness or not null, or could be an ad-hoc query that you wrote to validate your data. Here is a screenshot from a test run on a local development branch: ![test validation](/img/blog/pr-template-test-validation.png "dbt test validation") diff --git a/website/blog/2021-11-22-primary-keys.md b/website/blog/2021-11-22-primary-keys.md index 0467565ee28..84c92055eb0 100644 --- a/website/blog/2021-11-22-primary-keys.md +++ b/website/blog/2021-11-22-primary-keys.md @@ -51,7 +51,7 @@ In the days before testing your data was commonplace, you often found out that y ## How to test primary keys with dbt -Today, you can add two simple [dbt tests](https://docs.getdbt.com/docs/building-a-dbt-project/tests) onto your primary keys and feel secure that you are going to catch the vast majority of problems in your data. +Today, you can add two simple [dbt tests](/docs/build/tests) onto your primary keys and feel secure that you are going to catch the vast majority of problems in your data. Not surprisingly, these two tests correspond to the two most common errors found on your primary keys, and are usually the first tests that teams testing data with dbt implement: diff --git a/website/blog/2021-11-29-dbt-airflow-spiritual-alignment.md b/website/blog/2021-11-29-dbt-airflow-spiritual-alignment.md index 73eb4a510d9..7496f04f592 100644 --- a/website/blog/2021-11-29-dbt-airflow-spiritual-alignment.md +++ b/website/blog/2021-11-29-dbt-airflow-spiritual-alignment.md @@ -90,7 +90,7 @@ So instead of getting bogged down in defining roles, let’s focus on hard skill The common skills needed for implementing any flavor of dbt (Core or Cloud) are: * SQL: ‘nuff said -* YAML: required to generate config files for [writing tests on data models](/docs/building-a-dbt-project/tests) +* YAML: required to generate config files for [writing tests on data models](/docs/build/tests) * [Jinja](/guides/getting-started/learning-more/using-jinja): allows you to write DRY code (using [macros](/docs/building-a-dbt-project/jinja-macros), for loops, if statements, etc) YAML + Jinja can be learned pretty quickly, but SQL is the non-negotiable you’ll need to get started. diff --git a/website/blog/2021-12-05-how-to-build-a-mature-dbt-project-from-scratch.md b/website/blog/2021-12-05-how-to-build-a-mature-dbt-project-from-scratch.md index 00ed7ee35c8..7149f5a49b8 100644 --- a/website/blog/2021-12-05-how-to-build-a-mature-dbt-project-from-scratch.md +++ b/website/blog/2021-12-05-how-to-build-a-mature-dbt-project-from-scratch.md @@ -69,7 +69,7 @@ In addition to learning the basic pieces of dbt, we're familiarizing ourselves w If we decide not to do this, we end up missing out on what the dbt workflow has to offer. If you want to learn more about why we think analytics engineering with dbt is the way to go, I encourage you to read the [dbt Viewpoint](/docs/about/viewpoint)! -In order to learn the basics, we’re going to [port over the SQL file](/guides/getting-started/learning-more/refactoring-legacy-sql) that powers our existing "patient_claim_summary" report that we use in our KPI dashboard in parallel to our old transformation process. We’re not ripping out the old plumbing just yet. In doing so, we're going to try dbt on for size and get used to interfacing with a dbt project. +In order to learn the basics, we’re going to [port over the SQL file](/docs/get-started/learning-more/refactoring-legacy-sql) that powers our existing "patient_claim_summary" report that we use in our KPI dashboard in parallel to our old transformation process. We’re not ripping out the old plumbing just yet. In doing so, we're going to try dbt on for size and get used to interfacing with a dbt project. **Project Appearance** @@ -87,7 +87,7 @@ The most important thing we’re introducing when your project is an infant is t * Introduce modularity with [{{ ref() }}](/reference/dbt-jinja-functions/ref) and [{{ source() }}](/reference/dbt-jinja-functions/source) -* [Document](/docs/building-a-dbt-project/documentation) and [test](/docs/building-a-dbt-project/tests) your first models +* [Document](/docs/building-a-dbt-project/documentation) and [test](/docs/build/tests) your first models ![image alt text](/img/blog/building-a-mature-dbt-project-from-scratch/image_3.png) @@ -179,7 +179,7 @@ We've spent this level focused on deepening and optimizing our feature set — w **Key Outcomes** -* Formalize dbt’s relationship to BI with [exposures](/docs/building-a-dbt-project/exposures)! +* Formalize dbt’s relationship to BI with [exposures](/docs/build/exposures)! * Advanced use of metadata diff --git a/website/blog/2022-04-19-complex-deduplication.md b/website/blog/2022-04-19-complex-deduplication.md index be61eae643b..613b63c04b8 100644 --- a/website/blog/2022-04-19-complex-deduplication.md +++ b/website/blog/2022-04-19-complex-deduplication.md @@ -152,7 +152,7 @@ select * from filter_real_diffs > *What happens in this step? You check your data because you are thorough!* -Good thing dbt has already built this for you. Add a [unique test](https://docs.getdbt.com/docs/building-a-dbt-project/tests#generic-tests) to your YAML model block for your `grain_id` in this de-duped staging model, and give it a dbt test! +Good thing dbt has already built this for you. Add a [unique test](/docs/build/tests#generic-tests) to your YAML model block for your `grain_id` in this de-duped staging model, and give it a dbt test! ```yaml models: diff --git a/website/blog/2022-07-27-understanding-the-components-of-the-dbt-semantic-layer.md b/website/blog/2022-07-27-understanding-the-components-of-the-dbt-semantic-layer.md index afab89948c0..3db07f6f26a 100644 --- a/website/blog/2022-07-27-understanding-the-components-of-the-dbt-semantic-layer.md +++ b/website/blog/2022-07-27-understanding-the-components-of-the-dbt-semantic-layer.md @@ -51,7 +51,7 @@ The dbt Semantic layer is comprised of the following components[^2]: - **[`metric` node in dbt Core :](https://docs.getdbt.com/docs/building-a-dbt-project/metrics)** Similar to `models` or `sources` , this is a specific node type in dbt Core. It is the definition of a time-series aggregation over a table that supports zero or more dimensions. The resulting node is stored in the `manifest.json` just like `models` and referenced in the DAG. - **[`dbt_metrics` package:](https://github.com/dbt-labs/dbt_metrics)** this package provides macros that combine the version-controlled metric definition and query-time parameters (like dimensions, a time grain, and secondary calculations) to generate a SQL query which calculates the metric value. -- **[dbt Cloud Metadata API](https://docs.getdbt.com/docs/dbt-cloud/dbt-cloud-api/metadata/metadata-overview):** a GraphQL API which supports arbitrary queries over the metadata produced by dbt Cloud jobs. Contains metadata related to the accuracy, recency, configuration, and structure of the views and tables in the warehouse, as well as much more. +- **[dbt Cloud Metadata API](https://docs.getdbt.com/docs/dbt-cloud-apis/metadata-api):** a GraphQL API which supports arbitrary queries over the metadata produced by dbt Cloud jobs. Contains metadata related to the accuracy, recency, configuration, and structure of the views and tables in the warehouse, as well as much more. **New** diff --git a/website/blog/2022-08-31-august-product-update.md b/website/blog/2022-08-31-august-product-update.md index 5826db17a24..df326039f25 100644 --- a/website/blog/2022-08-31-august-product-update.md +++ b/website/blog/2022-08-31-august-product-update.md @@ -38,7 +38,7 @@ You’ll hear more in [Tristan’s keynote](https://coalesce.getdbt.com/agenda/k - **dbt_artifacts v1.2.0:** [Brooklyn Data Co just shipped a pretty significant re-write to the dbt_artifacts package](https://brooklyndata.co/blog/dbt-artifacts-v100). Capture all the metadata generated by dbt at the end of an invocation (project nodes, success rate, test results, etc), and store directly in Snowflake, Databricks, or BigQuery for immediate analysis. - **dbt YAML validator using JSON schema**: If you do any development in VS Code, [this repo unlocks autocomplete and validation for dbt’s YAML files](https://github.com/dbt-labs/dbt-jsonschema/). Find those tests that never ran because you messed up the indentation. *Not that that would ever happen to you.* -- **dbt Exposures for Hightouch**: [Exposures](https://docs.getdbt.com/docs/building-a-dbt-project/exposures) in dbt allow you to quickly see how downstream data applications are making use of your dbt models and sources. These don’t have to just represent dashboards in BI tools though — [you can now represent your Hightouch syncs as dbt exposures too](https://hightouch.com/blog/introducing-dbt-exposures-for-hightouch/). +- **dbt Exposures for Hightouch**: [Exposures](https://docs.getdbt.com/docs/build/exposures) in dbt allow you to quickly see how downstream data applications are making use of your dbt models and sources. These don’t have to just represent dashboards in BI tools though — [you can now represent your Hightouch syncs as dbt exposures too](https://hightouch.com/blog/introducing-dbt-exposures-for-hightouch/). - **Are you a certified dbt developer?** We recently launched our new [Analytics Engineering certification](https://www.getdbt.com/certifications/analytics-engineer-certification-exam/) program, and would love to hear what you think. We personally dug [this writeup from Charles Verleyen](https://medium.com/astrafy/dbt-exam-feedback-8d07a0593648) on what to expect, and exactly how much experience/prep he recommends. **Things to read 📚** diff --git a/website/blog/2022-09-28-analyst-to-ae.md b/website/blog/2022-09-28-analyst-to-ae.md index b6d03b81782..b89638520d9 100644 --- a/website/blog/2022-09-28-analyst-to-ae.md +++ b/website/blog/2022-09-28-analyst-to-ae.md @@ -111,7 +111,7 @@ The analyst caught the issue because they have the appropriate context to valida An analyst is able to identify which areas do *not* need to be 100% accurate, which means they can also identify which areas *do* need to be 100% accurate. -> dbt makes it very quick to add [data quality tests](https://docs.getdbt.com/docs/building-a-dbt-project/tests). In fact, it’s so quick, that it’ll take an analyst longer to write up what tests they want than it would take for an analyst to completely finish coding them. +> dbt makes it very quick to add [data quality tests](/docs/build/tests). In fact, it’s so quick, that it’ll take an analyst longer to write up what tests they want than it would take for an analyst to completely finish coding them. When data quality issues are identified by the business, we often see that analysts are the first ones to be asked: diff --git a/website/blog/ctas.yml b/website/blog/ctas.yml index 21a02255400..2267b05a42a 100644 --- a/website/blog/ctas.yml +++ b/website/blog/ctas.yml @@ -9,4 +9,4 @@ header: "Just Getting Started?" subheader: Check out guides on getting your warehouse set up and connected to dbt Cloud. button_text: Learn more - url: https://docs.getdbt.com/guides/getting-started/getting-set-up + url: https://docs.getdbt.com/docs/get-started/getting-started/overview diff --git a/website/dbt-versions.js b/website/dbt-versions.js index f1efcfa2cc2..008f81cedcd 100644 --- a/website/dbt-versions.js +++ b/website/dbt-versions.js @@ -26,10 +26,6 @@ exports.versions = [ ] exports.versionedPages = [ - { - "page": "docs/building-a-dbt-project/building-models/python-models", - "firstVersion": "1.3", - }, { "page": "reference/dbt-jinja-functions/set", "firstVersion": "1.2", diff --git a/website/docs/community/contribute.md b/website/docs/community/contribute.md new file mode 100644 index 00000000000..037edf0e430 --- /dev/null +++ b/website/docs/community/contribute.md @@ -0,0 +1,47 @@ +--- +title: Become a contributor +id: contribute +--- + +
+ +## Want to get involved? Start here + +The dbt Community predates dbt Labs as an organization and harkens back to the days when a scrappy analytics consultancy of a few [pissed off data analysts]() started hacking together an open source project around which gathered a community that would change how the world uses data. + +The dbt Community exists to allow analytics practitioners to share their knowledge, help others and collectively to drive forward the discipline of analytics engineering. This is something that can’t be done by any one individual or any one organization - to create a new discipline is necessarily a community effort. The only reason that dbt has become as widespread as it has is because people like you choose to get involved and share your knowledge. Contributing to the community can also be a great way to learn new skills, build up a public portfolio and make friends with other practitioners. + +There are opportunities here for everyone to get involved, whether you are just beginning your analytics engineering journey or you are a seasoned data professional. Contributing isn’t about knowing all of the answers, it’s about learning things together. + +Below you’ll find a sampling of the ways to get involved. There are a lot of options but these are ultimately just variations on the theme of sharing knowledge with the broader community. + +
+ + + + + + + + + +
+
diff --git a/website/docs/community/contributing/contributing-coding.md b/website/docs/community/contributing/contributing-coding.md new file mode 100644 index 00000000000..9157eb6b2ec --- /dev/null +++ b/website/docs/community/contributing/contributing-coding.md @@ -0,0 +1,59 @@ +--- +title: "Coding contributions" +id: "contributing-coding" +--- + +### Contribute to dbt Packages + +#### Overview + +[dbt Packages](https://docs.getdbt.com/docs/building-a-dbt-project/package-management) are the easiest way for analytics engineers to get involved with contributing code to the dbt Community, because dbt Packages are just standard [dbt Projects](https://docs.getdbt.com/docs/building-a-dbt-project/projects). If you can create a dbt Project, write a macro, and ref a model: you can make a dbt Package. Packages function much like libraries do in other programming languages. They allow for prewritten, modularized development of code to solve common problems in analytics engineering. You can view all dbt Packages on the [dbt Package Hub](https://hub.getdbt.com/). + +#### Contribution opportunities + +- Create a new package for the dbt Package Hub. This might be a new set of macros or tests that have been useful to you in your projects, a set of models for engaging with a commonly used datasource or anything else that can be done from within a dbt project. +- Improve an existing package: Alternatively you can help improve an existing package. This can be done by creating and engaging with Issues or by functionality to address an existing issue via opening a PR. + +#### Sample contributions + +- [dbt Expectations](https://hub.getdbt.com/calogica/dbt_expectations/latest/) +- [dbt Artifacts](https://hub.getdbt.com/brooklyn-data/dbt_artifacts/latest/) + +#### Get started + +- Use packages in your own projects! The best way to know how to improve a package is to use it in a production environment then look for ways it can be modified or improved. +- Read the following resources on package development: + - [So You Want to Build a dbt Package](https://docs.getdbt.com/blog/so-you-want-to-build-a-package) + - [Package Best Practices](https://github.com/dbt-labs/hubcap/blob/main/package-best-practices.md) +- Need help: Visit #package-ecosystem in the dbt Slack + +### Contribute to dbt open source software + +#### Overview + +dbt Core, adapters, tooling, and the sites powering the Package Hub and Developer Hub are all vibrant open source projects. Unlike dbt Packages, contributing code to these projects typically requires some working knowledge of programming languages outside of SQL and Jinja, but the supportive community around these repositories can help you advance those skills. Even without contributing code, there are many ways to be part of open source development in these projects, detailed below. You can find a curated list of the most active OSS projects that dbt Labs supports [here](/community/resources/oss-projects). + +#### Contribution opportunities + +There are three primary ways to contribute to the dbt OSS projects. We’ll use dbt Core as an example, as it’s the most active and mature OSS project we support, and a great place to start for newcomers: + +- [Open an issue](https://github.com/dbt-labs/dbt-core/issues/new/choose) to suggest an improvement or give feedback. +- Comment / engage on existing [issues](https://github.com/dbt-labs/dbt-core/issues) or [discussions](https://github.com/dbt-labs/dbt-core/discussions). This could be upvoting issues that would be helpful for your organization, commenting to add nuance to a feature request or sharing how a feature would impact your dbt usage. +- Create a pull request that resolves an open Issue. This involves writing the code and tests that add the feature/resolve the bug described in an Issue, and then going through the code review process asynchronously with a dbt Labs engineer. + +#### Sample contributions + +- Check out [this issue](https://github.com/dbt-labs/dbt-core/issues/3612) about improving error messages and [the PR that the community contributed to fix it](https://github.com/dbt-labs/dbt-core/pull/3703). +- From the above issue [another issue was generated](https://github.com/dbt-labs/dbt-bigquery/issues/202) to change not just the error message, but improve the behavior. This is the virtuous cycle of open source community development! Bit by bit we, the community, craft the tool to better fit our needs. + +#### Get started + +- Read the dbt Core [contribution guide](https://github.com/dbt-labs/dbt-core/blob/main/CONTRIBUTING.md) and the [Open Source Software Expectations](https://docs.getdbt.com/docs/contributing/oss-expectations). +- If contributing to dbt Core, find an issue labeled “[good first issue](https://github.com/dbt-labs/dbt-core/issues?q=is%3Aopen+is%3Aissue+label%3Agood_first_issue)”, or look for similar labels on other repositories. If in doubt, also feel free to ask the maintainers for a good first issue, they’ll be excited to welcome you! + +#### Need help? + +The following channels in the dbt Community Slack are a great place to ask questions: + +- #dbt-core-development +- #adapter-ecosystem diff --git a/website/docs/community/contributing/contributing-online-community.md b/website/docs/community/contributing/contributing-online-community.md new file mode 100644 index 00000000000..400a4dadc32 --- /dev/null +++ b/website/docs/community/contributing/contributing-online-community.md @@ -0,0 +1,46 @@ +--- +title: "Online community building" +id: "contributing-online-community" +--- + +### Maintaining a channel in the dbt Community Slack + +#### Overview + +The dbt Slack is the place for real time conversations with the dbt Community. Slack channels exist for specific locations, tools, industries and methodologies. In order to make sure that every channel has dedicated attention from a committed community member, we have Community Maintainers who oversee the discussion in particular channels. + +#### Contribution opportunities + +Every channel can benefit from people who are engaged and committed to making it a more interesting place to hang out! If there's a channel that you're interested in, spend time there. + +For new channels that you'd like to create and maintain, post a message in the #channel-requests channel. + +#### Sample contributions: + +- Karen Hsieh's [contributions](https://getdbt.slack.com/archives/C02TU2DSKND/p1661483529756289) to the #local-taipei channel are a fantastic example to learn from. + +#### Get started + +- Read the guide to [Maintaining a Slack Channel](community/resources/maintaining-a-channel) + +### Participating on the Community Forum + +#### Overview + +[The dbt Community Forum](https://discourse.getdbt.com) is the preferred platform for support questions as well as a space for long-lived discussions about dbt, analytics engineering, and the analytics profession. It's a place for us to build up a long-lasting knowledge base around the common challenges, opportunities, and patterns we work with every day. + +#### Contribution opportunities + +Participate in the Forum by asking and answering questions. These discussions are what allows us to find gaps in our best practices, documentation and other recommendation, as well as to get folks onboarded and understanding dbt. Remember, it’s a mitzvah to answer a question. + +If you see a great question or answer, be generous with your 💜 reactions. Click the Solved button when your question is answered, so others can benefit. + +#### Sample contributions + +- An analytics engineer wrote about [how they modified dbt to automatically put models into the correct schema](https://discourse.getdbt.com/t/extracting-schema-and-model-names-from-the-filename/575) based on their filename. +- Here's [an example of the supportive, thorough answers](https://discourse.getdbt.com/t/is-it-possible-to-have-multiple-files-with-the-same-name-in-dbt/647) you can receive when you take the time to ask a question well. + +#### Get started + +- Read the [Community Forum Guidelines](/community/resources/forum-guidelines) to understand what topics are a good fit and why this space is important in building long-term community knowledge. +- Head over to the “[Help](https://discourse.getdbt.com/c/help/19)” section of the forum and look for areas to hop in! You don’t need to know the exact answer to a question to be able to provide a helpful pointer. diff --git a/website/docs/community/contributing/contributing-realtime-events.md b/website/docs/community/contributing/contributing-realtime-events.md new file mode 100644 index 00000000000..36d1c9e2339 --- /dev/null +++ b/website/docs/community/contributing/contributing-realtime-events.md @@ -0,0 +1,47 @@ +--- +title: "Realtime event participation" +id: "contributing-realtime-events" +--- + +### Speak at a Meetup + +#### Overview + +Meetups are a place to engage and interact with your fellow dbt Community members (in person when possible but sometimes online). We’ve got 21 Meetups in 16 countries. + +#### Contribution opportunities + +Give a talk! Meetups are all about sharing your knowledge with other analytics practitioners. Have you recently solved a problem in your data organization, published a package or generally done something of interest to the dbt Community? Meet your local pals and share what you’ve done at a meetup. + +#### Sample contributions + +- Take a look at [the slides](https://docs.google.com/presentation/d/1iqVjzxxRggMnRoI40ku88miDKw795djpKV_v4bbLpPE/edit#slide=id.g553a984de0_0_19) and [watch the video](https://www.youtube.com/watch?v=BF7HH8JDUS0) from Kenny Ning's 2020 Meetup talk on predicting customer conversions with dbt and ML for Better.com. +- Dig into [the deck](https://docs.google.com/presentation/d/1wE8NSkFPLFKGQ8fvFUUKoZFVoUhws_FhFip-9mDhoPU/edit#slide=id.p) and [the video](https://www.youtube.com/watch?v=VhH614WVufM) from Bowery Farmings talk on migrating dbt models from Redshift to Snowflake. + +#### Get Started + +- Read [How to Deliver a Fantastic Meetup Talk](/community/resources/speaking-at-a-meetup). +- Find a [Meetup near you](https://www.meetup.com/pro/dbt/), start attending and let the organizers know you are interested! + +### Speak at Coalesce + +#### Overview + +[Coalesce](https://coalesce.getdbt.com/) is the annual analytics engineering conference hosted by dbt Labs. While Meetups are focused on sharing knowledge with a specific local hub of the Community - Coalesce is the way to share ideas with everyone. Each year we gather together, take stock of what we’ve learned and pool our best ideas about analytics. + +#### Contribution opportunities + +- Attend Coalesce: + - Coalesce is the once a year gathering for analytics engineers. Whether you choose to join online or at one of our in-person events, attending Coalesce is the best way to get an immersive experience of what the dbt Community is like. +- Speak at Coalesce! + - We’d love to hear what you’ve been working on, thinking about and dreaming up in the analytics engineering space. Coalesce talks can be forward looking views on the industry, deep dives into particular technical solutions or personal stories about your journey in data. + +#### Sample contributions + +- [Run Your Data Team as a Product Team](https://www.getdbt.com/coalesce-2020/run-your-data-team-as-a-product-team/) +- [Tailoring dbt's incremental_strategy to Artsy's data needs](https://www.getdbt.com/coalesce-2021/tailoring-dbts-incremental-strategy-to-artsys-data-needs/) + +#### Get started + +- If registrations are open register on the [Coalesce website](https://coalesce.getdbt.com/) +- Join #coalesce-updates on the dbt Community Slack diff --git a/website/docs/community/contributing/contributing-writing.md b/website/docs/community/contributing/contributing-writing.md new file mode 100644 index 00000000000..86635e651c7 --- /dev/null +++ b/website/docs/community/contributing/contributing-writing.md @@ -0,0 +1,55 @@ +--- +title: "Writing contributions" +id: "contributing-writing" +--- + +### Contribute to the product documentation + +#### Overview + +The [dbt Product Documentation](https://docs.getdbt.com/docs/introduction) sits at the heart of how people learn to use and engage with dbt. From explaining dbt to newcomers to providing references for advanced functionality and APIs, the product docs are a frequent resource for _every_ dbt Developer. + +#### Contribution opportunities + +We strive to create pathways that inspire you to learn more about dbt and enable you to continuously improve the way you solve data problems. We always appreciate the vigilance of the Community helping us to accurately represent the functionality and capabilities of dbt. You can participate by: + +- [Opening an issue](https://github.com/dbt-labs/docs.getdbt.com/issues/new/choose) when you see something that can be fixed, whether it’s large or small. +- Creating a PR when you see something you want to fix, or to address an existing issue. You can do this by clicking **Edit this page** at the bottom of any page on [docs.getdbt.com](http://docs.getdbt.com). + +#### Sample contributions + +We appreciate these contributions because they contain context in the original post (OP) that helps us understand their relevance. The also add value to the docs, even in small ways! + +- Larger contribution: https://github.com/dbt-labs/docs.getdbt.com/pull/1898 +- Smaller contribution: https://github.com/dbt-labs/docs.getdbt.com/pull/1114 + +#### Get started + +- You can contribute to [docs.getdbt.com](http://docs.getdbt.com) by looking at our repository’s [README](https://github.com/dbt-labs/docs.getdbt.com#readme) or clicking **Edit this page** at the bottom of most pages at docs.getdbt.com. +- Read the [OSS Expectations](https://docs.getdbt.com/docs/contributing/oss-expectations). +- Find an issue labeled “[good first issue](https://github.com/dbt-labs/docs.getdbt.com/issues?q=is%3Aopen+is%3Aissue+label%3A%22good+first+issue%22+).” +- Need help: Visit #community-writers on the Community Slack or mention `@dbt-labs/product-docs` in a pull request or issue comment. + +### Write a Developer Blog Post + +#### Overview + +The [dbt Developer Blog](https://docs.getdbt.com/blog) is the place for analytics practitioners to talk about _what it’s like to do data work right now._ This is the place to share tips and tricks, hard won knowledge and stories from the trenches with the dbt Community. + +#### Contribution opportunities + +We want to hear your stories! Did you recently solve a cool problem, discover an interesting bug or lead an organizational change? Come tell the story on the dbt Developer Blog. + +#### Sample contributions + +- [Founding an Analytics Engineering Team From Scratch](https://docs.getdbt.com/blog/founding-an-analytics-engineering-team-smartsheet#our-own-take-on-data-mesh) +- [Tackling the Complexity of Joining Snapshots](https://docs.getdbt.com/blog/joining-snapshot-complexity) + +#### Get started + +- [Read the contribution guide](https://github.com/dbt-labs/docs.getdbt.com/blob/current/contributing/developer-blog.md) +- [Open up an issue with your idea for a post](https://github.com/dbt-labs/docs.getdbt.com/issues/new?assignees=&labels=content%2Cdeveloper+blog&template=contribute-to-developer-blog.yml) + +#### Need help? + +Visit #community-writers in the dbt Community Slack diff --git a/website/docs/community/join.md b/website/docs/community/join.md new file mode 100644 index 00000000000..254a1a8547c --- /dev/null +++ b/website/docs/community/join.md @@ -0,0 +1,53 @@ +--- +title: Join the Community +id: join +--- + +
+ +Want to learn how organizations around the world are tackling the biggest challenges in data while making new friends from the best analytics teams? Join the dbt Community — data practitioners’ favorite place to learn new skills, keep on top of industry trends, and forge connections. + +
+ + + + + + + + + + + + + +
+
diff --git a/website/docs/community/resources/code-of-conduct.md b/website/docs/community/resources/code-of-conduct.md new file mode 100644 index 00000000000..7af49279e83 --- /dev/null +++ b/website/docs/community/resources/code-of-conduct.md @@ -0,0 +1,165 @@ +--- +title: "Code of Conduct" +id: "code-of-conduct" +--- + +# dbt Community Code of Conduct + +dbt has a supportive, active community of thousands of smart, kind, and helpful people who share a commitment to elevating the analytics profession. + +You can get involved in the dbt community by connecting at [events](/community/events), getting or giving help in any of our many channels, contributing to dbt or a dbt package, and many other ways. + +People genuinely love this community, and we are committed to maintaining the spirit of it. As such have written this Code of Conduct to help all participants understand how to best participate in our community. + +The Code of Conduct applies to all dbt Community spaces both online and off. This includes: Slack, Discourse, code repositories (dbt Core, dbt packages etc), Office Hours and Meetups. There are some guidelines specific to particular forums (listed below). Participants are responsible for knowing and abiding by this Code of Conduct. + +This Code of Conduct has three sections: + +- **dbt Community Values:** These values apply to all of our community spaces, and all of our guidelines are based on these values. +- **Forum-specific guidelines**: These guidelines explain some of the cultural norms that apply to specific forums. +- **Anti-harassment policy:** We are dedicated to providing a harassment-free experience for everyone in our community — here, we outline exactly what that means. + +We appreciate your support in continuing to build a community we’re all proud of. + +— The dbt Community Admin Team. + +## dbt Community Values + +### Be respectful. + +We want everyone to have a fulfilling and positive experience in the dbt Community and we are continuously grateful in your help ensuring that this is the case. + +Be courteous, respectful, and polite to fellow community members. Generally, don’t be a jerk. + +Be considerate of others’ time — many people in the community generously give their time for free. + +Ways to demonstrate this value: + +- Take the time to write bug reports well ([example](https://github.com/fishtown-analytics/dbt/issues/2370)) +- Thank people if they help solve a problem. + +### Be you. + +Some developer communities allow and even encourage anonymity — we prefer it when people identify themselves clearly. It helps to build empathy, and form relationships. + +Ways to demonstrate this value: + +- Update your profile on any dbt Community forums to include your name, and a clear picture. On Slack, use the “what I do” section to add your role title and current company +- Write in your own voice, and offer your own advice, rather than speaking in your company’s marketing or support voice. + +### Encourage diversity and participation. + +People with different mindsets and experiences, working together, create better outcomes. This includes diversity of race and gender, as well as the diversity of academic and career backgrounds, socio-economic backgrounds, geographic backgrounds, ideologies, and interests. + +Ways to demonstrate this value: + +- Make everyone in our community feel welcome, regardless of their background, and do everything possible to encourage participation in our community. +- Demonstrate empathy for a community member’s experience — not everyone comes from the same career background, so adjust answers accordingly. +- If you are sourcing speakers for events, put in additional effort to find speakers from underrepresented groups. + +### Create more value than you capture. + +Each community member should strive to create more value in the community than they capture. This is foundational to being a community. + +Ways to demonstrate this value: + +- Contribute to dbt or a dbt package +- Participate in discussions on Slack and Discourse +- Share things you have learned on Discourse +- Host events + +### Be curious. + +Always ask yourself “why?” and strive to be continually learning. + +Ways to demonstrate this value: + +- Try solving a problem yourself before asking for help, e.g. rather than asking “what happens when I do X”, experiment and observe the results! +- When asking questions, explain the “why” behind your decisions, e.g. “I’m trying to solve X problem, by writing Y code. I’m getting Z problem” +- When helping someone else, explain why you chose that solution, or if no solution exists, elaborate on the reason for that, e.g. “That’s not possible in dbt today — but here’s a workaround / check out this GitHub issue for a relevant discussion” + +## Guidelines + +### Participating in Slack + +dbt Slack is where the dbt community hangs out, discusses issues, and troubleshoots problems together. It is not a support service — please do not treat it like one. + +We also have a number of cultural norms in our Slack community. You must read and agree to the rules before joining Slack, but you can also find them [here](/community/resources/slack-rules-of-the-road/). + +As a short summary: + +- [Rule 1: Be respectful](/community/resources/slack-rules-of-the-road/#rule-1-be-respectful) +- [Rule 2: Use the right channel](/community/resources/slack-rules-of-the-road/#rule-2-use-the-right-channel) +- [Rule 3: Put effort into your question](/community/resources/slack-rules-of-the-road/#rule-3-put-effort-into-your-question) +- [Rule 4: Do not double-post](/community/resources/slack-rules-of-the-road/#rule-4-do-not-double-post) +- [Rule 5: Keep it in public channels](/community/resources/slack-rules-of-the-road/#rule-5-keep-it-in-public-channels) +- [Rule 6: Do not solicit members of our Slack](/community/resources/slack-rules-of-the-road/#rule-6-do-not-solicit-members-of-our-slack) +- [Rule 7: Do not demand attention with @channel and @here, or by tagging individuals](/community/resources/slack-rules-of-the-road/#rule-7-do-not-demand-attention-with-channel-and-here-or-by-tagging-individuals) +- [Rule 8: Use threads](/community/resources/slack-rules-of-the-road/#rule-8-use-threads) + +### Vendor guidelines + +If you are a vendor (i.e. you represent an organization that sells a product or service relevant to our community), then there are additional guidelines you should be aware of. + +Most importantly — do not solicit members of our community as lead generation. You can find the rest of these [here](/community/resources/vendor-guidelines). + +### Guideline violations — 3 strikes method + +The point of our guidelines is not to find opportunities to punish people, but we do need a fair way to deal with people who do harm to our community. Violations related to our anti-harassment policy (below) will be addressed immediately and are not subject to 3 strikes. + +1. First occurrence: We’ll give you a friendly, but public, reminder that the behavior is inappropriate according to our guidelines. +2. Second occurrence: We’ll send you a private message with a warning that any additional violations will result in removal from the community. +3. Third occurrence: Depending on the violation, we might need to delete or ban your account. + +Notes: + +- Obvious spammers are banned on first occurrence. +- Participation in the dbt Community is a privilege — we reserve the right to remove people from the community. +- Violations are forgiven after 6 months of good behavior, and we won’t hold a grudge. +- People who are committing minor formatting / style infractions will get some education, rather than hammering them in the 3 strikes process. +- Contact conduct@getdbt.com to report abuse or appeal violations. In the case of appeals, we know that mistakes happen, and we’ll work with you to come up with a fair solution if there has been a misunderstanding. + +## Anti-harassment policy + +Further to our guidelines for participating in the community in a positive manner, we are also dedicated to providing a harassment-free experience for everyone. We do not tolerate harassment of participants in any form. + +Harassment includes: + +- Offensive comments related to gender, gender identity and expression, sexual orientation, disability, mental illness, neuro(a)typicality, physical appearance, body size, age, race, or religion. +- Unwelcome comments regarding a person’s lifestyle choices and practices, including those related to food, health, parenting, drugs, and employment. +- Deliberate misgendering or use of ‘dead’ or rejected names. +- Gratuitous or off-topic sexual images or behaviour in spaces where they’re not appropriate. +- Physical contact and simulated physical contact (eg, textual descriptions like “*hug*” or “*backrub*”) without consent or after a request to stop. +- Threats of violence. +- Incitement of violence towards any individual, including encouraging a person to commit suicide or to engage in self-harm. +- Deliberate intimidation. +- Stalking or following. +- Harassing photography or recording, including logging online activity for harassment purposes. +- Sustained disruption of discussion. +- Unwelcome sexual attention. +- Pattern of inappropriate social contact, such as requesting/assuming inappropriate levels of intimacy with others +- Continued one-on-one communication after requests to cease. +- Deliberate “outing” of any aspect of a person’s identity without their consent except as necessary to protect vulnerable people from intentional abuse. +- Publication of non-harassing private communication. + +The dbt Community prioritizes marginalized people’s safety over privileged people’s comfort. The dbt Community Admin team reserves the right not to act on complaints regarding: + +- ‘Reverse’ -isms, including ‘reverse racism,’ ‘reverse sexism,’ and ‘cisphobia’ +- Reasonable communication of boundaries, such as “leave me alone,” “go away,” or “I’m not discussing this with you.” +- Communicating in a ‘tone’ you don’t find congenial +- Criticizing racist, sexist, cissexist, or otherwise oppressive behavior or assumptions + +### Reporting harassment + +If you are being harassed by a member of the dbt Community, notice that someone else is being harassed, or have any other concerns, please contact us at [community@dbtlabs.com](mailto:community@dbtlabs.com). + +We will respect confidentiality requests for the purpose of protecting victims of abuse. At our discretion, we may publicly name a person about whom we’ve received harassment complaints, or privately warn third parties about them, if we believe that doing so will increase the safety of dbt community members or the general public. We will not name harassment victims without their affirmative consent. + +### Consequences +Participants asked to stop any harassing behavior are expected to comply immediately. + +If a participant engages in harassing behavior, the dbt Community Admin team may take any action they deem appropriate, up to and including expulsion from all dbt Community spaces and identification of the participant as a harasser to other dbt Community members or the general public. + +## Credits + +Credit to [01.org](https://01.org/community/participation-guidelines), [Tizen.org](https://www.tizen.org/community/guidelines), and [Geek Feminism](https://geekfeminism.wikia.org/wiki/Community_anti-harassment/Policy) for some of the wording used in this Code of Conduct. diff --git a/website/docs/docs/contributing/contributor-license-agreements.md b/website/docs/community/resources/contributor-license-agreements.md similarity index 100% rename from website/docs/docs/contributing/contributor-license-agreements.md rename to website/docs/community/resources/contributor-license-agreements.md diff --git a/website/docs/community/resources/forum-guidelines.md b/website/docs/community/resources/forum-guidelines.md new file mode 100644 index 00000000000..9c86c703663 --- /dev/null +++ b/website/docs/community/resources/forum-guidelines.md @@ -0,0 +1,52 @@ +--- +title: "Community Forum guidelines" +id: "forum-guidelines" +--- + +## What is the dbt Community Forum? + +[The dbt Community Forum](https://discourse.getdbt.com) is the platform for getting support with dbt as well as to have long-lived discussions about dbt, analytics engineering, and analytics. It's a place for us to build up a long-lasting knowledge base around the common challenges, opportunities, and patterns we work with every day. The forum is different from the dbt Community Slack in a few key ways, most importantly it is: + +- **Asynchronous** and **long-lived** - sometimes conversations continue over weeks, months, and beyond. +- **Intentional** - we recommend taking at least 5 to 10 minutes thinking about and shaping your initial post and any comments. +- **Citable** - Slack conversations tend to be great in the moment but get lost in the flow — forum posts can more easily shared and referenced. + +**Guidelines for engaging on the Forum** + +The community [Rules of the Road](https://docs.getdbt.com/docs/contributing/slack-rules-of-the-road) apply, and following them is the best way to get momentum behind your discussion or answers to your questions. The following guidelines will set you up for success: + +- Be respectful +- Put effort into your posts +- Mark replies as Solutions in the Help section +- Don’t double post + +## Categories + +The forum is broken down into three categories: + +- [Help](https://discourse.getdbt.com/c/help/19) + - This is a Q&A style forum where you can ask the dbt Community for help with specific questions about dbt, dbt Cloud, data modeling, or anything else you want a definitive answer on. + - This category is for questions which can plausibly have a _single correct answer_. + - ✅ How do I debug this Jinja error? + - ✅ How do I set up CI in dbt Cloud on GitHub? + - ❌ What is the best way to do marketing attribution? (More general Discussions like this are perfect for the [In-Depth Discussions](https://discourse.getdbt.com/c/discussions/21) category) +- [Show and Tell](https://discourse.getdbt.com/c/show-and-tell/22) + - This is the place to show off all of the cool things you are doing in dbt. Whether it’s a new macro, design pattern, or package, post here to show the community what you are up to! +- [In-Depth Discussions](https://discourse.getdbt.com/c/discussions/21) + - Share anything you’re thinking about that has to do with dbt or analytics engineering! This is a great place to jot down some thoughts to share with the community or spark a discussion on a topic that’s currently interesting you. + +## Inclusivity on the Community Forum + +We are **strongly** committed to building a community where everyone can feel welcome. + +The dbt community started with people who were not traditionally considered “technical”, did not have ownership over technical systems, and were often left out of organizational decision-making. We came together to learn from each other, solve hard problems together, and to help build a new discipline where data folks have greater ownership over our own work. It really matters to us that everyone feels like they can ask questions and engage, no matter their professional or personal background. + +Technical forums have the potential to replicate harmful power structures, and can feel intimidating or hostile. We are working hard to create and sustain an inclusive environment through community-building, technological solutions, inclusive content, and diverse contributors. This is a long-term project, and we will continue to iterate and make improvements. + +If you have any ideas or feedback on how to make this space friendlier or more inclusive please let us know, either on the community Slack in the #community-strategy channel or via email at [community@dbtlabs.com](mailto:community@dbtlabs.com). We want to hear from you! + +## Following new and ongoing Discussions + +The best way to stay up to date is to [browse the forum](https://discourse.getdbt.com/) directly. You can also Track or Watch specific threads or the whole category to receive updates on them without commenting. + +Each category also has a companion Slack channel (#advice-dbt-for-beginners, #show-and-tell and #in-depth-discussions). You can reply to the initial post in Slack and it will be added as a comment on the forum thread, allowing you to participate from inside Slack if you prefer. diff --git a/website/docs/community/maintaining-a-channel.md b/website/docs/community/resources/maintaining-a-channel.md similarity index 84% rename from website/docs/community/maintaining-a-channel.md rename to website/docs/community/resources/maintaining-a-channel.md index 856082e238d..1961686d4a2 100644 --- a/website/docs/community/maintaining-a-channel.md +++ b/website/docs/community/resources/maintaining-a-channel.md @@ -11,27 +11,27 @@ There are three things you should do to be a good channel maintainer in the [dbt - Keep an eye out in #introductions for folks who might benefit from your new channel. For example if someone works in the space or on the same problems, then direct them to the channel. - Make sure folks follow the [Rules of the Road](https://docs.getdbt.com/docs/contributing/slack-rules-of-the-road) in the channel. If you notice someone is not following one, gently remind them of the rule in thread, and, ideally, provide an example of how they can rephrase their message or where they can redirect it. If you have a question about how to proceed, just post it in #ask-a-moderator with a screenshot or link to the thread and someone will give you advice. -## Scope of the Role +## Scope of the role -A maintainer can be a dbt Labs employee, but does not have to be. *Slack channel maintainer* is philosophically similar to OSS maintainer. At the onset, the channel maintainer will help build up this new space in Slack and stir up conversation during the first few weeks of the channel's existence. They are someone who stays on top of feedback and encourages generative contributions. This is not necessarily someone who is the generator of content and contributions, or answers every question. +A maintainer can be a dbt Labs employee, but does not have to be. *Slack channel maintainer* is philosophically similar to OSS maintainer. At the onset, the channel maintainer will help build up this new space in Slack and stir up conversation during the first few weeks of the channel's existence. They are someone who stays on top of feedback and encourages generative contributions. This is not necessarily someone who is the generator of content and contributions, or answers every question. -## Initial Instructions +## Initial instructions -1. Review the [Rules of the Road](https://docs.getdbt.com/docs/contributing/slack-rules-of-the-road) and [Code of Conduct](https://www.getdbt.com/community/code-of-conduct) and please let the the folks who created the channel know that you read both documents and you agree to be mindful of them. +1. Review the [Rules of the Road](community/resources/slack-rules-of-the-road) and [Code of Conduct](community/resources/code-of-conduct) and please let the the folks who created the channel know that you read both documents and you agree to be mindful of them. 2. If you are a vendor, review the [Vendor Guidelines](https://www.getdbt.com/community/vendor-guidelines). 3. Add the Topic and Description to the channel. @Mention your name in the channel Description, identifying yourself as the maintainer. Ex: *Maintainer: First Last (pronouns).* If you are a vendor, make sure your Handle contains your affiliation. 4. Complete or update your Slack profile by making sure your Company (in the ‘What I do’ field), Pronouns, and Handle, if you’re a vendor, are up-to-date. -5. Post initial conversation topics once a few folks get in the channel to help folks get to know each other. Check out this [example introductory post](https://getdbt.slack.com/archives/C02FXAZRRDW/p1632407767005000). -6. Stir up conversation during the first few weeks of the channel's existence. As you get started, answer the questions you can or help find someone with answers, seed discussions about once a week, and making sure folks follow the Rules of the Road. +5. Post initial conversation topics once a few folks get in the channel to help folks get to know each other. Check out this [example introductory post](https://getdbt.slack.com/archives/C02FXAZRRDW/p1632407767005000). +6. Stir up conversation during the first few weeks of the channel's existence. As you get started, answer the questions you can or help find someone with answers, seed discussions about once a week, and making sure folks follow the Rules of the Road. -## Long-term Expectations +## Long-term expectations - Maintaining the channel, checking in and being active on a regular basis by answering folks' questions, and seeding discussions. Want an example? Check out [this poll](https://getdbt.slack.com/archives/C022A67TLFL/p1628279819038800). - For guidance on how to answer a question, see [Answering Community Questions](https://www.getdbt.com/community/answering-community-questions). If you are not sure how to answer a lingering or unanswered question, you can post about it in #ask-a-moderator or direct it to another channel, if relevant. - If the channel is an industry channel, it’s helpful to monitor [#introductions](https://getdbt.slack.com/archives/CETJLH1V3) and invite people. Keep an eye out for folks who might benefit from being in the new channel if they mention they are working in the space, or are thinking about some of these problems. - Make sure folks follow the [Rules of the Road](https://docs.getdbt.com/docs/contributing/slack-rules-of-the-road). For example, if you notice someone is not following one, gently remind them of the rule in thread, and, ideally, provide an example of how they can rephrase their message or where they can redirect it. If you have a question about how to proceed, just post about it in #ask-a-moderator with a link to the thread or screenshot and someone will give you advice. - In tools channels, sharing customer stories and product updates is very okay in this channel because folks expect that when they join. However, please avoid any direct sales campaigns, pricing offers, etc. -- If you have any questions/doubts about the [Rules of the Road](https://docs.getdbt.com/docs/contributing/slack-rules-of-the-road) or [Vendor Guidelines](https://www.getdbt.com/community/vendor-guidelines), please post a question in #ask-a-moderator about what sort of things the community expects from interactions with vendors. +- If you have any questions/doubts about the [Rules of the Road](/community/resources/slack-rules-of-the-road) or [Vendor Guidelines](/community/resources/vendor-guidelines), please post a question in #ask-a-moderator about what sort of things the community expects from interactions with vendors. - A reminder that we never DM anyone in Slack without their permission in public channel or some prior relationship. - A reminder that @ here/all/channel are disabled. - Use and encourage the use of threads 🧵 to keep conversations tidy! diff --git a/website/docs/community/resources/organizing-inclusive-events.md b/website/docs/community/resources/organizing-inclusive-events.md new file mode 100644 index 00000000000..00a6c54d12b --- /dev/null +++ b/website/docs/community/resources/organizing-inclusive-events.md @@ -0,0 +1,57 @@ +--- +title: "Organizing inclusive events" +id: "organizing-inclusive-events" +--- + +# Tips for organizing inclusive events + +The dbt community is filled with dedicated community leaders who create opportunities for connection, learning and professional development within the analytics community. + +This guide is a resource to help organizers execute **inclusive digital events**. We understand that organizers, presenters, speakers, etc. might not be able to apply these tips to *every* event, but this guide will offer some food for thought. + +Additionally, this list can grow. If you would like to contribute a tip, please email [community@dbtlabs.com](mailto:community@dbtlabs.com). + +## General logistics + +- Try to choose a date that does not overlap with [holidays](http://www.holidayscalendar.com/months/) or general major events. Don’t forget to check international holidays (if applicable) +- Avoid really large national/local events (i.e. World Cup) + +## Marketing + +- If you are using photos, share images that include community members with a wide range of presentations, including people from underrepresented groups. +- Put event accessibility information on your event page (i.e. “closed captioning available for all video resources”) +- In the registration process provide an opportunity for attendees to: + - share pronouns + - ask questions in advance + - request specific needs or other accommodations (interpreting services, braille transcription, dietary restrictions, etc.) +- If this is a paid event (e.g. a conference), create a scholarship for attendees that might need financial support +- Think about how you are promoting your event — are you reaching underrepresented communities, marginalized populations and people who might not have access to the internet? + +## Programming + +- Book diverse speakers. Include speakers that represent underrepresented and marginalized populations. +- Do research on your speakers. Is there any reason that your speakers would make the audience uncomfortable? +- Design an [accessible presentation](https://www.smashingmagazine.com/2018/11/inclusive-design-accessible-presentations/) +- If possible, share a recording after the event for community members who are not able to make it and add closed captioning. +- Ask speakers to introduce themselves before starting their presentation, so that transcription services can capture who is talking. + +## Digital platforms for online events + +- Take a minute or two to explain the features of the platform that attendees will be using in the beginning of the event +- Offer the option for attendees to dial-in by phone and participate without a computer or internet +- Explore the accessibility features your platform offers and apply it where necessary (i.e. closed captioning, automatic transcripts, screen reader support, etc.) +- Check if your platform is compatible with assistive technology + +## Attendee communication + +- Make sure that attendees have any addresses, links, codes, numbers to accessing the event beforehand +- Share the agenda of the event beforehand so that attendees are able to make arrangements (if necessary) +- Share contact information with attendees so that they are able to reach out with questions before and after the event. +- Ask attendees for feedback in a post-event survey so that you are able to improve future experiences. + +## Speaker communication + +- Ask speakers how to pronounce their names before the event +- Ask speakers for their pronouns before the event +- Suggest that speakers use headphones to ensure clear audio +- Ask speakers to use plain language and avoid jargon, slang, idioms, etc. diff --git a/website/docs/docs/contributing/oss-expectations.md b/website/docs/community/resources/oss-expectations.md similarity index 79% rename from website/docs/docs/contributing/oss-expectations.md rename to website/docs/community/resources/oss-expectations.md index 414cc7090b4..66880bc63b7 100644 --- a/website/docs/docs/contributing/oss-expectations.md +++ b/website/docs/community/resources/oss-expectations.md @@ -1,5 +1,5 @@ --- -title: "Expectations for OSS Contributors" +title: "Expectations for OSS contributors" --- Whether it's a dbt package, a plugin, `dbt-core`, or this very documentation site, contributing to the open source code that supports the dbt ecosystem is a great way to level yourself up as a developer, and to give back to the community. The goal of this page is to help you understand what to expect when contributing to dbt open source software (OSS). While we can only speak for our own experience as open source maintainers, many of these guidelines apply when contributing to other open source projects, too. @@ -10,7 +10,7 @@ Have you seen things in other OSS projects that you quite like, and think we cou ### Open source is participatory -Why take time out of your day to write code you don’t *have* to? We all build dbt together. By using dbt, you’re invested in the future of the tool, and an agent in pushing forward the practice of analytics engineering. You’ve already benefited from using code contributed by community members, and documentation written by community members. Contributing to dbt OSS is your way to pay it forward, as an active participant in the thing we’re all creating together. +Why take time out of your day to write code you don’t _have_ to? We all build dbt together. By using dbt, you’re invested in the future of the tool, and an agent in pushing forward the practice of analytics engineering. You’ve already benefited from using code contributed by community members, and documentation written by community members. Contributing to dbt OSS is your way to pay it forward, as an active participant in the thing we’re all creating together. There’s a very practical reason, too: OSS prioritizes our collective knowledge and experience over any one person’s. We don’t have experience using every database, operating system, security environment, ... We rely on the community of OSS users to hone our product capabilities and documentation to the wide variety of contexts in which it operates. In this way, dbt gets to be the handiwork of thousands, rather than a few dozen. @@ -77,16 +77,16 @@ In all likelihood, the maintainer who responds will also add a number of labels. In some cases, the right resolution to an open issue might be tangential to the codebase. The right path forward might be in another codebase (we'll transfer it), a documentation update, or a change that can be made in user-space code. In other cases, the issue might describe functionality that the maintainers are unwilling or unable to incorporate into the main codebase. In these cases, a maintainer will close the issue (perhaps using a `wontfix` label) and explain why. -| tag | description | -| --- | ----------- | -| `triage` | This is a new issue which has not yet been reviewed by a maintainer. This label is removed when a maintainer reviews and responds to the issue. | -| `bug` | This issue represents a defect or regression from the behavior that's documented, or that you reasonably expect | -| `enhancement` | This issue represents net-new functionality, including an extension of an existing capability | -| `good first issue` | This issue does not require deep knowledge of the codebase to implement. This issue is appropriate for a first-time contributor. | -| `help wanted` | This issue is trickier than a "good first issue." The required changes are scattered across the codebase, or more difficult to test. The maintainers are happy to help an experienced community contributor; they aren't planning to prioritize this issue themselves. | -| `duplicate` | This issue is functionally identical to another open issue. The maintainers will close this issue and encourage community members to focus conversation on the other one. | -| `stale` | This is an old issue which has not recently been updated. In repositories with a lot of activity, stale issues will periodically be closed. | -| `wontfix` | This issue does not require a code change in the repository, or the maintainers are unwilling to merge a change which implements the proposed behavior. | +| tag | description | +| ------------------ | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | +| `triage` | This is a new issue which has not yet been reviewed by a maintainer. This label is removed when a maintainer reviews and responds to the issue. | +| `bug` | This issue represents a defect or regression from the behavior that's documented, or that you reasonably expect | +| `enhancement` | This issue represents net-new functionality, including an extension of an existing capability | +| `good first issue` | This issue does not require deep knowledge of the codebase to implement. This issue is appropriate for a first-time contributor. | +| `help wanted` | This issue is trickier than a "good first issue." The required changes are scattered across the codebase, or more difficult to test. The maintainers are happy to help an experienced community contributor; they aren't planning to prioritize this issue themselves. | +| `duplicate` | This issue is functionally identical to another open issue. The maintainers will close this issue and encourage community members to focus conversation on the other one. | +| `stale` | This is an old issue which has not recently been updated. In repositories with a lot of activity, stale issues will periodically be closed. | +| `wontfix` | This issue does not require a code change in the repository, or the maintainers are unwilling to merge a change which implements the proposed behavior. | ## Pull requests @@ -97,8 +97,9 @@ PRs are your surest way to make the change you want to see in dbt / packages / d **Our goal is to review most new PRs within 7 days.** The first review will include some high-level comments about the implementation, including (at a high level) whether it’s something we think suitable to merge. Depending on the scope of the PR, the first review may include line-level code suggestions, or we may delay specific code review until the PR is more finalized / until we have more time. **Automation that can help us:** Many repositories have a template for pull request descriptions, which will include a checklist that must be completed before the PR can be merged. You don’t have to do all of these things to get an initial PR, but they definitely help. Those many include things like: + - **Tests!** When you open a PR, some tests and code checks will run. (For security reasons, some may need to be approved by a maintainer.) We will not merge any PRs with failing tests. If you’re not sure why a test is failing, please say so, and we’ll do our best to get to the bottom of it together. -- **Contributor License Agreement** (CLA): This ensures that we can merge your code, without worrying about unexpected implications for the copyright or license of open source dbt software. For more details, read: ["Contributor License Agreements"](contributor-license-agreements) +- **Contributor License Agreement** (CLA): This ensures that we can merge your code, without worrying about unexpected implications for the copyright or license of open source dbt software. For more details, read: ["Contributor License Agreements"](../resources/contributor-license-agreements.md) - **Changelog:** In projects that include a number of changes in each release, we need a reliable way to signal what's been included. The mechanism for this will vary by repository, so keep an eye out for notes about how to update the changelog. **If my PR is lingering...?** This happens, despite our best efforts—we promise it’s not intentional! If it’s been more than two weeks, we’d encourage you to leave a comment tagging `@dbt-labs/oss-maintainers`. reminding us that you’re awaiting review. For best results, say what in particular you’d like feedback on, and explain what would it mean to you to have the change merged in. diff --git a/website/docs/community/resources/oss-projects.md b/website/docs/community/resources/oss-projects.md new file mode 100644 index 00000000000..50dddde2f15 --- /dev/null +++ b/website/docs/community/resources/oss-projects.md @@ -0,0 +1,25 @@ +# Open source projects + +Looking for a good place to get involved contributing code? dbt Labs supports the following OSS repos, organized by the language primarily needed for contribution: + +## Python + +- [dbt-core](https://github.com/dbt-labs/dbt-core/discussions) - the primary shared functionality powering dbt +- [hubcap](https://github.com/dbt-labs/hubcap) - the code powering the dbt Package hub +- adapters - [the warehouse specific code that wires core up to various platforms](https://docs.getdbt.com/docs/contributing/adapter-development/1-what-are-adapters), several major platforms’ development is supported by dbt Labs: + - [dbt-bigquery](https://github.com/dbt-labs/dbt-bigquery) + - [dbt-snowflake](https://github.com/dbt-labs/dbt-snowflake) + - [dbt-redshift](https://github.com/dbt-labs/dbt-redshift) + - [dbt-spark](https://github.com/dbt-labs/dbt-spark) + +## dbt + +- [dbt Labs' packages](https://hub.getdbt.com/dbt-labs/) - the dbt pacakges created and supported by dbt Labs. Packages are just dbt projects, so if you know the SQL, Jinja, and YAML necessary to work in dbt, you can contribute to packages. + +## YAML and JSON Config + +- [dbt-jsonschema](https://github.com/dbt-labs/dbt-jsonschema) - powering completion and linting for YAML configuration in dbt projects. + +## Shell + +- [dbt-completion.bash](https://github.com/dbt-labs/dbt-completion.bash) - provides shell completion of CLI commands and selectors such as models and tests for bash and zsh. diff --git a/website/docs/docs/contributing/slack-rules-of-the-road.md b/website/docs/community/resources/slack-rules-of-the-road.md similarity index 90% rename from website/docs/docs/contributing/slack-rules-of-the-road.md rename to website/docs/community/resources/slack-rules-of-the-road.md index bac70dd674d..27774f9e35e 100644 --- a/website/docs/docs/contributing/slack-rules-of-the-road.md +++ b/website/docs/community/resources/slack-rules-of-the-road.md @@ -3,7 +3,7 @@ title: "dbt Slack: Rules of the Road" id: "slack-rules-of-the-road" --- -As of February 2022, the dbt Slack community includes 25,000+ data professionals and is growing month-over-month. People genuinely love this community. It’s filled with smart, kind, and helpful people who share our commitment to elevating the analytics profession. +As of October 2022, the dbt Slack community includes 35,000+ data professionals and is growing month-over-month. People genuinely love this community. It’s filled with smart, kind, and helpful people who share our commitment to elevating the analytics profession. We are committed to maintaining the spirit of this community, and as such have written these rules to help new members understand how to best participate in our community. @@ -18,13 +18,13 @@ Everyone interacting in dbt Slack, codebase, issue trackers, and mailing lists a ## Rule 2: Use the right channel It’s important that we make it possible for members of the community to opt-in to various types of conversations. Our different Slack channels specifically exist for this purpose. Our members do a wonderful job at making sure messages are posted in the most relevant channel, and you’ll frequently see people (respectfully!) reminding each other about where to post messages. Here's a guide to our channels: -- If you're new to dbt and unsure where something belongs, feel free to post in **#dbt-beginners** - we'll be able to direct you to the right place +- If you're new to dbt and unsure where something belongs, feel free to post in **#advice-dbt-for-beginners** - we'll be able to direct you to the right place - **For job postings, use #jobs**. If you post a job description outside of #jobs, we will delete it and send you a link to this rule. - For database-specific questions, use **#db-snowflake**, **#db-bigquery**, **#db-redshift**, or similar. - For questions about data modeling or for SQL help, use **#modeling** - For conversations unrelated to dbt or analytics, consider if dbt Slack is an appropriate medium for the conversation. If so, use **#memes-and-off-topic-chatter**. -If you're hitting an error, consider posting to [Stack Overflow](https://stackoverflow.com/questions/ask?tags=dbt) — we're moving more troubleshooting questions to Stack Overflow. A community member might summon Slackbot to let you know that Stack Overflow is a more appropriate medium by posting the words `stack overflow bot` as a reply to your message. +If you're hitting an error, you should post your question in [the Community Forum](https://discourse.getdbt.com) instead. ## Rule 3: Put effort into your question dbt Slack is a community of volunteers. These are kind, knowledgeable, helpful people who share their time and expertise for free. diff --git a/website/docs/community/resources/speaking-at-a-meetup.md b/website/docs/community/resources/speaking-at-a-meetup.md new file mode 100644 index 00000000000..cc1a424139e --- /dev/null +++ b/website/docs/community/resources/speaking-at-a-meetup.md @@ -0,0 +1,249 @@ +--- +title: "How to deliver a fantastic meetup talk" +id: "speaking-at-a-meetup" +--- + +# How to deliver a fantastic meetup talk + +**Speaking at a dbt meetup? Here’s all the details you’ll need to know. If you’re speaking at another event, check out our additional tips at the end of the article.** + +## Understanding dbt meetups + +dbt meetups are an opportunity for the dbt community to learn from each other. We’re typically on the lookout for talks that last for ~15 minutes, and we reserve an additional 5-10 minutes for Q&A after your talk. + +We’re not *just* looking for talks that feature dbt — if your topic feels relevant to analytics engineers, we’d love to chat. + +In general, you can assume that around three quarters of the audience are dbt users. When shaping your talk, consider whether there’s something in there that might be new to an experienced dbt user, and, on the other end of the scale, something that feels relevant to a data practitioner that isn’t yet a dbt user. + +If you feel that your talk idea requires in-depth knowledge of dbt, consider speaking on Office Hours instead. Similarly, if you’re interested in giving a more introductory talk about dbt, consider reaching out to a local data meetup to see if it’s the right fit. + +For topic inspiration, you can find videos of past dbt meetup presentations [here](https://www.youtube.com/playlist?list=PL0QYlrC86xQn-jxWmEqtQRbZoyjq_ffq5). + +If you want to present at a dbt meetup, let us know [here](https://docs.google.com/forms/d/e/1FAIpQLScU4c0UvXLsasc7uwFBrzt6YzuGiMzEH_EyFfXGnIYDmTBDfQ/viewform). If we haven’t met you before, we might book-in a call to say hi and help shape your topic! We’ll also book a meeting before the event for a dry-run of the presentation to give any additional feedback. + + +## Recognize when you’re ready to give a talk +Below, we’ve listed four signs that you’re ready to give a talk (originally based on [this article](https://thinkgrowth.org/how-to-write-about-your-work-652441747f41) from our Head of Marketing, Janessa — read that too!). We’ve also included examples for each category — where possible these are dbt meetup talks, but some of them are also links to blog posts from members in our community. + +### You recently finished a high-impact project +These are a great option for first-time speakers as they mix together both big-picture thinking and tactics. For example: + +- "Improving data reliability" — Andrea Kopitz ([video](https://www.youtube.com/watch?v=M_cNspn2XsE), [slides](https://docs.google.com/presentation/d/1gHChax5aM3tqKkhepX7Mghmg0DTDbY5yoDBCfUR23lg/)) +- "Predicting customer conversions using dbt + machine learning" — Kenny Ning ([video](https://www.youtube.com/watch?v=BF7HH8JDUS0), [slides](https://docs.google.com/presentation/d/1iqVjzxxRggMnRoI40ku88miDKw795djpKV_v4bbLpPE/)) +- "Migrating 387 models from Redshift to Snowflake" — Sam Swift and Travis Dunlop ([video](https://www.youtube.com/watch?v=VhH614WVufM), [slides](https://docs.google.com/presentation/d/1wE8NSkFPLFKGQ8fvFUUKoZFVoUhws_FhFip-9mDhoPU/)) + +### You hit an inflection point in your career +Have you recently changed something about your career that you think others can learn from? Started a new job, grown in your role? These topics might not mention dbt at all, but will be relevant to many people in the audience. For example: + +- “Getting hired as an analytics engineer: a candidate’s perspective” — Danielle Leong ([video](https://www.youtube.com/watch?v=6VCr30ZFxZ0)) +- “One analyst's guide for going from good to great” — Jason Ganz ([blog post](https://blog.getdbt.com/one-analysts-guide-for-going-from-good-to-great/)) + +Other ideas: +- You moved from a team of many to a team of one (or vice-versa), and want to share what each can learn from the other +- You started to manage others and learned some things along the way + +### You’re digging deep into a topic +If you’ve spent many hours going deep on a topic, it could be a good idea to share what you’ve learned. For example: + +- “The farm-to-table testing framework” — Andrea Fabry ([blog post](https://blog.getdbt.com/data-testing-framework/)) +- “How to create a career ladder” — Caitlin Moorman ([blog post](https://locallyoptimistic.com/post/career-ladders-part-2/)) + +### You have a strong opinion about something +Is there a “best practice” that you think is outdated? Want to convince others to see your point of view? In the data-space, we’ve seen this in topics like: + +- “Engineers shouldn’t write ETL” — Jeff Magnusson ([blog post](https://multithreaded.stitchfix.com/blog/2016/03/16/engineers-shouldnt-write-etl/)) +- “You probably don’t need a data dictionary” — Michael Kaminsky & Alexander Jia ([blog post](https://locallyoptimistic.com/post/data_dictionaries/)) +- “Write better SQL: In defense of `group by 1`” — Claire Carroll ([blog post](https://blog.getdbt.com/write-better-sql-a-defense-of-group-by-1/)) + +## Checkpoint: Is someone else well-placed to give this talk? +Once you have a topic idea, stop for a moment and consider whether someone else on your team might also be a great fit for delivering this talk. Individuals from underrepresented groups are far less likely to self-nominate to give a talk — sometimes a shoulder tap is the nudge that’s needed. + +## Shaping your talk +Now, it’s time to write! Rather than starting with a slide deck, open up a blank document (or use [our template](https://docs.google.com/document/d/16aog0VitdLSScgxSNKe36q1C92QmG2vjXmtXYcPAhfw/edit#)), and start writing some notes. This helps you clarify your thinking, and is a great way to get feedback early, rather than investing the time into creating slides that might later be reworked. + +Don’t get too hung up on a title at this stage — we’re happy to work with you on that later in the process. + +### The basic structure +Below, we’ve outlined a common structure used for meetup talks — if this is your first talk, this is a great way to get started (in fact, even experienced speakers often use a structure like this). Use this as a starting point, rather than an exact formula! + +###### 1. What is the business problem? + +Relating to a business problem helps audience members understand why you undertook a project. For example: +- The finance team didn’t trust our numbers +- We were never sure what led to an increase in customer conversion +- The data team couldn’t find a balance between ad hoc requests and roadmap work +- Our tracking across mobile and web was completely inconsistent + +###### 2. How did this manifest? +Include evidence that this is a genuine problem — this helps create buy-in from the audience. Slack screenshots, quotes, charts, etc. are all good here! + +###### 3. What tactics were used to solve the problem? +Three feels like a good number here. Make sure to emphasize people and process solutions as well as technology solutions. + +###### 4. What was the impact on the business problem? +Since you set out a problem to be solved, it’s worth revisiting it. It’s okay if you found that your project didn’t go as planned — there’s a valuable lesson in there. Again, including evidence of improvement feels valuable. + +###### 5. What other things were learned, and/or what next steps are you taking? +Summarize high level lessons that others can take-away, and potentially talk about what you’d do differently, or what you plan on doing next. + +### Why does this structure work? + +The above structure might seem formulaic, but we’ve seen it work a number of times. In our opinion, this structure works because: + +- **Your presentation has the structure of a story** — problem, journey, solution. Human beings love stories, and so the flow feels natural and easy for your audience to follow. +- **It increases the target audience**. Sharing a few different tactics means that it’s more likely there will be something in your talk for different audience members. Compare that to narrowly scoping a talk on “[Writing packages when a source table may or may not exist](https://discourse.getdbt.com/t/writing-packages-when-a-source-table-may-or-may-not-exist/1487)”— it’s not going to feel relevant to most people in the room. +- **It covers both theory and application.** Too much theory and you’re giving a TedTalk, too much application and you’re just giving a product demo. The best Meetup talks help people understand how you thought through a problem and why you made certain decisions so they can apply your knowledge within their unique context. + +### Examples that follow this structure + +Here's a few of our favorite talks mapped to the structure — trust us, it works! + +#### Improving data reliability — Andrea Kopitz, Envoy + +*[Video](https://www.youtube.com/watch?v=M_cNspn2XsE), [slides](https://docs.google.com/presentation/d/1gHChax5aM3tqKkhepX7Mghmg0DTDbY5yoDBCfUR23lg/).* + +###### 1. What is the business problem? +Envoy’s financial data appeared inconsistent. + +###### 2. How did this manifest? +Respondents to the team’s data survey said they no longer trusted the data. + +###### 3. What tactics were used to solve the problem? +1. Determine responsibility +2. Build more specific dbt tests +3. Track progress + +###### 4. What was the impact on the business problem? +In their next data survey, satisfaction rating increased, and no mention of financial data accuracy. + +###### 5. What other things were learned, and/or what next steps are you taking? +Lesson: Send out a data survey to your company to inform your roadmap. + +#### Predicting customer conversions with dbt + machine learning — Kenny Ning, Better.com + + +*[Video](https://www.youtube.com/watch?v=BF7HH8JDUS0), [slides](https://docs.google.com/presentation/d/1iqVjzxxRggMnRoI40ku88miDKw795djpKV_v4bbLpPE/).* + +###### 1. What is the business problem? +No one knew why conversion rates for better.com customers would improve or worsen, making it difficult to know the value of different parts of the business. + +###### 2. How did this manifest? +Different parts of the business took responsibility when it improved, no one took responsibility when it worsened. + +###### 3. What tactics were used to solve the problem? +1. Use a different approach to conversion rates — kaplan-meier conversion rates +2. Sketch out an ideal ML solution and see if it theoretically solves the problem +3. Build it! (ft. demonstration of solution) + +###### 4. What was the impact on the business problem? +In the end — not as valuable as originally hoped (and that’s ok!). Editor note: [this article](https://better.engineering/2020-06-24-wizard-part-ii/) was a great follow up on the initial project. + +###### 5. What other things were learned, and/or what next steps are you taking? +- Focus on end-to-end solutions +- Materialize your clean dataset to improve collaboration +- Sell to the business + +#### Migrating 387 models from Redshift to Snowflake — Bowery Farming Data Team + +*[Video](https://www.youtube.com/watch?v=VhH614WVufM), [slides](https://docs.google.com/presentation/d/1wE8NSkFPLFKGQ8fvFUUKoZFVoUhws_FhFip-9mDhoPU/).* + +###### 1. What is the business problem? +A new Bowery Farming site had increased the amount of data the team were dealing with, which put a strain on their data stack. + +###### 2. How did this manifest? +Charts show increased dbt run times, and increased Redshift costs. + +###### 3. What tactics were used to solve the problem? +1. Push Redshift to its limit: Leverage Athena, Redshift configurations, separate clusters, python pre-processing +2. Trial Snowflake for cost and performance +3. Commit to a migration with strong project management + +###### 4. What was the impact on the business problem? +Yet to be determined (at the time, they had just finished the project). But the team showed evidence that the project has been successfully completed! + +###### 5. What other things were learned, and/or what next steps are you taking? +Other things learned: +- Differences between Redshift and Snowflake SQL syntax +- Teamwork and coordination are key to completing a migration + +## Turn it into a presentation +Now, it's time to take your idea and turn it into a presentation. + +### Structuring your slides +As well as the slides that directly support your content, consider including: +- At the start: + - An intro slide for yourself (and teammates) + - An intro slide for your company — you might also include some impressive numbers about your business, after all, your audience is full of people who love numbers! + - Potentially include your tech stack for context — there’s no need to spend too much time on this, most audience members will be familiar with the tools. +- Before diving into the specific tactics used: + - Use a slide to list the three tactics at a high level — this signposting helps set expectations for audience members. +- At the end: + - A closing slide to prompt questions, and list your contact details. + - If your company is hiring, mention that too! + +If available, use your corporate-branded slide deck. We also have dbt-branded slides if you want to use those. + +### Making your presentation shine + +When turning your story into a presentation, also consider doing the following: + +#### Use full sentences in your slide headings + +When presenting (especially virtually), it’s hard to hold everyone’s focus. That’s ok! By including full sentences as your heading, people can “hook” back into the presentation. For example, rather than having a slide on "Slide headings", use a title like “Use full sentences in your slide headings” (woah — meta!) + +#### Make your slides accessible + +This is a [great guide](https://www.smashingmagazine.com/2018/11/inclusive-design-accessible-presentations/) on making your slides accessible — read it! + +#### Use evidence in your slides + +Evidence is a key part of getting buy-in that the story you’re telling is valuable. Consider including: + +- Screenshots of slack conversations +- Quotes, survey results, charts +- If talking about a complex transformation, include small samples of data to demonstrate the concept. You may need to generate some fake data to simplify the problem (example) +- If one of your tactics is heavily code-based, consider sharing that code in a separate piece so that interested folks can refer back to it later. (Discourse is great for this) + +#### (Virtual events) Create moments for interactivity + +For virtual events: is there a poll you can launch, or a question you can throw out to the chat? This can help create a sense of community at the event. + +## Pair it with a blog post + +The hardest part of nailing a great talk is the content, so if you’ve made it this far, you’ve already done most of the work. Turning your content into a blog post is a great way to solidify your thinking, and get some extra exposure. If you’d like to be features on the [dbt Blog](https://blog.getdbt.com/), reach out to us (@Claire and @Janessa) on Slack. + +We’ll also be adding more resources on how to write about your work soon! + +## Speaking at a non-dbt event + +Above, we’ve given specific advice for speaking at a dbt meetup. If you’re a dbt community member who wants to speak at a non-dbt meetup or conference, there’s a few extra ways you can adjust your process. + +### Questions to ask the event organizer + +#### What is the technical baseline for the audience? + +Do they know about dbt? If not, are they familiar with SQL? You’ll likely have a range of people in the audience so there won’t be one exact answer, but gathering information about the median knowledge is useful. As a guideline, aim to teach something new to at least half of the audience. + +#### What kind of talks have been the most successful? + +Is the event oriented around technical talks or strategic talks? Is there an expectation of demo-ing code? Do they have past examples of talks that were well-received, or any tips? + +#### What are the event logistics? + +How long is your talk supposed to go for? Is there an opportunity to do Q&A? + +If the event is virtual, what is the software setup like? How will questions be moderated? + +If the event is in-person, will you be able to use your own computer, or will you use someone else’s? What sort of screen is there? How do you connect to it? And do you have the right dongle for your MacBook Pro? + +#### Is there an opportunity for topic feedback? + +Is the organizer interested in working with you to make your topic great? If not, can they point you to someone in their community who might be interested in helping out? + +#### Are there any additional accessibility considerations you should be aware of? + +Do any audience members use a communication device? Can you share your slides ahead of time to make them easier for audience members to access? Will the event be recorded for those who can’t attend in person? + +### Responding to a conference Call for Speakers + +If you’re submitting a response for a Call for Speakers, and talking about dbt, we’re happy to work with you on this. Reach out to us (@Claire and @Janessa) in Slack to let us know! diff --git a/website/docs/community/resources/vendor-guidelines.md b/website/docs/community/resources/vendor-guidelines.md new file mode 100644 index 00000000000..1b6bb6c9511 --- /dev/null +++ b/website/docs/community/resources/vendor-guidelines.md @@ -0,0 +1,66 @@ +--- +title: "Vendor guidelines" +id: "vendor-guidelines" +--- + +# Engaging in the dbt Community as a Vendor + +A key aspect that makes dbt stand out from other tools is the dbt Community. +This community was built to drive our mission statement of empowering analysts. +This includes advancing the field of analytics engineering practices. +We are creating spaces where folks can learn from each other, share best practices, +discover what it means to use software engineering workflows, and so on. + +The dbt community extends far beyond what happens in dbt Slack. There are regular meetups, +blog posts, and even a conference! Our North Star is to extend the knowledge loop; +we are a community, not an audience. + +Our community members expect a thoughtful space full of kind, curious, and bright individuals. +They contribute to the knowledge loop with their own expertise and benefit from the relevant knowledge brought to the table by other community experts (including vendors). +Along those lines, **we value diversity and inclusion**. +We seek to amplify underrepresented communities and have no tolerance for anyone who is disrespectful in this space. + +As a vendor/dbt partner, you are also a member of this community, one that we want +and deeply encourage to share your expertise in tooling, analytics, etc. +Our community members are truly open to discovering and discussing innovative solutions and tools. +We have seen folks grow fantastic user relationships for their products when they come in with the mindset to share rather than pushing a pitch. + +To guide you on your community journey, we have created this document for you to read and share with your coworkers. +By following these guidelines, you will help us maintain this community as well as gain +full access to all the benefits that this community can provide. + + +## Dos & Don'ts for dbt Slack + +### Dos +- **Read the Rules of The Road.** These rules are the best ways to participate in our community. +- **Fill your profile!** We want to get to know you so do upload a picture of yourself and add your company in your name (e.g. "Alice (DataCo)"). Be sure to include your company in your profile so folks know that you work for a vendor +- **Introduce Yourself in #introductions.** Tell us about yourself! +- **Be helpful.** We encourage folks to answer questions and offer their product expertise to conversations already in motion. You can even invite folks to chat in DMs if anyone wants more info about your product. But be sure you identify yourself and your business interests in thread. +- **Be yourself when posting, speak in your own voice.** +- **Participate in all the conversations that interest you.** Make a meme if you’re so inclined. Get in a (friendly) debate. You are not limited to only your company's products and services. +- **Post with intention.** If you have a link or product update that is appropriate to share, give context. + +### Don'ts +- **Do not do 1:1 outbound.** Only initiate DMs if you’ve received active confirmation in a public channel that a DM would be welcome. +- **Do not be anonymous.** Folks who identify themselves clearly are able to build empathy and form genuine relationships much easier. This is what we want for the community. +- Spam channels with Marketing material. +- **Do not post without context.** Posts that include context outside of just the pitch are the ones that add value to our community. + + +## Summary + +This community is centered around feeding into the knowledge loop. It’s a place intended for building genuine, helpful connections. We found that most vendors find success in our space by leading with this intention. + +Here are some ways you can contribute to the community: + +- contribute to the dbt core repository +- write dbt packages +- write other public content (blog posts, case studies, etc.) +- respond to questions on slack / discourse +- host events +- promote / respond to content written by community members +- Partner up with community members on blog posts/code/etc. + +For more information on the thought behind our community, especially if you are interested in creating your own, feel free to +reach out to our community managers. diff --git a/website/docs/docs/about/viewpoint.md b/website/docs/community/resources/viewpoint.md similarity index 97% rename from website/docs/docs/about/viewpoint.md rename to website/docs/community/resources/viewpoint.md index 9601a3fd46f..e159c6178a3 100644 --- a/website/docs/docs/about/viewpoint.md +++ b/website/docs/community/resources/viewpoint.md @@ -1,9 +1,9 @@ --- -title: "Viewpoint" +title: "The dbt Viewpoint" id: "viewpoint" --- -:::info Building a Mature Analytics Workflow: The dbt Viewpoint +:::info Building a Mature Analytics Workflow: The dbt Viewpoint! In 2015-2016, a team of folks at RJMetrics had the opportunity to observe, and participate in, a significant evolution of the analytics ecosystem. The seeds of dbt were conceived in this environment, and the viewpoint below was written to reflect what we had learned and how we believed the world should be different. **dbt is our attempt to address the workflow challenges we observed, and as such, this viewpoint is the most foundational statement of the dbt project's goals.** @@ -53,7 +53,7 @@ Analytics requires multiple environments. Analysts need the freedom to work with Analytics teams should stand behind the accuracy of all analysis that has been promoted to production. Errors should be treated with the same level of urgency as bugs in a production product. Any code being retired from production should go through a deprecation process. ### Design for maintainability -Most of the cost involved in software development is in the maintenance phase. Because of this, software engineers write code with an eye towards maintainability. Analytic code, however, is often fragile. Changes in underlying data break most analytic code in ways that are hard to predict and to fix. +Most of the cost involved in software development is in the maintenance phase. Because of this, software engineers write code with an eye towards maintainability. Analytic code, however, is often fragile. Changes in underlying data break most analytic code in ways that are hard to predict and to fix. Analytic code should be written with an eye towards maintainability. Future changes to the schema and data should be anticipated and code should be written to minimize the corresponding impact. diff --git a/website/docs/docs/about/license.md b/website/docs/docs/about/license.md deleted file mode 100644 index ab47907a12a..00000000000 --- a/website/docs/docs/about/license.md +++ /dev/null @@ -1,8 +0,0 @@ ---- -title: "License" -id: "license" ---- - -[dbt Core is licensed under the Apache 2.0 License](https://github.com/dbt-labs/dbt). - -dbt Cloud is proprietary. diff --git a/website/docs/docs/building-a-dbt-project/analyses.md b/website/docs/docs/build/analyses.md similarity index 100% rename from website/docs/docs/building-a-dbt-project/analyses.md rename to website/docs/docs/build/analyses.md diff --git a/website/docs/docs/building-a-dbt-project/building-models/using-custom-aliases.md b/website/docs/docs/build/custom-aliases.md similarity index 92% rename from website/docs/docs/building-a-dbt-project/building-models/using-custom-aliases.md rename to website/docs/docs/build/custom-aliases.md index 5675c64ae3a..53671291ef8 100644 --- a/website/docs/docs/building-a-dbt-project/building-models/using-custom-aliases.md +++ b/website/docs/docs/build/custom-aliases.md @@ -1,6 +1,6 @@ --- -title: "Using aliases" -id: "using-custom-aliases" +title: "Custom aliases" +id: "custom-aliases" --- ## Overview @@ -8,7 +8,7 @@ id: "using-custom-aliases" When dbt runs a model, it will generally create a relation (either a `table` or a `view`) in the database. By default, dbt uses the filename of the model as the identifier for this relation in the database. This identifier can optionally be overridden using the `alias` model configuration. ### Why alias model names? -The names of schemas and tables are effectively the "user interface" of your . Well-named schemas and tables can help provide clarity and direction for consumers of this data. In combination with [custom schemas](using-custom-schemas), model aliasing is a powerful mechanism for designing your warehouse. +The names of schemas and tables are effectively the "user interface" of your . Well-named schemas and tables can help provide clarity and direction for consumers of this data. In combination with [custom schemas](/docs/build/custom-schemas), model aliasing is a powerful mechanism for designing your warehouse. ### Usage The `alias` config can be used to change the name of a model's identifier in the database. The following shows examples of database identifiers for models both with, and without, a supplied `alias`. @@ -50,7 +50,7 @@ select * from {{ ref('snowplow_sessions') }} ### generate_alias_name -The alias generated for a model is controlled by a macro called `generate_alias_name`. This macro can be overridden in a dbt project to change how dbt aliases models. This macro works similarly to the [generate_schema_name](using-custom-schemas#advanced-custom-schema-configuration) macro. +The alias generated for a model is controlled by a macro called `generate_alias_name`. This macro can be overridden in a dbt project to change how dbt aliases models. This macro works similarly to the [generate_schema_name](/docs/build/custom-schemas#advanced-custom-schema-configuration) macro. To override dbt's alias name generation, create a macro named `generate_alias_name` in your own dbt project. The `generate_alias_name` macro accepts two arguments: @@ -113,4 +113,4 @@ Compilation Error - model.my_project.sessions (models/sessions.sql) ``` -If these models should indeed have the same database identifier, you can work around this error by configuring a [custom schema](using-custom-schemas) for one of the models. +If these models should indeed have the same database identifier, you can work around this error by configuring a [custom schema](/docs/build/custom-schemas) for one of the models. diff --git a/website/docs/docs/building-a-dbt-project/building-models/using-custom-databases.md b/website/docs/docs/build/custom-databases.md similarity index 94% rename from website/docs/docs/building-a-dbt-project/building-models/using-custom-databases.md rename to website/docs/docs/build/custom-databases.md index c466c7d44b3..75f9ee45d46 100644 --- a/website/docs/docs/building-a-dbt-project/building-models/using-custom-databases.md +++ b/website/docs/docs/build/custom-databases.md @@ -1,5 +1,6 @@ --- -title: "Using custom databases" +title: "Custom databases" +id: "custom-databases" --- @@ -55,7 +56,7 @@ select * from ... New in v0.16.0 -The database name generated for a model is controlled by a macro called `generate_database_name`. This macro can be overridden in a dbt project to change how dbt generates model database names. This macro works similarly to the [generate_schema_name](using-custom-schemas#advanced-custom-schema-configuration) macro. +The database name generated for a model is controlled by a macro called `generate_database_name`. This macro can be overridden in a dbt project to change how dbt generates model database names. This macro works similarly to the [generate_schema_name](/docs/build/custom-schemas#advanced-custom-schema-configuration) macro. To override dbt's database name generation, create a macro named `generate_database_name` in your own dbt project. The `generate_database_name` macro accepts two arguments: diff --git a/website/docs/docs/building-a-dbt-project/building-models/using-custom-schemas.md b/website/docs/docs/build/custom-schemas.md similarity index 90% rename from website/docs/docs/building-a-dbt-project/building-models/using-custom-schemas.md rename to website/docs/docs/build/custom-schemas.md index 3a66d914db9..95c0c77becc 100644 --- a/website/docs/docs/building-a-dbt-project/building-models/using-custom-schemas.md +++ b/website/docs/docs/build/custom-schemas.md @@ -1,6 +1,6 @@ --- -title: "Using custom schemas" -id: "using-custom-schemas" +title: "Custom schemas" +id: "custom-schemas" --- ## What is a custom schema? @@ -55,7 +55,7 @@ models: ### Why does dbt concatenate the custom schema to the target schema? When first using custom schemas, it's common to assume that a model will be built in schema that matches the `schema` configuration exactly, for example, a model that has the configuration `schema: marketing`, would be built in the `marketing` schema. However, dbt instead creates it in a schema like `_marketing` by default – there's good reason for this! -In a typical setup of dbt, each dbt user will use a separate target schema (see [Managing Environments](using-custom-schemas#managing-environments)). If dbt created models in a schema that matches a model's custom schema exactly, every dbt user would create models in the same schema. +In a typical setup of dbt, each dbt user will use a separate target schema (see [Managing Environments](/docs/build/custom-schemas#managing-environments)). If dbt created models in a schema that matches a model's custom schema exactly, every dbt user would create models in the same schema. Further, the schema that your development models are built in would be the same schema that your production models are built in! Instead, concatenating the custom schema to the target schema helps create distinct schema names, reducing naming conflicts. @@ -151,15 +151,16 @@ for more information on these changes. Globally-scoped variables and variables defined on the command line with -[--vars](using-variables) are accessible in the `generate_schema_name` context. +[--vars](/docs/build/project-variables) are accessible in the `generate_schema_name` context. ## Managing environments In the `generate_schema_name` macro examples shown above, the `target.name` context variable is used to change the schema name that dbt generates for models. If the `generate_schema_name` macro in your project uses the `target.name` context variable, you must additionally ensure that your different dbt environments are configured appropriately. While you can use any naming scheme you'd like, we typically recommend: - **dev**: Your local development environment; configured in a `profiles.yml` file on your computer. - - **ci**: A [continuous integration](cloud-enabling-continuous-integration-with-github) environment running on Pull Requests in GitHub, GitLab, etc. - - **prod**: The production deployment of your dbt project, eg. in dbt Cloud, Airflow, or [similar](running-dbt-in-production) +* **ci**: A [continuous integration](/docs/collaborate/git/connect-github) environment running on Pull Requests in GitHub, GitLab, etc. + - **prod**: The production deployment of your dbt project, like in dbt Cloud, Airflow, or [similar](/docs/deploy/deployments). +>>>>>>> next If your schema names are being generated incorrectly, double check your target name in the relevant environment. -For more information, consult the [Managing environments](managing-environments) guide. +For more information, consult the [Managing environments](/docs/collaborate/environments) guide. diff --git a/website/docs/docs/dbt-cloud/using-dbt-cloud/cloud-setting-a-custom-target-name.md b/website/docs/docs/build/custom-target-names.md similarity index 93% rename from website/docs/docs/dbt-cloud/using-dbt-cloud/cloud-setting-a-custom-target-name.md rename to website/docs/docs/build/custom-target-names.md index 3944bfc3d58..4e14f36b784 100644 --- a/website/docs/docs/dbt-cloud/using-dbt-cloud/cloud-setting-a-custom-target-name.md +++ b/website/docs/docs/build/custom-target-names.md @@ -1,6 +1,6 @@ --- -title: "Setting a custom target name" -id: "cloud-setting-a-custom-target-name" +title: "Custom target names" +id: "custom-target-names" description: "You can define a custom target name for any dbt Cloud job to correspond to settings in your dbt project." --- diff --git a/website/docs/docs/dbt-cloud/using-dbt-cloud/cloud-environment-variables.md b/website/docs/docs/build/environment-variables.md similarity index 88% rename from website/docs/docs/dbt-cloud/using-dbt-cloud/cloud-environment-variables.md rename to website/docs/docs/build/environment-variables.md index 028701a25b0..c6a2517c9a2 100644 --- a/website/docs/docs/dbt-cloud/using-dbt-cloud/cloud-environment-variables.md +++ b/website/docs/docs/build/environment-variables.md @@ -1,6 +1,6 @@ --- title: Environment variables -id: "cloud-environment-variables" +id: "environment-variables" description: "Use environment variables to customize the behavior of your dbt project." --- @@ -19,16 +19,16 @@ Environment variable values can be set in multiple places within dbt Cloud. As a -There are four levels of environment variables: +There are four levels of environment variables: 1. the optional default argument supplied to the `env_var` Jinja function in code - 2. a project-wide default value, which can be overridden at - 3. the environment level, which can in turn be overridden again at + 2. a project-wide default value, which can be overridden at + 3. the environment level, which can in turn be overridden again at 4. the job level (job override) or in the IDE for an individual dev (personal override). **Setting environment variables at the project and environment level** -To set environment variables at the project and environment level, click **Deploy** in the top left, then select **Environments**. Click **Environments Variables** to add and update your environment variables. +To set environment variables at the project and environment level, click **Deploy** in the top left, then select **Environments**. Click **Environments Variables** to add and update your environment variables. @@ -44,7 +44,7 @@ To the right of the `Project Default` column are all your environments. Values s **Overriding environment variables at the job level** -You may have multiple jobs that run in the same environment, and you'd like the environment variable to be interpretted differently depending on the job. +You may have multiple jobs that run in the same environment, and you'd like the environment variable to be interpretted differently depending on the job. When setting up or editing a job, you will see a section where you can override environment variable values defined at the environment or project level. @@ -59,7 +59,7 @@ Every job runs in a specific, deployment environment, and by default, a job will **Overriding environment variables at the personal level** -You can also set a personal value override for an environment variable when you develop in the dbt integrated developer environment (IDE). By default, dbt Cloud uses environment variable values set in the project's development environment. To see and override these values, click the gear icon in the top right. Under "Your Profile," click **Credentials** and select your project. Click **Edit** and make any changes in "Environment Variables." +You can also set a personal value override for an environment variable when you develop in the dbt integrated developer environment (IDE). By default, dbt Cloud uses environment variable values set in the project's development environment. To see and override these values, click the gear icon in the top right. Under "Your Profile," click **Credentials** and select your project. Click **Edit** and make any changes in "Environment Variables." @@ -83,12 +83,12 @@ There are some known issues with partial parsing of a project and changing envir ### Handling secrets -While all environment variables are encrypted at rest in dbt Cloud, dbt Cloud has additional capabilities for managing environment variables with secret or otherwise sensitive values. If you want a particular environment variable to be scrubbed from all logs and error messages, in addition to obfuscating the value in the UI, you can prefix the key with `DBT_ENV_SECRET_`. This functionality is supported from `dbt v1.0` and on. +While all environment variables are encrypted at rest in dbt Cloud, dbt Cloud has additional capabilities for managing environment variables with secret or otherwise sensitive values. If you want a particular environment variable to be scrubbed from all logs and error messages, in addition to obfuscating the value in the UI, you can prefix the key with `DBT_ENV_SECRET_`. This functionality is supported from `dbt v1.0` and on. -**Note**: An environment variable can be used to store a [git token for repo cloning](/cloud-environment-variables#clone-private-packages). We recommend you make the git token's permissions read only and consider using a machine account or service user's PAT with limited repo access in order to practice good security hygiene. +**Note**: An environment variable can be used to store a [git token for repo cloning](/docs/build/environment-variables#clone-private-packages). We recommend you make the git token's permissions read only and consider using a machine account or service user's PAT with limited repo access in order to practice good security hygiene. ### Special environment variables @@ -118,12 +118,12 @@ PR builds triggered via a webhook_ Environment variables can be used in many ways, and they give you the power and flexibility to do what you want to do more easily in dbt Cloud. #### Clone private packages -Now that you can set secrets as environment variables, you can pass git tokens into your package HTTPS URLs to allow for on-the-fly cloning of private repositories. Read more about enabling [private package cloning](/building-a-dbt-project/package-management#private-packages). +Now that you can set secrets as environment variables, you can pass git tokens into your package HTTPS URLs to allow for on-the-fly cloning of private repositories. Read more about enabling [private package cloning](/docs/build/packages#private-packages). #### Dynamically set your warehouse in your Snowflake connection -Environment variables make it possible to dynamically change the Snowflake virtual warehouse size depending on the job. Instead of calling the warehouse name directly in your project connection, you can reference an environment variable which will get set to a specific virtual warehouse at runtime. +Environment variables make it possible to dynamically change the Snowflake virtual warehouse size depending on the job. Instead of calling the warehouse name directly in your project connection, you can reference an environment variable which will get set to a specific virtual warehouse at runtime. -As example, suppose you'd like to run a full-refresh job in an XL warehouse, but your incremental job only needs to run in a medium-sized warehouse. Both jobs are configured in the same dbt Cloud environment. In your connection configuration, you can use an environment variable to set the warehouse name to `{{env_var('DBT_WAREHOUSE')}}`. Then in the job settings, you can set a different value for the `DBT_WAREHOUSE` environment variable depending on the job's workload. +For example, suppose you'd like to run a full-refresh job in an XL warehouse, but your incremental job only needs to run in a medium-sized warehouse. Both jobs are configured in the same dbt Cloud environment. In your connection configuration, you can use an environment variable to set the warehouse name to `{{env_var('DBT_WAREHOUSE')}}`. Then in the job settings, you can set a different value for the `DBT_WAREHOUSE` environment variable depending on the job's workload. diff --git a/website/docs/docs/building-a-dbt-project/exposures.md b/website/docs/docs/build/exposures.md similarity index 98% rename from website/docs/docs/building-a-dbt-project/exposures.md rename to website/docs/docs/build/exposures.md index a2ad5301ee9..e20867662e3 100644 --- a/website/docs/docs/building-a-dbt-project/exposures.md +++ b/website/docs/docs/build/exposures.md @@ -14,7 +14,7 @@ id: "exposures" * [Exposure properties](exposure-properties) * [`exposure:` selection method](node-selection/methods#the-exposure-method) -## Getting started +## Overview Exposures make it possible to define and describe a downstream use of your dbt project, such as in a dashboard, application, or data science pipeline. By defining exposures, you can then: - run, test, and list resources that feed into your exposure @@ -28,19 +28,19 @@ Exposures are defined in `.yml` files nested under an `exposures:` key. ```yaml exposures: - + - name: weekly_jaffle_metrics type: dashboard maturity: high url: https://bi.tool/dashboards/1 description: > Did someone say "exponential growth"? - + depends_on: - ref('fct_orders') - ref('dim_customers') - source('gsheets', 'goals') - + owner: name: Claire from Data email: data@jaffleshop.com diff --git a/website/docs/docs/building-a-dbt-project/hooks-operations.md b/website/docs/docs/build/hooks-operations.md similarity index 99% rename from website/docs/docs/building-a-dbt-project/hooks-operations.md rename to website/docs/docs/build/hooks-operations.md index 620ad9e8a7f..524a75aaf9c 100644 --- a/website/docs/docs/building-a-dbt-project/hooks-operations.md +++ b/website/docs/docs/build/hooks-operations.md @@ -1,5 +1,5 @@ --- -title: "Hooks & Operations" +title: "Hooks and operations" id: "hooks-operations" --- diff --git a/website/docs/docs/building-a-dbt-project/building-models/configuring-incremental-models.md b/website/docs/docs/build/incremental-models.md similarity index 98% rename from website/docs/docs/building-a-dbt-project/building-models/configuring-incremental-models.md rename to website/docs/docs/build/incremental-models.md index 6df02ada930..08911764e32 100644 --- a/website/docs/docs/building-a-dbt-project/building-models/configuring-incremental-models.md +++ b/website/docs/docs/build/incremental-models.md @@ -1,9 +1,9 @@ --- -title: "Configuring incremental models" -id: "configuring-incremental-models" +title: "Incremental models" +id: "incremental-models" --- -## About incremental models +## Overview Incremental models are built as tables in your . The first time a model is run, the is built by transforming _all_ rows of source data. On subsequent runs, dbt transforms _only_ the rows in your source data that you tell dbt to filter for, inserting them into the target table which is the table that has already been built. @@ -299,3 +299,6 @@ select ... ``` + + + diff --git a/website/docs/docs/building-a-dbt-project/jinja-macros.md b/website/docs/docs/build/jinja-macros.md similarity index 96% rename from website/docs/docs/building-a-dbt-project/jinja-macros.md rename to website/docs/docs/build/jinja-macros.md index 701487bf62c..ec36cc06e91 100644 --- a/website/docs/docs/building-a-dbt-project/jinja-macros.md +++ b/website/docs/docs/build/jinja-macros.md @@ -1,5 +1,5 @@ --- -title: "Jinja & Macros" +title: "Jinja and macros" id: "jinja-macros" --- @@ -22,7 +22,9 @@ Using Jinja turns your dbt project into a programming environment for SQL, givin In fact, if you've used the [`{{ ref() }}` function](ref), you're already using Jinja! -Jinja can be used in any SQL in a dbt project, including [models](building-models), [analyses](analyses), [tests](building-a-dbt-project/tests), and even [hooks](hooks-operations). + +Jinja can be used in any SQL in a dbt project, including [models](/docs/build/sql-models), [analyses](analyses), [tests](building-a-dbt-project/tests), and even [hooks](hooks-operations). + :::info Ready to get started with Jinja and macros? @@ -184,3 +186,6 @@ Writing a macro for the first time? Check whether we've open sourced one in [dbt ... {% endfor %} ``` + + + diff --git a/website/docs/docs/building-a-dbt-project/building-models/materializations.md b/website/docs/docs/build/materializations.md similarity index 63% rename from website/docs/docs/building-a-dbt-project/building-models/materializations.md rename to website/docs/docs/build/materializations.md index de9275ec6b5..95535491286 100644 --- a/website/docs/docs/building-a-dbt-project/building-models/materializations.md +++ b/website/docs/docs/build/materializations.md @@ -84,7 +84,7 @@ When using the `table` materialization, your model is rebuilt as a expression. * **Pros:** * You can still write reusable logic - * Ephemeral models can help keep your clean by reducing clutter (also consider splitting your models across multiple schemas by [using custom schemas](using-custom-schemas)). + - Ephemeral models can help keep your clean by reducing clutter (also consider splitting your models across multiple schemas by [using custom schemas](/docs/build/custom-schemas)). * **Cons:** * You cannot select directly from this model. * Operations (e.g. macros called via `dbt run-operation` cannot `ref()` ephemeral nodes) @@ -102,3 +102,83 @@ When using the `table` materialization, your model is rebuilt as a + + + +```python +import snowflake.snowpark.functions as F + +def model(dbt, session): + dbt.config(materialized = "incremental") + df = dbt.ref("upstream_table") + + if dbt.is_incremental: + + # only new rows compared to max in current table + max_from_this = f"select max(updated_at) from {dbt.this}" + df = df.filter(df.updated_at >= session.sql(max_from_this).collect()[0][0]) + + # or only rows from the past 3 days + df = df.filter(df.updated_at >= F.dateadd("day", F.lit(-3), F.current_timestamp())) + + ... + + return df +``` + + + + + +
+ + + +```python +import pyspark.sql.functions as F + +def model(dbt, session): + dbt.config(materialized = "incremental") + df = dbt.ref("upstream_table") + + if dbt.is_incremental: + + # only new rows compared to max in current table + max_from_this = f"select max(updated_at) from {dbt.this}" + df = df.filter(df.updated_at >= session.sql(max_from_this).collect()[0][0]) + + # or only rows from the past 3 days + df = df.filter(df.updated_at >= F.date_add(F.current_timestamp(), F.lit(-3))) + + ... + + return df +``` + + + +
+ + + +**Note:** Incremental models are supported on BigQuery/Dataproc for the `merge` incremental strategy. The `insert_overwrite` strategy is not yet supported. + + + + diff --git a/website/docs/docs/building-a-dbt-project/metrics.md b/website/docs/docs/build/metrics.md similarity index 99% rename from website/docs/docs/building-a-dbt-project/metrics.md rename to website/docs/docs/build/metrics.md index 8f31f3465f8..1042467b9d1 100644 --- a/website/docs/docs/building-a-dbt-project/metrics.md +++ b/website/docs/docs/build/metrics.md @@ -490,3 +490,5 @@ Functionality for `develop` is only supported in v1.2 and higher. Please navigat + + diff --git a/website/docs/docs/build/models.md b/website/docs/docs/build/models.md new file mode 100644 index 00000000000..029e2856abb --- /dev/null +++ b/website/docs/docs/build/models.md @@ -0,0 +1,20 @@ +--- +title: "About dbt models" +id: "models" +--- + +## Overview + +dbt Core and Cloud are composed of different moving parts working harmoniously. All of them are important to what dbt does — transforming data—the 'T' in ELT. When you execute `dbt run`, you are running a model that will transform your data without that data ever leaving your warehouse. + +Models are where your developers spend most of their time within a dbt environment. Models are primarily written as a `select` statement and saved as a `.sql` file. While the definition is straightforward, the complexity of the execution will vary from environment to environment. Models will be written and rewritten as needs evolve and your organization finds new ways to maximize efficiency. + +SQL is the language most dbt users will utilize, but it is not the only one for building models. Starting in version 1.3, dbt Core and dbt Cloud support Python models. Python models are useful for training or deploying data science models, complex transformations, or where a specific Python package meets a need — such as using the `dateutil` library to parse dates. + +### Models and modern workflows + +The top level of a dbt workflow is the project. A project is a directory of a `.yml` file (the project configuration) and either `.sql` or `.py` files (the models). The project file tells dbt the project context, and the models let dbt know how to build a specific data set. For more details on projects, refer to [About dbt projects](/docs/build/projects). + +Your organization may need only a few models, but more likely you’ll need a complex structure of nested models to transform the required data. A model is a single file containing a final `select` statement, and a project can have multiple models, and models can even reference each other. Add to that, numerous projects and the level of effort required for transforming complex data sets can improve drastically compared to older methods. + +Learn more about models in [SQL models](/docs/build/sql-models) and [Python models](/docs/build/python-models) pages. If you'd like to begin with a bit of practice, visit our [Getting Started Guide](/docs/get-started/getting-started/overview) for instructions on setting up the Jaffle_Shop sample data so you can get hands-on with the power of dbt. diff --git a/website/docs/docs/building-a-dbt-project/package-management.md b/website/docs/docs/build/packages.md similarity index 99% rename from website/docs/docs/building-a-dbt-project/package-management.md rename to website/docs/docs/build/packages.md index 7c8a7cfa99a..ac05724e836 100644 --- a/website/docs/docs/building-a-dbt-project/package-management.md +++ b/website/docs/docs/build/packages.md @@ -1,6 +1,6 @@ --- title: "Packages" -id: "package-management" +id: "packages" --- ## What is a package? @@ -146,7 +146,7 @@ As of v0.14.0, dbt will warn you if you install a package using the `git` syntax ### Private packages #### SSH Key Method (Command Line only) -If you're using the Command Line, private packages can be cloned via SSH and an SSH key. +If you're using the Command Line, private packages can be cloned via SSH and an SSH key. When you use SSH keys to authenticate to your git remote server, you don’t need to supply your username and password each time. Read more about SSH keys, how to generate them, and how to add them to your git provider here: [Github](https://docs.github.com/en/github/authenticating-to-github/connecting-to-github-with-ssh) and [GitLab](https://docs.gitlab.com/ee/ssh/). diff --git a/website/docs/docs/building-a-dbt-project/building-models/using-variables.md b/website/docs/docs/build/project-variables.md similarity index 96% rename from website/docs/docs/building-a-dbt-project/building-models/using-variables.md rename to website/docs/docs/build/project-variables.md index 72c8ba01298..04d713756d7 100644 --- a/website/docs/docs/building-a-dbt-project/building-models/using-variables.md +++ b/website/docs/docs/build/project-variables.md @@ -1,6 +1,6 @@ --- -title: "Using variables" -id: "using-variables" +title: "Project variables" +id: "project-variables" --- dbt provides a mechanism, [variables](reference/dbt-jinja-functions/var), to provide data to models for @@ -98,3 +98,6 @@ The order of precedence for variable declaration is as follows (highest priority 4. The variable's default argument (if one is provided). If dbt is unable to find a definition for a variable after checking these four places, then a compilation error will be raised. + + + diff --git a/website/docs/docs/build/projects.md b/website/docs/docs/build/projects.md new file mode 100644 index 00000000000..8f985e7e6a4 --- /dev/null +++ b/website/docs/docs/build/projects.md @@ -0,0 +1,72 @@ +--- +title: "About dbt projects" +id: "projects" +--- + +A dbt project informs dbt the context of your project and how to transform your data (build your data sets). By design, dbt enforces the top-level structure of a dbt project such as the `dbt_project.yml` file, the `models` directory, the `snapshots` directory, and so on. Within the directories of the top-level, you can organize your project in any way that meets the needs of your organization and data pipeline. + +At a minimum, all a project needs is the `dbt_project.yml` project configuration file. dbt supports a number of different resources, so a project may also include: + +| Resource | Description | +| :--- | :--- | +| [models](/docs/build/models) | Each model lives in a single file and contains logic that either transforms raw data into a dataset that is ready for analytics or, more often, is an intermediate step in such a transformation. | +| [snapshots](/docs/build/snapshots) | A way to capture the state of your mutable tables so you can refer to it later. | +| [seeds](/docs/build/seeds) | CSV files with static data that you can load into your data platform with dbt. | +| [tests](/docs/build/tests) | SQL queries that you can write to test the models and resources in your project. | +| [macros](/docs/build/jinja-macros) | Blocks of code that you can reuse multiple times. | +| [docs](/docs/collaborate/documentation) | Docs for your project that you can build. | +| [sources](/docs/build/sources) | A way to name and describe the data loaded into your warehouse by your Extract and Load tools. | +| [exposures](/docs/build/exposures) | A way to define and describe a downstream use of your project. | +| [metrics](/docs/build/metrics) | A way for you to define metrics for your project. | +| [analysis](/docs/build/analyses) | A way to organize analytical SQL queries in your project such as the general ledger from your QuickBooks. | + +When building out the structure of your project, you should consider these impacts to your organization's workflow: + +* **How would people run dbt commands** — Selecting a path +* **How would people navigate within the project** — Whether as developers in the IDE or stakeholders from the docs +* **How would people configure the models** — Some bulk configurations are easier done at the directory level so people don’t have to remember to do everything in a config block with each new model + +## Project configuration +Every dbt project includes a project configuration file called `dbt_project.yml`. It defines the directory of the dbt project and other project configurations. + +Edit `dbt_project.yml` to set up common project configurations such as: + +
+ +| YAML key | Value description | +| :--- | :--- | +| [name](/reference/project-configs/name) | Your project’s name in [snake case](https://en.wikipedia.org/wiki/Snake_case) | +| [version](/reference/project-configs/version) | Version of your project | +| [require-dbt-version](/reference/project-configs/require-dbt-version) | Restrict your project to only work with a range of [dbt Core versions](/docs/dbt-versions/core) | +| [profile](/reference/project-configs/profile) | The profile dbt uses to connect to your data platform | +| [model-paths](/reference/project-configs/model-paths) | Directories to where your model and source files live | +| [seed-paths](/reference/project-configs/seed-paths) | Directories to where your seed files live | +| [test-paths](/reference/project-configs/test-paths) | Directories to where your test files live | +| [analysis-paths](/reference/project-configs/analysis-paths) | Directories to where your analyses live | +| [macro-paths](/reference/project-configs/macro-paths) | Directories to where your macros live | +| [snapshot-paths](/reference/project-configs/snapshot-paths) | Directories to where your snapshots live | +| [docs-paths](/reference/project-configs/docs-paths) | Directories to where your docs blocks live | +| [vars](/docs/build/project-variables) | Project variables you want to use for data compilation | + +
+ +For complete details on project configurations, see [dbt_project.yml](/reference/dbt_project.yml). + +## New projects + +You can create new projects and [share them](/docs/collaborate/git-version-control) with other people by making them available on a hosted git repository like GitHub, GitLab, and BitBucket. + +After you set up a connection with your data platform, you can [initialize your new project in dbt Cloud](/docs/develop/getting-started/getting-set-up/setting-up-bigquery#initialize-your-dbt-project) and start developing. Or, run [dbt init from the command line](/reference/commands/init) to set up your new project. + +During project initialization, dbt creates sample model files in your project directory to help you start developing quickly. + +## Sample projects + +If you want to explore dbt projects more in-depth, you can clone dbt Lab’s [Jaffle shop](https://github.com/dbt-labs/jaffle_shop) on GitHub. It's a runnable project that contains sample configurations and helpful notes. + +If you want to see what a mature, production project looks like, check out the [GitLab Data Team public repo](https://gitlab.com/gitlab-data/analytics/-/tree/master/transform/snowflake-dbt). + +## Related docs +- [Best practices: How we structure our dbt projects](/guides/best-practices/how-we-structure/1-guide-overview) +* [Get started with dbt Cloud](/docs/get-started/getting-started/set-up-dbt-cloud) +* [Get started with dbt Core](/docs/get-started/getting-started-dbt-core) diff --git a/website/docs/docs/build/python-models.md b/website/docs/docs/build/python-models.md new file mode 100644 index 00000000000..3f213f1fdca --- /dev/null +++ b/website/docs/docs/build/python-models.md @@ -0,0 +1,648 @@ +--- +title: "Python models" +id: "python-models" +--- +- [Overview](#overview) +- [Configuring Python Models](#configuring-python-models) +- [Python Specific Functionality](#configuring-python-models) +- [Limitations](#limitations) +- [Supported data platforms](#supported-data-platforms) + +dbt Core v1.3 adds support for Python models. Note that only [specific data platforms](#specific-data-platforms) support dbt-py models. + +We encourage you to: +- Read [the original discussion](https://github.com/dbt-labs/dbt-core/discussions/5261) that proposed this feature. +- Contribute to [best practices for developing Python models in dbt](https://github.com/dbt-labs/docs.getdbt.com/discussions/1811). +- Weigh in on [next steps for Python models, beyond v1.3](https://github.com/dbt-labs/dbt-core/discussions/5742). +- Join the **#beta-feedback-python-models** channel in the [dbt Community Slack](https://www.getdbt.com/community/join-the-community/). + + +In the following article, you'll see a section titled "❓ **dbt questions**." We are excited to release the first set of functionality in v1.3, which will solve real use cases. We also know this is the first step toward a much wider field of possibility. We don't pretend to have all the answers. + +We're excited to keep developing our opinionated recommendations and next steps for product development, and we want your help. Comment in the GitHub discussions; leave thoughts in Slack; bring up dbt + Python in casual conversation with colleagues and friends. + + +## Overview + +dbt Python ("dbt-py") models will help you solve use cases that can't be solved with SQL. You can perform analyses using tools available in the open-source Python ecosystem, including state-of-the-art packages for data science and statistics. Before, you would have needed separate infrastructure and orchestration to run Python transformations in production. Python transformations defined in dbt are models in your project with all the same capabilities around testing, documentation, and lineage. + + + +Python models are supported in dbt Core 1.3 and higher. Learn more about [upgrading your version in dbt Cloud](https://docs.getdbt.com/docs/dbt-cloud/cloud-configuring-dbt-cloud/cloud-upgrading-dbt-versions) and [upgrading dbt Core versions](https://docs.getdbt.com/docs/core-versions#upgrading-to-new-patch-versions). + +To read more about Python models, change the [docs version to 1.3](/docs/build/python-models?version=1.3) (or higher) in the menu bar. + + + + + + + + +```python +import ... + +def model(dbt, session): + + my_sql_model_df = dbt.ref("my_sql_model") + + final_df = ... # stuff you can't write in SQL! + + return final_df +``` + + + + + +```yml +version: 2 + +models: + - name: my_python_model + + # Document within the same codebase + description: My transformation written in Python + + # Configure in ways that feel intuitive and familiar + config: + materialized: table + tags: ['python'] + + # Test the results of my Python transformation + columns: + - name: id + # Standard validation for 'grain' of Python results + tests: + - unique + - not_null + tests: + # Write your own validation logic (in SQL) for Python results + - [custom_generic_test](writing-custom-generic-tests) +``` + + + + + + +The prerequisites for dbt Python models include using an adapter for a data platform that supports a fully featured Python runtime. In a dbt Python model, all Python code is executed remotely on the platform. None of it is run by dbt locally. We believe in clearly separating _model definition_ from _model execution_. In this and many other ways, you'll find that dbt's approach to Python models mirrors its longstanding approach to modeling data in SQL. + +We've written this guide assuming that you have some familiarity with dbt. If you've never before written a dbt model, we encourage you to start by first reading [dbt Models](building-models). Throughout, we'll be drawing connections between Python models and SQL models, as well as making clear their differences. + +### What is a Python model? + +A dbt Python model is a function that reads in dbt sources or other models, applies a series of transformations, and returns a transformed dataset. DataFrame operations define the starting points, the end state, and each step along the way. + +This is similar to the role of CTEs in dbt SQL models. We use CTEs to pull in upstream datasets, define (and name) a series of meaningful transformations, and end with a final `select` statement. You can run the compiled version of a dbt SQL model to see the data included in the resulting view or table. When you `dbt run`, dbt wraps that query in `create view`, `create table`, or more complex DDL to save its results in the database. + +Instead of a final `select` statement, each Python model returns a final DataFrame. Each DataFrame operation is "lazily evaluated." In development, you can preview its data, using methods like `.show()` or `.head()`. When you run a Python model, the full result of the final DataFrame will be saved as a table in your data warehouse. + +dbt Python models have access to almost all of the same configuration options as SQL models. You can test them, document them, add `tags` and `meta` properties to them, grant access to their results to other users, and so on. You can select them by their name, their file path, configurations, whether they are upstream or downstream of another model, or if they have been modified compared to a previous project state. + +### Defining a Python model + +Each Python model lives in a `.py` file in your `models/` folder. It defines a function named **`model()`**, which takes two parameters: +- **`dbt`**: A class compiled by dbt Core, unique to each model, enables you to run your Python code in the context of your dbt project and DAG. +- **`session`**: A class representing your data platform’s connection to the Python backend. The session is needed to read in tables as DataFrames, and to write DataFrames back to tables. In PySpark, by convention, the `SparkSession` is named `spark`, and available globally. For consistency across platforms, we always pass it into the `model` function as an explicit argument called `session`. + +The `model()` function must return a single DataFrame. On Snowpark (Snowflake), this can be a Snowpark or pandas DataFrame. Via PySpark (Databricks + BigQuery), this can be a Spark, pandas, or pandas-on-Spark DataFrame. For more about choosing between pandas and native DataFrames, see [DataFrame API + syntax](#dataframe-api--syntax). + +When you `dbt run --select python_model`, dbt will prepare and pass in both arguments (`dbt` and `session`). All you have to do is define the function. This is how every single Python model should look: + + + +```python +def model(dbt, session): + + ... + + return final_df +``` + + + + +### Referencing other models + +Python models participate fully in dbt's directed acyclic graph (DAG) of transformations. Use the `dbt.ref()` method within a Python model to read data from other models (SQL or Python). If you want to read directly from a raw source table, use `dbt.source()`. These methods return DataFrames pointing to the upstream source, model, seed, or snapshot. + + + +```python +def model(dbt, session): + + # DataFrame representing an upstream model + upstream_model = dbt.ref("upstream_model_name") + + # DataFrame representing an upstream source + upstream_source = dbt.source("upstream_source_name", "table_name") + + ... +``` + + + +Of course, you can `ref()` your Python model in downstream SQL models, too: + + + +```sql +with upstream_python_model as ( + + select * from {{ ref('my_python_model') }} + +), + +... +``` + + + +## Configuring Python models + +Just like SQL models, there are three ways to configure Python models: +1. In `dbt_project.yml`, where you can configure many models at once +2. In a dedicated `.yml` file, within the `models/` directory +3. Within the model's `.py` file, using the `dbt.config()` method + +Calling the `dbt.config()` method will set configurations for your model within your `.py` file, similar to the `{{ config() }}` macro in `.sql` model files: + + + +```python +def model(dbt, session): + + # setting configuration + dbt.config(materialized="table") +``` + + + +There's a limit to how complex you can get with the `dbt.config()` method. It accepts _only_ literal values (strings, booleans, and numeric types). Passing another function or a more complex data structure is not possible. The reason is that dbt statically analyzes the arguments to `config()` while parsing your model without executing your Python code. If you need to set a more complex configuration, we recommend you define it using the [`config` property](resource-properties/config) in a YAML file. + +#### Accessing project context + +dbt Python models don't use Jinja to render compiled code. Python models have limited access to global project contexts compared to SQL models. That context is made available from the `dbt` class, passed in as an argument to the `model()` function. + +Out of the box, the `dbt` class supports: +- Returning DataFrames referencing the locations of other resources: `dbt.ref()` + `dbt.source()` +- Accessing the database location of the current model: `dbt.this()` (also: `dbt.this.database`, `.schema`, `.identifier`) +- Determining if the current model's run is incremental: `dbt.is_incremental` + +It is possible to extend this context by "getting" them via `dbt.config.get()` after they are configured in the [model's config](/reference/model-configs). This includes inputs such as `var`, `env_var`, and `target`. If you want to use those values to power conditional logic in your model, we require setting them through a dedicated `.yml` file config: + + + +```yml +version: 2 + +models: + - name: my_python_model + config: + materialized: table + target_name: "{{ target.name }}" + specific_var: "{{ var('SPECIFIC_VAR') }}" + specific_env_var: "{{ env_var('SPECIFIC_ENV_VAR') }}" +``` + + + +Then, within the model's Python code, use the `dbt.config.get()` function to _access_ values of configurations that have been set: + + + +```python +def model(dbt, session): + target_name = dbt.config.get("target_name") + specific_var = dbt.config.get("specific_var") + specific_env_var = dbt.config.get("specific_env_var") + + orders_df = dbt.ref("fct_orders") + + # limit data in dev + if target_name == "dev": + orders_df = orders_df.limit(500) +``` + + + +### Materializations + +Python models support dbt Materializations. To learn more about them visit the [Materializations page](/docs/build/materializations.md) + +## Python-specific functionality + +### Defining functions + +In addition to defining a `model` function, the Python model can import other functions or define its own. Here's an example on Snowpark, defining a custom `add_one` function: + + + +```python +def add_one(x): + return x + 1 + +def model(dbt, session): + dbt.config(materialized="table") + temps_df = dbt.ref("temperatures") + + # warm things up just a little + df = temps_df.withColumn("degree_plus_one", add_one(temps_df["degree"])) + return df +``` + + + +Currently, Python functions defined in one dbt model can't be imported and reused in other models. See the ["Code reuse"](#code-reuse) section for the potential patterns we're considering. + +### Using PyPI packages + +You can also define functions that depend on third-party packages so long as those packages are installed and available to the Python runtime on your data platform. See notes on "Installing Packages" for [specific data warehouses](#specific-data-warehouses). + +In this example, we use the `holidays` package to determine if a given date is a holiday in France. The code below uses the pandas API for simplicity and consistency across platforms. The exact syntax, and the need to refactor for multi-node processing, still vary. + + + +
+ + + +```python +import holidays + +def is_holiday(date_col): + # Chez Jaffle + french_holidays = holidays.France() + is_holiday = (date_col in french_holidays) + return is_holiday + +def model(dbt, session): + dbt.config( + materialized = "table", + packages = ["holidays"] + ) + + orders_df = dbt.ref("stg_orders") + + df = orders_df.to_pandas() + + # apply our function + # (columns need to be in uppercase on Snowpark) + df["IS_HOLIDAY"] = df["ORDER_DATE"].apply(is_holiday) + + # return final dataset (Pandas DataFrame) + return df +``` + + + +
+ +
+ + + +```python +import holidays + +def is_holiday(date_col): + # Chez Jaffle + french_holidays = holidays.France() + is_holiday = (date_col in french_holidays) + return is_holiday + +def model(dbt, session): + dbt.config( + materialized = "table", + packages = ["holidays"] + ) + + orders_df = dbt.ref("stg_orders") + + df = orders_df.to_pandas_on_spark() # Spark 3.2+ + # df = orders_df.toPandas() in earlier versions + + # apply our function + df["is_holiday"] = df["order_date"].apply(is_holiday) + + # convert back to PySpark + df = df.to_spark() # Spark 3.2+ + # df = session.createDataFrame(df) in earlier versions + + # return final dataset (PySpark DataFrame) + return df +``` + + + +
+ + + +#### Configuring packages + +We encourage you to configure required packages and versions so dbt can track them in project metadata. This configuration is required for the implementation on some platforms. If you need specific versions of packages, specify them. + + + +```python +def model(dbt, session): + dbt.config( + packages = ["numpy==1.23.1", "scikit-learn"] + ) +``` + + + + + +```yml +version: 2 + +models: + - name: my_python_model + config: + packages: + - "numpy==1.23.1" + - scikit-learn +``` + + + +#### User-defined functions (UDFs) + +You can use the `@udf` decorator or `udf` function to define an "anonymous" function and call it within your `model` function's DataFrame transformation. This is a typical pattern for applying more complex functions as DataFrame operations, especially if those functions require inputs from third-party packages. +- [Snowpark Python: Creating s](https://docs.snowflake.com/en/developer-guide/snowpark/python/creating-udfs.html) +- ["PySpark functions: udf"](https://spark.apache.org/docs/latest/api/python/reference/pyspark.sql/api/pyspark.sql.functions.udf.html) + + + +
+ + + +```python +import snowflake.snowpark.types as T +import snowflake.snowpark.functions as F +import numpy + +def register_udf_add_random(): + add_random = F.udf( + # use 'lambda' syntax, for simple functional behavior + lambda x: x + numpy.random.normal(), + return_type=T.FloatType(), + input_types=[T.FloatType()] + ) + return add_random + +def model(dbt, session): + + dbt.config( + materialized = "table", + packages = ["numpy"] + ) + + temps_df = dbt.ref("temperatures") + + add_random = register_udf_add_random() + + # warm things up, who knows by how much + df = temps_df.withColumn("degree_plus_random", add_random("degree")) + return df +``` + + + +**Note:** Due to a Snowpark limitation, it is not currently possible to register complex named UDFs within stored procedures and, therefore, dbt Python models. We are looking to add native support for Python UDFs as a project/DAG resource type in a future release. For the time being, if you want to create a "vectorized" Python UDF via the Batch API, we recommend either: +- Writing [`create function`](https://docs.snowflake.com/en/developer-guide/udf/python/udf-python-batch.html) inside a SQL macro, to run as a hook or run-operation +- [Registering from a staged file](https://docs.snowflake.com/ko/developer-guide/snowpark/reference/python/_autosummary/snowflake.snowpark.udf.html#snowflake.snowpark.udf.UDFRegistration.register_from_file) within your Python model code + +
+ +
+ + + +```python +from pyspark.sql.types as T +import pyspark.sql.functions as F +import numpy + +# use a 'decorator' for more readable code +@F.udf(returnType=T.DoubleType()) +def add_random(x): + random_number = numpy.random.normal() + return x + random_number + +def model(dbt, session): + dbt.config( + materialized = "table", + packages = ["numpy"] + ) + + temps_df = dbt.ref("temperatures") + + # warm things up, who knows by how much + df = temps_df.withColumn("degree_plus_random", add_random("degree")) + return df +``` + + + +
+ + + +#### Code reuse + +Currently, Python functions defined in one dbt model cannot be imported and reused in other models. This is something wdbt would like to support, so there are two patterns we're considering: +1. Creating and registering **"named" UDFs** — This process is different across data platforms and has some performance limitations. (Snowpark does support ["vectorized" UDFs](https://docs.snowflake.com/en/developer-guide/udf/python/udf-python-batch.html): Pandas-like functions that can be executed in parallel.) +2. **Private Python packages** — In addition to importing reusable functions from public PyPI packages, many data platforms support uploading custom Python assets and registering them as packages. The upload process looks different across platforms, but your code’s actual `import` looks the same. + +:::note ❓ dbt questions + +- Should dbt have a role in abstracting over UDFs? Should dbt support a new type of DAG node, `function`? Would the primary use case be code reuse across Python models or defining Python-language functions that can be called from SQL models? +- How can dbt help users when uploading or initializing private Python assets? Is this a new form of `dbt deps`? +- How can dbt support users who want to test custom functions? If defined as UDFs: "unit testing" in the database? If "pure" functions in packages: encourage adoption of `pytest`? + +💬 Discussion: ["Python models: package, artifact/object storage, and UDF management in dbt"](https://github.com/dbt-labs/dbt-core/discussions/5741) +::: + +### DataFrame API and syntax + +Over the past decade, most people writing data transformations in Python have adopted DataFrame as their common abstraction. dbt follows this convention by returning `ref()` and `source()` as DataFrames, and it expects all Python models to return a DataFrame. + +A DataFrame is a two-dimensional data structure (rows and columns). It supports convenient methods for transforming that data and creating new columns from calculations performed on existing columns. It also offers convenient ways for previewing data while developing locally or in a notebook. + +That's about where the agreement ends. There are numerous frameworks with their own syntaxes and APIs for DataFrames. The [pandas](https://pandas.pydata.org/docs/) library offered one of the original DataFrame APIs, and its syntax is the most common to learn for new data professionals. Most newer DataFrame APIs are compatible with pandas-style syntax, though few can offer perfect interoperability. This is true for Snowpark and PySpark, which have their own DataFrame APIs. + +When developing a Python model, you will find yourself asking these questions: + +**Why pandas?** — It's the most common API for DataFrames. It makes it easy to explore sampled data and develop transformations locally. You can “promote” your code as-is into dbt models and run it in production for small datasets. + +**Why _not_ pandas?** — Performance. pandas runs "single-node" transformations, which cannot benefit from the parallelism and distributed computing offered by modern data warehouses. This quickly becomes a problem as you operate on larger datasets. Some data platforms support optimizations for code written using pandas' DataFrame API, preventing the need for major refactors. For example, ["pandas on PySpark"](https://spark.apache.org/docs/latest/api/python/getting_started/quickstart_ps.html) offers support for 95% of pandas functionality, using the same API while still leveraging parallel processing. + +:::note ❓ dbt questions +- When developing a new dbt Python model, should we recommend pandas-style syntax for rapid iteration and then refactor? +- Which open source libraries provide compelling abstractions across different data engines and vendor-specific APIs? +- Should dbt attempt to play a longer-term role in standardizing across them? + +💬 Discussion: ["Python models: the pandas problem (and a possible solution)"](https://github.com/dbt-labs/dbt-core/discussions/5738) +::: + +## Limitations + +Python models have capabilities that SQL models do not. They also have some drawbacks compared to SQL models: + +- **Time and cost.** Python models are slower to run than SQL models, and the cloud resources that run them can be more expensive. Running Python requires more general-purpose compute. That compute might sometimes live on a separate service or architecture from your SQL models. **However:** We believe that deploying Python models via dbt—with unified lineage, testing, and documentation—is, from a human standpoint, **dramatically** faster and cheaper. By comparison, spinning up separate infrastructure to orchestrate Python transformations in production and different tooling to integrate with dbt is much more time-consuming and expensive. +- **Syntax differences** are even more pronounced. Over the years, dbt has done a lot, via dispatch patterns and packages such as `dbt_utils`, to abstract over differences in SQL dialects across popular data warehouses. Python offers a **much** wider field of play. If there are five ways to do something in SQL, there are 500 ways to write it in Python, all with varying performance and adherence to standards. Those options can be overwhelming. As the maintainers of dbt, we will be learning from state-of-the-art projects tackling this problem and sharing guidance as we develop it. +- **These capabilities are very new.** As data warehouses develop new features, we expect them to offer cheaper, faster, and more intuitive mechanisms for deploying Python transformations. **We reserve the right to change the underlying implementation for executing Python models in future releases.** Our commitment to you is around the code in your model `.py` files, following the documented capabilities and guidance we're providing here. + +As a general rule, if there's a transformation you could write equally well in SQL or Python, we believe that well-written SQL is preferable: it's more accessible to a greater number of colleagues, and it's easier to write code that's performant at scale. If there's a transformation you _can't_ write in SQL, or where ten lines of elegant and well-annotated Python could save you 1000 lines of hard-to-read Jinja-SQL, Python is the way to go. + +## Supported data platforms + +In their initial launch, Python models are supported on three of the most popular data platforms: Snowflake, Databricks, and BigQuery/GCP (via Dataproc). Both Databricks and GCP's Dataproc use PySpark as the processing framework. Snowflake uses its own framework, Snowpark, which has many similarities to PySpark. + + + +
+ +**Additional setup:** Snowpark Python is in Public Preview - Open and enabled by default for all accounts. You will need to [acknowledge and accept Snowflake Third Party Terms](https://docs.snowflake.com/en/developer-guide/udf/python/udf-python-packages.html#getting-started) to use Anaconda packages. + +**Installing packages:** Snowpark supports several popular packages via Anaconda. The complete list is at https://repo.anaconda.com/pkgs/snowflake/. Packages are installed at the time your model is being run. Different models can have different package dependencies. If you are using third-party packages, Snowflake recommends using a dedicated virtual warehouse for best performance rather than one with many concurrent users. + +**About "sprocs":** dbt submits Python models to run as "stored procedures," which some people call "sprocs" for short. By default, dbt will create a named sproc containing your model's compiled Python code, and then "call" it to execute. Snowpark has a Private Preview feature for "temporary" or "anonymous" stored procedures ([docs](https://docs.snowflake.com/en/LIMITEDACCESS/call-with.html)), which are faster and leave a cleaner query history. If this feature is enabled for your account, you can switch it on for your models by configuring `use_anonymous_sproc: True`. We plan to switch this on for all dbt + Snowpark Python models in a future release. + + + +```yml +# I asked Snowflake Support to enable this Private Preview feature, +# and now my dbt-py models run even faster! +models: + use_anonymous_sproc: True +``` + + + +**Docs:** ["Developer Guide: Snowpark Python"](https://docs.snowflake.com/en/developer-guide/snowpark/python/index.html) + +
+ +
+ +**Submission methods:** Databricks supports a few different mechanisms to submit PySpark code, each with relative advantages. Some are better for supporting iterative development, while others are better for supporting lower-cost production deployments. The options are: +- `all_purpose_cluster` (default): dbt will run your Python model using the cluster ID configured as `cluster` in your connection profile or for this specific model. These clusters are more expensive but also much more responsive. We recommend using an interactive all-purpose cluster for quicker iteration in development. + - `create_notebook: True`: dbt will upload your model's compiled PySpark code to a notebook in the namespace `/Shared/dbt_python_model/{schema}`, where `{schema}` is the configured schema for the model, and execute that notebook to run using the all-purpose cluster. The appeal of this approach is that you can easily open the notebook in the Databricks UI for debugging or fine-tuning right after running your model. Remember to copy any changes into your dbt `.py` model code before re-running. + - `create_notebook: False` (default): dbt will use the [Command API](https://docs.databricks.com/dev-tools/api/1.2/index.html#run-a-command), which is slightly faster. +- `job_cluster`: dbt will upload your model's compiled PySpark code to a notebook in the namespace `/Shared/dbt_python_model/{schema}`, where `{schema}` is the configured schema for the model, and execute that notebook to run using a short-lived jobs cluster. For each Python model, Databricks will need to spin up the cluster, execute the model's PySpark transformation, and then spin down the cluster. As such, job clusters take longer before and after model execution, but they're also less expensive, so we recommend these for longer-running Python models in production. To use the `job_cluster` submission method, your model must be configured with `job_cluster_config`, which defines key-value properties for `new_cluster`, as defined in the [JobRunsSubmit API](https://docs.databricks.com/dev-tools/api/latest/jobs.html#operation/JobsRunsSubmit). + +You can configure each model's `submission_method` in all the standard ways you supply configuration: + +```python +def model(dbt, session): + dbt.config( + submission_method="all_purpose_cluster", + create_notebook=True, + cluster_id="abcd-1234-wxyz" + ) + ... +``` +```yml +version: 2 +models: + - name: my_python_model + config: + submission_method: job_cluster + job_cluster_config: + spark_version: ... + node_type_id: ... +``` +```yml +# dbt_project.yml +models: + project_name: + subfolder: + # set defaults for all .py models defined in this subfolder + +submission_method: all_purpose_cluster + +create_notebook: False + +cluster_id: abcd-1234-wxyz +``` + +If not configured, `dbt-spark` will use the built-in defaults: the all-purpose cluster (based on `cluster` in your connection profile) without creating a notebook. The `dbt-databricks` adapter will default to the cluster configured in `http_path`. We encourage explicitly configuring the clusters for Python models in Databricks projects. + +**Installing packages:** When using all-purpose clusters, we recommend installing packages which you will be using to run your Python models. + +**Docs:** +- [PySpark DataFrame syntax](https://spark.apache.org/docs/latest/api/python/reference/pyspark.sql/api/pyspark.sql.DataFrame.html) +- [Databricks: Introduction to DataFrames - Python](https://docs.databricks.com/spark/latest/dataframes-datasets/introduction-to-dataframes-python.html) + +
+ +
+ +The `dbt-bigquery` adapter uses a service called Dataproc to submit your Python models as PySpark jobs. That Python/PySpark code will read from your tables and views in BigQuery, perform all computation in Dataproc, and write the final result back to BigQuery. + +**Submission methods.** Dataproc supports two submission methods: `serverless` and `cluster`. Dataproc Serverless does not require a ready cluster, which saves on hassle and cost—but it is slower to start up, and much more limited in terms of available configuration. For example, Dataproc Serverless supports only a small set of Python packages, though it does include `pandas`, `numpy`, and `scikit-learn`. (See the full list [here](https://cloud.google.com/dataproc-serverless/docs/guides/custom-containers#example_custom_container_image_build), under "The following packages are installed in the default image"). Whereas, by creating a Dataproc Cluster in advance, you can fine-tune the cluster's configuration, install any PyPI packages you want, and benefit from faster, more responsive runtimes. + +Use the `cluster` submission method with dedicated Dataproc clusters you or your organization manage. Use the `serverless` submission method to avoid managing a Spark cluster. The latter may be quicker for getting started, but both are valid for production. + +**Additional setup:** +- Create or use an existing [Cloud Storage bucket](https://cloud.google.com/storage/docs/creating-buckets) +- Enable Dataproc APIs for your project + region +- If using the `cluster` submission method: Create or use an existing [Dataproc cluster](https://cloud.google.com/dataproc/docs/guides/create-cluster) with the [Spark BigQuery connector initialization action](https://github.com/GoogleCloudDataproc/initialization-actions/tree/master/connectors#bigquery-connectors). (Google recommends copying the action into your own Cloud Storage bucket, rather than using the example version shown in the screenshot) + + + +The following configurations are needed to run Python models on Dataproc. You can add these to your [BigQuery profile](bigquery-profile) or configure them on specific Python models: +- `gcs_bucket`: Storage bucket to which dbt will upload your model's compiled PySpark code +- `dataproc_region`: GCP region in which you have enabled Dataproc (for example `us-central1`) +- `dataproc_cluster_name`: Name of Dataproc cluster to use for running Python model (executing PySpark job). Only required if `submission_method: cluster` + +```python +def model(dbt, session): + dbt.config( + submission_method="cluster", + dataproc_cluster_name="my-favorite-cluster" + ) + ... +``` +```yml +version: 2 +models: + - name: my_python_model + config: + submission_method: serverless +``` + +Any user or service account that runs dbt Python models will need the following permissions(in addition to the required BigQuery permissions) ([docs](https://cloud.google.com/dataproc/docs/concepts/iam/iam)): +``` +dataproc.clusters.use +dataproc.jobs.create +dataproc.jobs.get +dataproc.operations.get +storage.buckets.get +storage.objects.create +storage.objects.delete +``` + +**Installing packages:** If you are using a Dataproc Cluster (as opposed to Dataproc Serverless), you can add third-party packages while creating the cluster. + +Google recommends installing Python packages on Dataproc clusters via initialization actions: +- [How initialization actions are used](https://github.com/GoogleCloudDataproc/initialization-actions/blob/master/README.md#how-initialization-actions-are-used) +- [Actions for installing via `pip` or `conda`](https://github.com/GoogleCloudDataproc/initialization-actions/tree/master/python) + +You can also install packages at cluster creation time by [defining cluster properties](https://cloud.google.com/dataproc/docs/tutorials/python-configuration#image_version_20): `dataproc:pip.packages` or `dataproc:conda.packages`. + + + +**Docs:** +- [Dataproc overview](https://cloud.google.com/dataproc/docs/concepts/overview) +- [PySpark DataFrame syntax](https://spark.apache.org/docs/latest/api/python/reference/pyspark.sql/api/pyspark.sql.DataFrame.html) + +
+ + + + diff --git a/website/docs/docs/building-a-dbt-project/seeds.md b/website/docs/docs/build/seeds.md similarity index 97% rename from website/docs/docs/building-a-dbt-project/seeds.md rename to website/docs/docs/build/seeds.md index a0b935461f5..bd26c1fceea 100644 --- a/website/docs/docs/building-a-dbt-project/seeds.md +++ b/website/docs/docs/build/seeds.md @@ -7,7 +7,7 @@ id: "seeds" * [Seed properties](seed-properties) * [`seed` command](seed) -## Getting started +## Overview Seeds are CSV files in your dbt project (typically in your `seeds` directory), that dbt can load into your using the `dbt seed` command. Seeds can be referenced in downstream models the same way as referencing models — by using the [`ref` function](/reference/dbt-jinja-functions/ref). @@ -21,7 +21,7 @@ Good use-cases for seeds: Poor use-cases of dbt seeds: * Loading raw data that has been exported to CSVs -* Any kind of production data containing sensitive information. For example +* Any kind of production data containing sensitive information. For example personal identifiable information (PII) and passwords. @@ -86,4 +86,4 @@ You can document and test seeds in yaml by declaring properties — check out th - + \ No newline at end of file diff --git a/website/docs/docs/building-a-dbt-project/snapshots.md b/website/docs/docs/build/snapshots.md similarity index 97% rename from website/docs/docs/building-a-dbt-project/snapshots.md rename to website/docs/docs/build/snapshots.md index 1e3fe6bc7da..a204c0416c5 100644 --- a/website/docs/docs/building-a-dbt-project/snapshots.md +++ b/website/docs/docs/build/snapshots.md @@ -8,10 +8,10 @@ id: "snapshots" * [Snapshot properties](snapshot-properties) * [`snapshot` command](snapshot) -## Getting started +## Overview ### What are snapshots? -Commonly, analysts need to "look back in time" at some previous state of data in their mutable tables. While some source data systems are built in a way that makes accessing historical data possible, this is often not the case. dbt provides a mechanism, **snapshots**, which records changes to a mutable over time. +Analysts often need to "look back in time" at previous data states in their mutable tables. While some source data systems are built in a way that makes accessing historical data possible, this is not always the case. dbt provides a mechanism, **snapshots**, which records changes to a mutable over time. Snapshots implement [type-2 Slowly Changing Dimensions](https://en.wikipedia.org/wiki/Slowly_changing_dimension#Type_2:_add_new_row) over mutable source tables. These Slowly Changing Dimensions (or SCDs) identify how a row in a table changes over time. Imagine you have an `orders` table where the `status` field can be overwritten as the order is processed. @@ -347,7 +347,7 @@ For the `timestamp` strategy, the configured `updated_at` column is used to popu Details for the timestamp strategy Snapshot query results at `2019-01-01 11:00` - + | id | status | updated_at | | -- | ------- | ---------------- | | 1 | pending | 2019-01-01 10:47 | @@ -414,4 +414,4 @@ Snapshot results: - + \ No newline at end of file diff --git a/website/docs/docs/building-a-dbt-project/using-sources.md b/website/docs/docs/build/sources.md similarity index 98% rename from website/docs/docs/building-a-dbt-project/using-sources.md rename to website/docs/docs/build/sources.md index 663a05f90d2..08b0d793d5c 100644 --- a/website/docs/docs/building-a-dbt-project/using-sources.md +++ b/website/docs/docs/build/sources.md @@ -1,6 +1,6 @@ --- title: "Sources" -id: "using-sources" +id: "sources" --- ## Related reference docs @@ -84,7 +84,7 @@ You can also: - Add tests to sources - Add descriptions to sources, that get rendered as part of your documentation site -These should be familiar concepts if you've already added tests and descriptions to your models (if not check out the guides on [testing](building-a-dbt-project/tests) and [documentation](documentation)). +These should be familiar concepts if you've already added tests and descriptions to your models (if not check out the guides on [testing](/docs/build/tests) and [documentation](documentation)). diff --git a/website/docs/docs/building-a-dbt-project/building-models.md b/website/docs/docs/build/sql-models.md similarity index 69% rename from website/docs/docs/building-a-dbt-project/building-models.md rename to website/docs/docs/build/sql-models.md index 3477ed45734..0660684f015 100644 --- a/website/docs/docs/building-a-dbt-project/building-models.md +++ b/website/docs/docs/build/sql-models.md @@ -1,6 +1,6 @@ --- -title: "dbt Models" -id: "building-models" +title: "SQL models" +id: "sql-models" --- ## Related reference docs @@ -13,24 +13,24 @@ id: "building-models" :::info Building your first models -If you're new to dbt, we recommend that you check out our [Getting Started guide](/guides/getting-started) to build your first dbt project with models. +If you're new to dbt, we recommend that you read the [Getting Started guide](/docs/get-started/getting-started/overview) to build your first dbt project with models. ::: -In v1.3, dbt Core is adding support for **Python models**. +Starting in v1.3, dbt Core adds support for **Python models**. -dbt's Python capabilities are an extension of its capabilities with SQL models, which are introduced in the discussion and examples below. If you're new to dbt, we recommend that you read this page first, before reading: ["Python Models"](python-models) +dbt's Python capabilities are an extension of its capabilities with SQL models. If you're new to dbt, we recommend that you read this page first, before reading: ["Python Models"](python-models) -A model is a `select` statement. Models are defined in `.sql` files (typically in your `models` directory): +A SQL model is a `select` statement. Models are defined in `.sql` files (typically in your `models` directory): - Each `.sql` file contains one model / `select` statement -- The name of the file is used as the model name +- The model name is inherited from the filename. - Models can be nested in subdirectories within the `models` directory -When you execute the [`dbt run` command](run), dbt will build this model in your by wrapping it in a `create view as` or `create table as` statement. +When you execute the [`dbt run` command](run), dbt will build this model by wrapping it in a `create view as` or `create table as` statement. For example, consider this `customers` model: @@ -64,7 +64,7 @@ left join customer_orders using (customer_id) -When you execute `dbt run`, dbt will build this as a named `customers` in your target schema: +When you execute `dbt run`, dbt will build this as a _view_ named `customers` in your target schema: ```sql create view dbt_alice.customers as ( @@ -95,11 +95,11 @@ create view dbt_alice.customers as ( ``` Why a _view_ named `dbt_alice.customers`? By default dbt will: -* create models as views -* build models in a target schema you define -* use your file name as the view or name in the database +* Create models as views +* Build models in a target schema you define +* Use your file name as the view or name in the database -You can use _configurations_ to change any of these behaviors — more on that below. +You can use _configurations_ to change any of these behaviors — more on that later. ### FAQs @@ -110,8 +110,9 @@ You can use _configurations_ to change any of these behaviors — more on that b ## Configuring models Configurations are "model settings" that can be set in your `dbt_project.yml` file, _and_ in your model file using a `config` block. Some example configurations include: -* Change the [materialization](materializations) that a model uses — a determines the SQL that dbt uses to create the model in your warehouse. -* Build models into separate [schemas](using-custom-schemas). + +* Changing the that a model uses — a [materialization](materializations) determines the SQL that dbt uses to create the model in your warehouse. +* Build models into separate [schemas](/docs/build/custom-schemas). * Apply [tags](resource-configs/tags) to a model. Here's an example of model configuration: @@ -151,7 +152,7 @@ with customer_orders as ... -Importantly, configurations are applied hierarchically — a configuration applied to a subdirectory will override any general configurations. +It is important to note that configurations are applied hierarchically — a configuration applied to a subdirectory will override any general configurations. You can learn more about configurations in the [reference docs](model-configs). @@ -161,7 +162,7 @@ You can learn more about configurations in the [reference docs](model-configs). ## Building dependencies between models -By using the [`ref` function](ref) in the place of table names in a query, you can build dependencies between models. Use the name of another model as the argument for `ref`. +You can build dependencies between models by using the [`ref` function](ref) in place of table names in a query. Use the name of another model as the argument for `ref`. -* Manage separate environments — dbt will replace the model specified in the `ref` function with the database name for the (or view). Importantly, this is environment-aware — if you're running dbt with a target schema named `dbt_alice`, it will select from an upstream table in the same schema. Check out the tabs above to see this in action. +* Manage separate environments — dbt will replace the model specified in the `ref` function with the database name for the (or view). Importantly, this is environment-aware — if you're running dbt with a target schema named `dbt_alice`, it will select from an upstream table in the same schema. Check out the tabs above to see this in action. Additionally, the `ref` function encourages you to write modular transformations, so that you can re-use models, and reduce repeated code. ## Testing and documenting models -You can also document and test models — skip ahead to the section on [testing](building-a-dbt-project/tests) and [documentation](documentation) for more information. +<<<<<<< HEAD +You can also document and test models — skip ahead to the section on [testing](/docs/build/tests) and [documentation](documentation) for more information. +======= +You can also document and test models — skip ahead to the section on [testing](building-a-dbt-project/tests) and [documentation](documentation) for more information. +>>>>>>> next ## Additional FAQs diff --git a/website/docs/docs/building-a-dbt-project/tests.md b/website/docs/docs/build/tests.md similarity index 90% rename from website/docs/docs/building-a-dbt-project/tests.md rename to website/docs/docs/build/tests.md index 04fa4f43506..f8523a19fc3 100644 --- a/website/docs/docs/building-a-dbt-project/tests.md +++ b/website/docs/docs/build/tests.md @@ -1,5 +1,6 @@ --- title: "Tests" +id: "tests" --- ## Related reference docs @@ -8,10 +9,12 @@ title: "Tests" * [Test configurations](test-configs) * [Test selection examples](test-selection-examples) -## Getting started +## Overview Tests are assertions you make about your models and other resources in your dbt project (e.g. sources, seeds and snapshots). When you run `dbt test`, dbt will tell you if each test in your project passes or fails. +You can use tests to improve the integrity of the SQL in each model by making assertions about the results generated. Out of the box, you can test whether a specified column in a model only contains non-null values, unique values, or values that have a corresponding value in another model (for example, a `customer_id` for an `order` corresponds to an `id` in the `customers` model), and values from a specified list. You can extend tests to suit business logic specific to your organization – any assertion that you can make about your model in the form of a select query can be turned into a test. + * `v0.20.0`: Both types of tests return a set of failing records. Previously, generic/schema tests returned a numeric value representing failures. Generic tests (f.k.a. schema tests) are defined using `test` blocks instead of macros prefixed `test_`. @@ -27,7 +30,7 @@ There are two ways of defining tests in dbt: Defining tests is a great way to confirm that your code is working correctly, and helps prevent regressions when your code changes. Because you can use them over and over again, making similar assertions with minor variations, generic tests tend to be much more common—they should make up the bulk of your dbt testing suite. That said, both ways of defining tests have their time and place. :::tip Creating your first tests -If you're new to dbt, we recommend that you check out our [Getting Started guide](/guides/getting-started) to build your first dbt project with models and tests. +If you're new to dbt, we recommend that you check out our [Getting Started guide](/docs/get-started/getting-started/overview) to build your first dbt project with models and tests. ::: ## Singular tests @@ -112,7 +115,7 @@ You can find more information about these tests, and additional configurations ( Those four tests are enough to get you started. You'll quickly find you want to use a wider variety of tests—a good thing! You can also install generic tests from a package, or write your own, to use (and reuse) across your dbt project. Check out the [guide on custom generic tests](custom-generic-tests) for more information. :::info -There are generic tests defined in some open source packages, such as [dbt-utils](https://hub.getdbt.com/dbt-labs/dbt_utils/latest/) and [dbt-expectations](https://hub.getdbt.com/calogica/dbt_expectations/latest/) — skip ahead to the docs on [packages](package-management) to learn more! +There are generic tests defined in some open source packages, such as [dbt-utils](https://hub.getdbt.com/dbt-labs/dbt_utils/latest/) and [dbt-expectations](https://hub.getdbt.com/calogica/dbt_expectations/latest/) — skip ahead to the docs on [packages](/docs/build/packages) to learn more! ::: ### Example @@ -251,7 +254,7 @@ This workflow allows you to query and examine failing records much more quickly Note that, if you elect to store test failures: -- Test result tables are created in a schema suffixed or named `dbt_test__audit`, by default. It is possible to change this value by setting a `schema` config. (For more details on schema naming, see [using custom schemas](using-custom-schemas).) +* Test result tables are created in a schema suffixed or named `dbt_test__audit`, by default. It is possible to change this value by setting a `schema` config. (For more details on schema naming, see [using custom schemas](/docs/build/custom-schemas).) - A test's results will always **replace** previous failures for the same test. ## FAQs @@ -263,9 +266,4 @@ Note that, if you elect to store test failures: - - - + \ No newline at end of file diff --git a/website/docs/docs/building-a-dbt-project/archival.md b/website/docs/docs/building-a-dbt-project/archival.md deleted file mode 100644 index 86fe28bb7e3..00000000000 --- a/website/docs/docs/building-a-dbt-project/archival.md +++ /dev/null @@ -1,15 +0,0 @@ ---- -title: "Archives" -id: "archival" ---- - - -:::info Archives are now Snapshots! - -Archives have been renamed to "Snapshots" in dbt v0.14.0. Check out the docs on [Snapshots](snapshots) for more information. - -::: - - - - diff --git a/website/docs/docs/building-a-dbt-project/projects.md b/website/docs/docs/building-a-dbt-project/projects.md deleted file mode 100644 index 349696a1fe6..00000000000 --- a/website/docs/docs/building-a-dbt-project/projects.md +++ /dev/null @@ -1,90 +0,0 @@ ---- -title: "Projects" -id: "projects" ---- - -## Related reference docs -* [`dbt_project.yml` configurations](reference/dbt_project.yml.md) -* The [`dbt init` command](init) - -## Getting started -A dbt project is a directory of `.sql` and `.yml` files, which dbt uses to transform your data. At a minimum, a dbt project must contain: -* A project file: A `dbt_project.yml` file tells dbt that a particular directory is a dbt project, and also contains configurations for your project. -* [Models](building-models): A model is a single `.sql` file. Each model contains a single select statement that either transforms raw data into a dataset that is ready for analytics, or, more often, is an intermediate step in such a transformation. - -A project may also contain a number of other resources, such as [snapshots](snapshots), [seeds](seeds), [tests](building-a-dbt-project/tests), [macros](jinja-macros#macros), [documentation](documentation), and [sources](using-sources). - -## Creating a dbt project - -:::info Creating your first dbt project - -If you're new to dbt, we recommend that you check out our [Getting Started guide](/guides/getting-started) to build your first dbt project. - -::: - -If you don't yet have a dbt project, follow these instructions to create one. The dbt [starter project](https://github.com/dbt-labs/dbt-starter-project) contains default configurations as well as helpful notes. - - - - - -To create a new dbt project when developing in dbt Cloud: - -1. Create a dbt Cloud account [here](https://cloud.getdbt.com/signup/). If your organization already has a dbt Cloud account, ask an admin to add you as a Developer. -2. If you created a new account, a new project should automatically be created. If you were added to an existing account: - * Click the gear icon to the top right, then **Projects** under Account Settings. - * Name your project, and click **Continue**. There's no need to fill in the other details. -3. Complete the project setup flow: - * Connect to your - * Add a repository — either choose a managed repository, or connect to an existing, but bare, repository. - - - -4. Click **Develop** in the top left. -5. If this is the first time you are setting up this project, then select **Initialize a project** to create your project. You will see a directory structure with `.sql` and `.yml` files generated by running the `init` command. - - - - -To create a new dbt project, run: - -```bash -$ dbt init [project_name] -``` - -This will create a new directory in your current path (i.e. at `./[project-name]`. - - - - - -### FAQs - - - - - -## Using an existing project - - - -If your organization already has a dbt Cloud account, and you wish to develop your project using dbt Cloud, ask an admin to add you as a Developer. - - -To work on an existing project: -1. Ensure that the project is checked into a hosted git repository (for example, on GitHub, GitLab or BitBucket) that you have access to. -2. Clone the repository to your computer. - - diff --git a/website/docs/docs/dbt-cloud/using-dbt-cloud/cloud-generating-documentation.md b/website/docs/docs/collaborate/cloud-build-and-view-your-docs.md similarity index 60% rename from website/docs/docs/dbt-cloud/using-dbt-cloud/cloud-generating-documentation.md rename to website/docs/docs/collaborate/cloud-build-and-view-your-docs.md index 31f3f95c430..c5fcb43f06d 100644 --- a/website/docs/docs/dbt-cloud/using-dbt-cloud/cloud-generating-documentation.md +++ b/website/docs/docs/collaborate/cloud-build-and-view-your-docs.md @@ -1,6 +1,6 @@ --- -title: "Generating documentation in dbt Cloud" -id: "cloud-generating-documentation" +title: "Build and view your docs with dbt Cloud" +id: "build-and-view-your-docs" description: "Automatically generate project documentation as you run jobs." --- @@ -26,17 +26,27 @@ You configure project documentation to generate documentation when the job you s 1. Click the gear icon in the top right. 2. Select **Projects** and click the project that needs documentation. -3. Click **Edit**. +3. Click **Edit**. 4. Under "Artifacts," select the job that should generate docs when it runs. 5. Click **Save**. -## Viewing documentation +## Generating documentation -Once you have a job set up to generate documentation for your project, then click **Documentation** in the top left. Your project's documentation should open. This link will always navigate you to the most recent version of your project's documentation in dbt Cloud. +To generate documentation in the IDE, run the `dbt docs generate` command in the +Command Bar in the IDE. This command will generate the Docs for your dbt project as it exists in development in your IDE session. - + + +After generating your documentation, you can click the "view docs" button to see the latest version of your documentation rendered in a new browser window. + + -## Easy access +## Viewing documentation + +Once you set up a job to generate documentation for your project, you can click **Documentation** in the top left. Your project's documentation should open. This link will always navigate you to the most recent version of your project's documentation in dbt Cloud. -See [Building and Configuring Artifacts](artifacts) for more information on exposing links to the latest Documentation and Source Freshness reports to your team. \ No newline at end of file +The dbt Cloud IDE makes it possible to view [documentation](/docs/collaborate/documentation) +for your dbt project while your code is still in development. With this workflow, you can inspect and verify what your project's generated documentation will look like before your changes are released to production. + + diff --git a/website/docs/docs/building-a-dbt-project/documentation.md b/website/docs/docs/collaborate/documentation.md similarity index 96% rename from website/docs/docs/building-a-dbt-project/documentation.md rename to website/docs/docs/collaborate/documentation.md index a3e99f5927f..dc9a3a6c848 100644 --- a/website/docs/docs/building-a-dbt-project/documentation.md +++ b/website/docs/docs/collaborate/documentation.md @@ -1,5 +1,5 @@ --- -title: "Documentation" +title: "About documentation" id: "documentation" --- @@ -8,10 +8,11 @@ id: "documentation" * [Declaring properties](configs-and-properties) * [`dbt docs` command](cmd-docs) * [`doc` Jinja function](/reference/dbt-jinja-functions) -* If you're new to dbt, we recommend that you check out our [Getting Started Tutorial](guides/getting-started/getting-set-up) to build your first dbt project, complete with documentation. +* If you're new to dbt, we recommend that you check out our [Getting Started Tutorial](/docs/get-started/getting-started/overview) to build your first dbt project, complete with documentation. ## Assumed knowledge -* [Tests](building-a-dbt-project/tests) + +* [Tests](/docs/build/tests) ## Overview @@ -28,7 +29,7 @@ Here's an example docs site: ## Adding descriptions to your project -To add descriptions to your project, use the `description:` key in the same files where you declare [tests](building-a-dbt-project/tests), like so: +To add descriptions to your project, use the `description:` key in the same files where you declare [tests](/docs/build/tests), like so: @@ -196,7 +197,7 @@ The `dbt docs serve` command is only intended for local/development hosting of t dbt's documentation website was built to make it easy to host on the web. The site is "static,” meaning you don't need any "dynamic" servers to serve the docs. You can host your documentation in several ways: -* Use [dbt Cloud](cloud-generating-documentation) +* Use [dbt Cloud](/docs/collaborate/documentation) * Host on [Amazon S3](https://docs.aws.amazon.com/AmazonS3/latest/dev/WebsiteHosting.html) (optionally [with IP access restrictions](https://docs.aws.amazon.com/AmazonS3/latest/dev/example-bucket-policies.html#example-bucket-policies-use-case-3)) * Publish with [Netlify](https://discourse.getdbt.com/t/publishing-dbt-docs-to-netlify/121) * Use your own web server like Apache/Nginx diff --git a/website/docs/docs/building-a-dbt-project/managing-environments.md b/website/docs/docs/collaborate/environments.md similarity index 96% rename from website/docs/docs/building-a-dbt-project/managing-environments.md rename to website/docs/docs/collaborate/environments.md index a62b584bd51..d072a188609 100644 --- a/website/docs/docs/building-a-dbt-project/managing-environments.md +++ b/website/docs/docs/collaborate/environments.md @@ -1,6 +1,6 @@ --- -title: "Managing environments" -id: "managing-environments" +title: "Environments" +id: "environments" --- ## What are environments? @@ -17,7 +17,7 @@ dbt makes it easy to maintain separate production and development environments t :::info Running dbt in production -You can learn more about different ways to run dbt in production in [this article](running-dbt-in-production) +You can learn more about different ways to run dbt in production in [this article](/docs/deploy/deployments). ::: diff --git a/website/docs/docs/collaborate/git-version-control.md b/website/docs/docs/collaborate/git-version-control.md new file mode 100644 index 00000000000..7006b8836f2 --- /dev/null +++ b/website/docs/docs/collaborate/git-version-control.md @@ -0,0 +1,24 @@ +--- +title: "About git" +id: git-version-control +description: "Git overview" +sidebar_label: "About git" +--- + +A [version control](https://en.wikipedia.org/wiki/Version_control) system allows you and your teammates to work collaboratively, safely, and simultaneously on a single project. Version control helps you track all the code changes made in your dbt project. + +In a distributed version control system, every developer has a full copy of the project and project history. Git is one of the most popular distributed version control systems and is commonly used for both open source and commercial software development, with great benefits for individuals, teams and businesses. + +![Git overview](https://docs.getdbt.com/img/docs/dbt-cloud/cloud-ide/git-overview.png) + + +Git allows developers see the entire timeline of their changes, decisions, and progression of any project in one place. From the moment they access the history of a project, the developer has all the context they need to understand it and start contributing. + +When you develop in the command line interface (CLI) or Cloud integrated development environment (IDE), you can leverage Git directly to version control your code. To use version control, make sure you are connected to a Git repository in the CLI or Cloud IDE. + + +## Related docs +- [Version control basics](/docs/collaborate/git/version-control-basics) +- [Resolve merge conflicts](/docs/collaborate/git/resolve-merge-conflicts) +- [Connect to GitHub](/docs/collaborate/git/connect-github) +- [Connect to GitLab](/docs/collaborate/git/connect-gitlab) diff --git a/website/docs/docs/dbt-cloud/cloud-configuring-dbt-cloud/authenticate-azure.md b/website/docs/docs/collaborate/git/authenticate-azure.md similarity index 100% rename from website/docs/docs/dbt-cloud/cloud-configuring-dbt-cloud/authenticate-azure.md rename to website/docs/docs/collaborate/git/authenticate-azure.md diff --git a/website/docs/docs/dbt-cloud/cloud-configuring-dbt-cloud/connecting-azure-devops.md b/website/docs/docs/collaborate/git/connect-azure-devops.md similarity index 71% rename from website/docs/docs/dbt-cloud/cloud-configuring-dbt-cloud/connecting-azure-devops.md rename to website/docs/docs/collaborate/git/connect-azure-devops.md index 157260215fa..0997c4b0228 100644 --- a/website/docs/docs/dbt-cloud/cloud-configuring-dbt-cloud/connecting-azure-devops.md +++ b/website/docs/docs/collaborate/git/connect-azure-devops.md @@ -1,7 +1,6 @@ --- -title: "Connecting your Azure DevOps Account" -id: "connecting-azure-devops" -sidebar_label: "Connecting Azure DevOps" +title: "Connect to Azure DevOps" +id: "connect-azure-devops" --- @@ -19,7 +18,5 @@ You can connect your Azure DevOps account in dbt Cloud to unlock new product exp To connect Azure DevOps in dbt Cloud: -1. An account admin needs to [set up an Active Directory application and add it to dbt Cloud](docs/dbt-cloud/cloud-configuring-dbt-cloud/setup-azure). -2. dbt Cloud developers need to [personally authenticate with Azure DevOps](docs/dbt-cloud/cloud-configuring-dbt-cloud/authenticate-azure) from dbt Cloud. - - +1. An account admin needs to [set up an Active Directory application and add it to dbt Cloud](/docs/collaborate/git/setup-azure). +2. dbt Cloud developers need to [personally authenticate with Azure DevOps](/docs/collaborate/git/authenticate-azure) from dbt Cloud. diff --git a/website/docs/docs/dbt-cloud/cloud-configuring-dbt-cloud/cloud-installing-the-github-application.md b/website/docs/docs/collaborate/git/connect-github.md similarity index 86% rename from website/docs/docs/dbt-cloud/cloud-configuring-dbt-cloud/cloud-installing-the-github-application.md rename to website/docs/docs/collaborate/git/connect-github.md index 59e3d813a5d..4db02b82a0f 100644 --- a/website/docs/docs/dbt-cloud/cloud-configuring-dbt-cloud/cloud-installing-the-github-application.md +++ b/website/docs/docs/collaborate/git/connect-github.md @@ -1,7 +1,6 @@ --- -title: "Connecting your GitHub account" -id: "cloud-installing-the-github-application" -sidebar_label: "Connecting GitHub" +title: "Connect to GitHub" +id: "connect-github" --- ## Overview @@ -20,15 +19,15 @@ To connect GitHub in dbt Cloud: If you are the GitHub organization owner tasked with the installation of the dbt Cloud app in step 1, you will also be automatically personally authenticated after completion, so step 2 will be taken care of. This means teams of one only need to complete step 1. :::info Use GitHub On-Premise? -If you're using an On-Premise GitHub deployment, this method will not work for your account. Please instead reference our -docs on [importing a project by git URL](docs/dbt-cloud/cloud-configuring-dbt-cloud/cloud-import-a-project-by-git-url#github) to set up your connection. This alternative connection method does not include the benefits of the native integration mentioned above. +If you're using an On-Premises GitHub deployment, this method will not work for your account. Please instead reference our +docs on [importing a project by git URL](/docs/dbt-cloud/cloud-configuring-dbt-cloud/cloud-import-a-project-by-git-url#github) to set up your connection. This alternative connection method does not include the benefits of the native integration mentioned above. ::: ## Installing dbt Cloud in your GitHub account A GitHub organization owner needs to connect and configure the dbt Cloud app for their GitHub organization. If you are a team of one or wish to connect your personal GitHub account, then these instructions also apply to you. -To link your dbt Cloud account to your team's GitHub account, navigate to Your Profile settings by clicking the gear icon in the top right. Select **Linked Accounts** in the left menu. +To link your dbt Cloud account to your team's GitHub account, navigate to Your Profile settings by clicking the gear icon in the top right. Select **Linked Accounts** from the left menu. @@ -43,11 +42,11 @@ The dbt Cloud GitHub App requires the following permissions: Once you grant access to the app, you will be redirected back to dbt Cloud and shown a linked account success state. You are now personally authenticated too, and your team members can begin [connecting their profiles](/cloud-installing-the-github-application#personally-authenticate-with-github). ## Configuring the dbt Cloud app in your GitHub account -If you are your GitHub organization owner, you can also configure the dbt Cloud GitHub application to have access to only select repositories. This configuration must be done in GitHub, but we provide an easy link in dbt Cloud to start this process. +If you are your GitHub organization owner, you can also configure the dbt Cloud GitHub application to have access to only select repositories. This configuration must be done in GitHub, but we provide an easy link in dbt Cloud to start this process. ## Personally authenticate with GitHub -dbt Cloud developers on the Enterprise plan must each connect their GitHub profiles to dbt Cloud, as every developer's read / write access for the dbt repo is checked in the dbt Cloud IDE. dbt Cloud developers on the Team plan do not need to each connect their profiles to GitHub, but it is still recommended to do so. +dbt Cloud developers on the Enterprise plan must each connect their GitHub profiles to dbt Cloud, as every developer's read / write access for the dbt repo is checked in the dbt Cloud IDE. dbt Cloud developers on the Team plan do not need to each connect their profiles to GitHub, but it is still recommended to do so. To connect a personal GitHub account, dbt Cloud developers should navigate to Your Profile settings by clicking the gear icon in the top right, then select **Linked Accounts** in the left menu. diff --git a/website/docs/docs/dbt-cloud/cloud-configuring-dbt-cloud/connecting-gitlab.md b/website/docs/docs/collaborate/git/connect-gitlab.md similarity index 83% rename from website/docs/docs/dbt-cloud/cloud-configuring-dbt-cloud/connecting-gitlab.md rename to website/docs/docs/collaborate/git/connect-gitlab.md index 6fe1244d25c..8eb1a863dc1 100644 --- a/website/docs/docs/dbt-cloud/cloud-configuring-dbt-cloud/connecting-gitlab.md +++ b/website/docs/docs/collaborate/git/connect-gitlab.md @@ -1,7 +1,6 @@ --- -title: "Connecting your GitLab Account" -id: "connecting-gitlab" -sidebar_label: "Connecting GitLab" +title: "Connect to GitLab" +id: "connect-gitlab" --- ## Overview @@ -13,19 +12,19 @@ Connecting your GitLab account to dbt Cloud provides convenience and another lay - Trigger [Continuous integration](cloud-enabling-continuous-integration-with-github) builds when merge requests are opened in GitLab. The steps to integrate GitLab in dbt Cloud depend on your plan. If you are on: -- the Developer or Team plan, read these [instructions](/connecting-gitlab#for-dbt-cloud-developer-and-team-tiers). -- the Enterprise plan, jump ahead to these [instructions](/connecting-gitlab#for-the-dbt-cloud-enterprise-tier). +- the Developer or Team plan, read these [instructions](#for-dbt-cloud-developer-and-team-tiers). +- the Enterprise plan, jump ahead to these [instructions](#for-the-dbt-cloud-enterprise-tier). ## For dbt Cloud Developer and Team tiers -To connect your GitLab account: -1. Navigate to Your Profile settings by clicking the gear icon in the top right. -2. Select **Linked Accounts** in the left menu. +To connect your GitLab account: +1. Navigate to Your Profile settings by clicking the gear icon in the top right. +2. Select **Linked Accounts** in the left menu. 3. Click **Link** to the right of your GitLab account. -When you click **Link**, you will be redirected to GitLab and prompted to sign into your account. GitLab will then ask for your explicit authorization: +When you click **Link**, you will be redirected to GitLab and prompted to sign into your account. GitLab will then ask for your explicit authorization: @@ -39,11 +38,11 @@ dbt Cloud enterprise customers have the added benefit of bringing their own GitL - Carry GitLab's user repository permissions (read / write access) through to dbt Cloud IDE's git actions. In order to connect GitLab in dbt Cloud, a GitLab account admin must: -1. [Set up a GitLab OAuth application](/cloud-configuring-dbt-cloud/connecting-gitlab#setting-up-a-gitlab-oauth-application). -2. [Add the GitLab app to dbt Cloud](/connecting-gitlab#adding-the-gitlab-oauth-application-to-dbt-cloud). +1. [Set up a GitLab OAuth application](#setting-up-a-gitlab-oauth-application). +2. [Add the GitLab app to dbt Cloud](#adding-the-gitlab-oauth-application-to-dbt-cloud). Once the admin completes those steps, dbt Cloud developers need to: -1. [Personally authenticate with GitLab](cloud-configuring-dbt-cloud/connecting-gitlab#personally-authenticating-with-gitlab) from dbt Cloud. +1. [Personally authenticate with GitLab](#personally-authenticating-with-gitlab) from dbt Cloud. ### Setting up a GitLab OAuth application @@ -71,10 +70,10 @@ The application form in GitLab should look as follows when completed: -Click **Save application** in GitLab, and GitLab will then generate an **Application ID** and **Secret**. These values will be available even if you close the app screen, so this is not the only chance you have to save them. +Click **Save application** in GitLab, and GitLab will then generate an **Application ID** and **Secret**. These values will be available even if you close the app screen, so this is not the only chance you have to save them. ### Adding the GitLab OAuth application to dbt Cloud -After you've created your GitLab application, you need to provide dbt Cloud information about the app. In dbt Cloud, account admins should navigate to **Account Settings**, click on the **Integrations** tab, and expand the GitLab section. +After you've created your GitLab application, you need to provide dbt Cloud information about the app. In dbt Cloud, account admins should navigate to **Account Settings**, click on the **Integrations** tab, and expand the GitLab section. @@ -86,15 +85,15 @@ In dbt Cloud, input the following values: | **Application ID** | *copy value from GitLab app* | | **Secret** | *copy value from GitLab app* | -Note, if you have a special hosted version of GitLab, modify the **GitLab Instance** to use the hostname provided for your organization instead - for example https://gitlab.yourgreatcompany.com/. +Note, if you have a special hosted version of GitLab, modify the **GitLab Instance** to use the hostname provided for your organization instead - for example `https://gitlab.yourgreatcompany.com/`. Once the form is complete in dbt Cloud, click **Save**. -You will then be redirected to GitLab and prompted to sign into your account. GitLab will ask for your explicit authorization: +You will then be redirected to GitLab and prompted to sign into your account. GitLab will ask for your explicit authorization: -Once you've accepted, you should be redirected back to dbt Cloud, and your integration is ready for developers on your team to [personally authenticate with](/connecting-gitlab#personally-authenticating-with-gitlab). +Once you've accepted, you should be redirected back to dbt Cloud, and your integration is ready for developers on your team to [personally authenticate with](#personally-authenticating-with-gitlab). ### Personally authenticating with GitLab dbt Cloud developers on the Enterprise plan must each connect their GitLab profiles to dbt Cloud, as every developer's read / write access for the dbt repo is checked in the dbt Cloud IDE. @@ -117,4 +116,4 @@ If you do not see your repository listed, double-check that: If you do see your repository listed, but are unable to import the repository successfully, double-check that: - You are a maintainer of that repository. Only users with maintainer permissions can set up repository connections. -If you imported a repository using the dbt Cloud native integration with GitLab, you should be able to see the clone strategy is using a `deploy_token`. If it's relying on an SSH key, this means the repository was not set up using the native GitLab integration, but rather using the generic git clone option. The repository must be reconnected in order to get the benefits described above. \ No newline at end of file +If you imported a repository using the dbt Cloud native integration with GitLab, you should be able to see the clone strategy is using a `deploy_token`. If it's relying on an SSH key, this means the repository was not set up using the native GitLab integration, but rather using the generic git clone option. The repository must be reconnected in order to get the benefits described above. diff --git a/website/docs/docs/dbt-cloud/cloud-configuring-dbt-cloud/cloud-import-a-project-by-git-url.md b/website/docs/docs/collaborate/git/import-a-project-by-git-url.md similarity index 91% rename from website/docs/docs/dbt-cloud/cloud-configuring-dbt-cloud/cloud-import-a-project-by-git-url.md rename to website/docs/docs/collaborate/git/import-a-project-by-git-url.md index 3f5c387217e..5d09e336ccd 100644 --- a/website/docs/docs/dbt-cloud/cloud-configuring-dbt-cloud/cloud-import-a-project-by-git-url.md +++ b/website/docs/docs/collaborate/git/import-a-project-by-git-url.md @@ -1,6 +1,6 @@ --- -title: "Importing a project by git URL" -id: "cloud-import-a-project-by-git-url" +title: "Import a project by git URL" +id: "import-a-project-by-git-url" --- In dbt Cloud, you can import a git repository from any valid git URL that points to a dbt project. There are a couple of important considerations to keep in mind when doing this: @@ -17,7 +17,7 @@ After importing a project by Git URL, dbt Cloud will generate a Deploy Key for y :::info Use GitHub? -If you use GitHub, you can import your repo directly using [dbt Cloud's GitHub Application](cloud-installing-the-github-application). Connecting your repo via the GitHub Application [enables Continuous Integration](cloud-enabling-continuous-integration-with-github). +If you use GitHub, you can import your repo directly using [dbt Cloud's GitHub Application](/docs/collaborate/git/connect-github). Connecting your repo via the GitHub Application [enables Continuous Integration](/docs/deploy/cloud-ci-job). ::: @@ -31,7 +31,7 @@ See also: [Adding a deploy key in GitHub](https://github.blog/2015-06-16-read-o :::info Use GitLab? -If you use GitLab, you can import your repo directly using [dbt Cloud's GitLab Application](connecting-gitlab). Connecting your repo via the GitLab Application [enables Continuous Integration](cloud-enabling-continuous-integration-with-github). +If you use GitLab, you can import your repo directly using [dbt Cloud's GitLab Application](/docs/collaborate/git/connect-gitlab). Connecting your repo via the GitLab Application [enables Continuous Integration](/docs/deploy/cloud-ci-job). ::: @@ -76,7 +76,7 @@ You're all set! Once support handles your request, your project is set up and yo ### Azure DevOps :::info Use Azure DevOps? -If you use Azure DevOps and you are on the dbt Cloud Enterprise plan, you can import your repo directly using [dbt Cloud's Azure DevOps Integration](connecting-azure-devops). Connecting your repo via the Azure DevOps Application [enables Continuous Integration](cloud-enabling-continuous-integration-with-github). +If you use Azure DevOps and you are on the dbt Cloud Enterprise plan, you can import your repo directly using [dbt Cloud's Azure DevOps Integration](/docs/collaborate/git/connect-azure-devops). Connecting your repo via the Azure DevOps Application [enables Continuous Integration](/docs/deploy/cloud-ci-job). ::: diff --git a/website/docs/docs/dbt-cloud/cloud-configuring-dbt-cloud/cloud-using-a-managed-repository.md b/website/docs/docs/collaborate/git/managed-repository.md similarity index 87% rename from website/docs/docs/dbt-cloud/cloud-configuring-dbt-cloud/cloud-using-a-managed-repository.md rename to website/docs/docs/collaborate/git/managed-repository.md index e5b347e0f05..d7beb38c4f5 100644 --- a/website/docs/docs/dbt-cloud/cloud-configuring-dbt-cloud/cloud-using-a-managed-repository.md +++ b/website/docs/docs/collaborate/git/managed-repository.md @@ -1,17 +1,17 @@ --- -title: "Using a dbt Cloud managed repository" -id: "cloud-using-a-managed-repository" +title: "Managed repository" +id: "managed-repository" --- -If you do not already have a git repository for your dbt project, you can let dbt Cloud manage a repository for you. Managed repositories are a great way to trial dbt without needing to create a new repository. +If you do not already have a git repository for your dbt project, you can let dbt Cloud manage a repository for you. Managed repositories are a great way to trial dbt without needing to create a new repository. -To set up a project with a managed repository: +To set up a project with a managed repository: 1. From your Account settings in dbt Cloud, select the project you want to set up with a managed repository. If the project already has a repository set up, you need to edit the repository settings and disconnect the existing repository. 2. Click **Edit** for the project. 3. Under Repository, click **Configure repository**. 4. Select **Managed**. -5. Enter a name for the repository. For example, "analytics" or "dbt-models." +5. Enter a name for the repository. For example, "analytics" or "dbt-models." 6. Click **Create**. diff --git a/website/docs/docs/dbt-cloud/cloud-configuring-dbt-cloud/cloud-configuring-repositories.md b/website/docs/docs/collaborate/git/pr-template.md similarity index 94% rename from website/docs/docs/dbt-cloud/cloud-configuring-dbt-cloud/cloud-configuring-repositories.md rename to website/docs/docs/collaborate/git/pr-template.md index 604528be825..5480f5528e3 100644 --- a/website/docs/docs/dbt-cloud/cloud-configuring-dbt-cloud/cloud-configuring-repositories.md +++ b/website/docs/docs/collaborate/git/pr-template.md @@ -1,6 +1,6 @@ --- -title: "Configuring repositories" -id: "cloud-configuring-repositories" +title: "PR template" +id: "pr-template" --- ## Configure pull request (PR) template URLs @@ -46,7 +46,7 @@ https://github.com/dbt-labs/jaffle_shop/compare/master..my-branch ## Configure custom branches -By default in Development Environments, dbt Cloud attempts to reference the `main` branch in connected repositories. If you want to use a different default branch name, you can configure dbt Cloud with a custom branch setting. +By default in Development Environments, dbt Cloud attempts to reference the `main` branch in connected repositories. If you want to use a different default branch name, you can configure dbt Cloud with a custom branch setting. For example, you can use the `develop` branch of a connected repository. Edit an environment, then in "General settings" select **Only run on a custom branch** , and in "Custom branch" type **develop** or the name of your custom branch. @@ -55,7 +55,7 @@ For example, you can use the `develop` branch of a connected repository. Edit an ## Example templates Some common URL templates are provided below, but please note that the exact -value may vary depending on your configured git provider. +value may vary depending on your configured git provider. ### GitHub ``` diff --git a/website/docs/docs/dbt-cloud/cloud-ide/handling-merge-conflicts.md b/website/docs/docs/collaborate/git/resolve-merge-conflicts.md similarity index 97% rename from website/docs/docs/dbt-cloud/cloud-ide/handling-merge-conflicts.md rename to website/docs/docs/collaborate/git/resolve-merge-conflicts.md index c9f48a0f13d..1058046856c 100644 --- a/website/docs/docs/dbt-cloud/cloud-ide/handling-merge-conflicts.md +++ b/website/docs/docs/collaborate/git/resolve-merge-conflicts.md @@ -1,15 +1,15 @@ --- -title: "Handling Merge Conflicts" -id: "handling-merge-conflicts" +title: "Resolve merge conflicts" +id: "resolve-merge-conflicts" --- Merge conflicts often occur when multiple users are concurrently making edits to the same section in the same file. This makes it difficult for Git to determine which change should be kept. The merge conflict process gives users the ability to sort out which lines of code should be kept and committed. Here we'll show you how you'd resolve merge conflicts in the IDE! ## Running into a merge conflict -In this example we have a column that represents the total number of orders your customer has ever had. It's currently named `number_of_orders` but your stakeholder feels like this could be named better. +In this example we have a column that represents the total number of orders your customer has ever had. It's currently named `number_of_orders` but your stakeholder feels like this could be named better. -You and a teammate make changes to the column name, but have gone two separate routes. You rename this column to `total_number_of_orders` and your teammate has renamed it `historical_order_count`. +You and a teammate make changes to the column name, but have gone two separate routes. You rename this column to `total_number_of_orders` and your teammate has renamed it `historical_order_count`. Your teammate has committed their change first, so you encounter a merge conflict when you press commit. diff --git a/website/docs/docs/dbt-cloud/cloud-configuring-dbt-cloud/setup-azure.md b/website/docs/docs/collaborate/git/setup-azure.md similarity index 93% rename from website/docs/docs/dbt-cloud/cloud-configuring-dbt-cloud/setup-azure.md rename to website/docs/docs/collaborate/git/setup-azure.md index 0bc06fb4b43..084e0291ec2 100644 --- a/website/docs/docs/dbt-cloud/cloud-configuring-dbt-cloud/setup-azure.md +++ b/website/docs/docs/collaborate/git/setup-azure.md @@ -9,7 +9,7 @@ sidebar_label: "Set up Azure DevOps" ## Overview -To use our native integration with Azure DevOps in dbt Cloud, an account admin needs to set up an Azure Active Directory (Azure AD) app. We recommend setting up a separate [Azure AD application than used for SSO](/setting-up-enterprise-sso-with-azure-active-directory). +To use our native integration with Azure DevOps in dbt Cloud, an account admin needs to set up an Azure Active Directory (Azure AD) app. We recommend setting up a separate [Azure AD application than used for SSO](/docs/collaborate/manage-access/set-up-sso-azure-active-directory). 1. [Register an Azure AD app](#register-an-azure-ad-app). 2. [Add permissions to your new app](#add-permissions-to-your-new-app). @@ -21,7 +21,7 @@ Once the the Azure AD app is added to dbt Cloud, an account admin must also conn 1. [Connecting a Service User](#connecting-a-service-user). -Once the Azure AD app is added to dbt Cloud and the service user is connected, then dbt Cloud developers can personally authenticate in dbt Cloud from Azure DevOps. For more on this, see [Authenticate with Azure DevOps](docs/dbt-cloud/cloud-configuring-dbt-cloud/authenticate-azure). +Once the Azure AD app is added to dbt Cloud and the service user is connected, then dbt Cloud developers can personally authenticate in dbt Cloud from Azure DevOps. For more on this, see [Authenticate with Azure DevOps](/docs/collaborate/git/authenticate-azure). ## Register an Azure AD app @@ -29,7 +29,7 @@ Once the Azure AD app is added to dbt Cloud and the service user is connected, t 2. Select **App registrations** in the left panel. 3. Select **New registration**. The form for creating a new Active Directory app opens. 4. Provide a name for your app. We recommend using, "dbt Labs Azure DevOps App". -5. Select **Accounts in any organizational directory (Any Azure AD directory - Multitenant)** as the Supported Account Types. +5. Select **Accounts in any organizational directory (Any Azure AD directory - Multitenant)** as the Supported Account Types. Many customers ask why they need to select Multitenant instead of Single tenant, and they frequently get this step wrong. Microsoft considers Azure DevOps (formerly called Visual Studio) and Azure Active Directory as separate tenants, and in order for this Active Directory application to work properly, you must select Multitenant. 6. Add a redirect URI by selecting **Web** and typing in `https://cloud.getdbt.com/complete/azure_active_directory`. If you have a custom dbt Cloud URL be sure to use the appropriate domain. 7. Click **Register**. @@ -53,7 +53,7 @@ Provide your new app access to Azure DevOps: -## Add another redirect URI +## Add another redirect URI You also need to add another redirect URI to your Azure AD application. This redirect URI will be used to authenticate the service user for headless actions in deployment environments. @@ -89,11 +89,11 @@ Once you connect your Azure AD app and Azure DevOps, you need to provide dbt Clo 4. Complete the form: - **Azure DevOps Organization:** Must match the name of your Azure DevOps organization exactly. - **Application (client) ID:** Found in the Azure AD App. - - **Client Secrets:** You need to first create a secret in the Azure AD App under **Client credentials**. Make sure to copy the **Value** field in the Azure AD App and paste it in the **Client Secret** field in dbt Cloud. You are responsible for the Azure AD app secret expiration and rotation. + - **Client Secrets:** You need to first create a secret in the Azure AD App under **Client credentials**. Make sure to copy the **Value** field in the Azure AD App and paste it in the **Client Secret** field in dbt Cloud. You are responsible for the Azure AD app secret expiration and rotation. - **Directory(tenant) ID:** Found in the Azure AD App. -Your Azure AD app should now be added to your dbt Cloud Account. People on your team who want to develop in dbt Cloud's IDE can now personally [authorize Azure DevOps from their profiles](dbt-cloud/cloud-configuring-dbt-cloud/authenticate-azure). +Your Azure AD app should now be added to your dbt Cloud Account. People on your team who want to develop in dbt Cloud's IDE can now personally [authorize Azure DevOps from their profiles](/docs/collaborate/git/authenticate-azure). ## Connecting a service user @@ -101,12 +101,12 @@ Because Azure DevOps forces all authentication to be linked to a user's permissi ### More on Service Users -A service user account must have the following Azure DevOps permissions for all Azure DevOps projects and repos you want accessible in dbt Cloud. Read more about how dbt Cloud uses each permission in the following paragraphs. +A service user account must have the following Azure DevOps permissions for all Azure DevOps projects and repos you want accessible in dbt Cloud. Read more about how dbt Cloud uses each permission in the following paragraphs. - **Project Reader** - **ViewSubscriptions** - **EditSubscriptions** - - **DeleteSubscriptions** * + - **DeleteSubscriptions** * - **PullRequestContribute** - **GenericContribute** @@ -127,17 +127,17 @@ This service user's permissions will also power which repositories a team can se **Namespace:** ServiceHooks **Permission:** -```json -{ - "bit": 1, - "displayName": "View Subscriptions", +```json +{ + "bit": 1, + "displayName": "View Subscriptions", "name": "ViewSubscriptions" -} +} ``` **Uses:** To view existing Azure DevOps service hooks subscriptions -**Token (where applicable - API only):** +**Token (where applicable - API only):** - PublisherSecurity for access to all projects - PublisherSecurity/ for per project access @@ -154,7 +154,7 @@ This service user's permissions will also power which repositories a team can se **Namespace:** ServiceHooks **Permission:** -```json +```json { "bit": 2, "displayName": "Edit Subscription", @@ -165,7 +165,7 @@ This service user's permissions will also power which repositories a team can se **Uses:** To add or update existing Azure DevOps service hooks subscriptions -**Token (where applicable - API only):** +**Token (where applicable - API only):** - PublisherSecurity for access to all projects - PublisherSecurity/ for per project access @@ -182,7 +182,7 @@ This service user's permissions will also power which repositories a team can se **Namespace:** ServiceHooks **Permission:** -```json +```json { "bit": 4, "displayName": "Delete Subscriptions", @@ -195,7 +195,7 @@ This service user's permissions will also power which repositories a team can se **Uses:** To delete any redundant Azure DevOps service hooks subscriptions -**Token (where applicable - API only):** +**Token (where applicable - API only):** - PublisherSecurity for access to all projects - PublisherSecurity/ for per project access @@ -215,7 +215,7 @@ This service user's permissions will also power which repositories a team can se **Namespace:** Git Repositories **Permission:** -```json +```json { "bit": 16384, "displayName": "Contribute to pull requests", @@ -227,7 +227,7 @@ This service user's permissions will also power which repositories a team can se **Uses:** To post Pull Request statuses to Azure DevOps -**Token (where applicable - API only):** +**Token (where applicable - API only):** - repoV2 for access to all projects - repoV2/ for per project access - repoV2// for per repo access @@ -249,7 +249,7 @@ This service user's permissions will also power which repositories a team can se **Namespace:** Git Repositories **Permission:** -```json +```json { "bit": 4, "displayName": "Contribute", @@ -262,7 +262,7 @@ This service user's permissions will also power which repositories a team can se **Uses:** To post commit statuses to Azure DevOps -**Token (where applicable - API only):** +**Token (where applicable - API only):** - repoV2 for access to all projects - repoV2/ for access to a single project at a time - repoV2// for access to a single repo at a time diff --git a/website/docs/docs/collaborate/git/version-control-basics.md b/website/docs/docs/collaborate/git/version-control-basics.md new file mode 100644 index 00000000000..6276fb61c16 --- /dev/null +++ b/website/docs/docs/collaborate/git/version-control-basics.md @@ -0,0 +1,62 @@ +--- +title: "Version control basics" +id: version-control-basics +description: "Leverage Git to version control your code." +sidebar_label: "Version control basics" +--- + +# Version control basics + +When you develop in the command line interface (CLI) or Cloud integrated development environment (IDE), you can leverage Git directly to version control your code. To use version control, make sure you are connected to a Git repository in the CLI or Cloud IDE. + +You can create a separate branch to develop and make changes. The changes you make aren’t merged into the main branch unless it successfully passes tests. This helps keep the code organized and improves productivity by making the development process smooth. + +You can read more about git terminology below and also check out [GitHub Docs](https://docs.github.com/en) as well. + +## Git overview + +Check out some common git terms below that you might encounter when developing: + +| Name | Definition | +| --- | --- | +| Repository or repo | A repository is a directory that stores all the files, folders, and content needed for your project. You can think of this as an object database of the project, storing everything from the files themselves to the versions of those files, commits, and deletions. Repositories are not limited by user and can be shared and copied. | +| Branch | A branch is a parallel version of a repository. It is contained within the repository but does not affect the primary or main branch allowing you to work freely without disrupting the live version. When you've made the changes you want to make, you can merge your branch back into the main branch to publish your changes | +| Checkout | The `checkout` command is used to create a new branch, change your current working branch to a different branch, or switch to a different version of a file from a different branch. | +| Commit | A commit is a user’s change to a file (or set of files). When you make a commit to save your work, Git creates a unique ID that allows you to keep a record of the specific changes committed along with who made them and when. Commits usually contain a commit message which is a brief description of what changes were made. | +| main | The primary, base branch of all repositories. All committed and accepted changes should be on the main branch. In the Cloud IDE, the main branch is read-only. This is because any changes/edits to code cannot and should not be made directly in the base branch. A new branch should be created in order to make any changes to your project | +| Merge | Merge takes the changes from one branch and adds them into another (usually main) branch. These commits are usually first requested via pull request before being merged by a maintainer. | +| Pull Request | If someone has changed code on a separate branch of a project and wants it to be reviewed to add to the main branch, they can submit a pull request. Pull requests ask the repo maintainers to review the commits made, and then, if acceptable, merge the changes upstream. A pull happens when adding the changes to the main branch. | +| Push | A `push` updates a remote branch with the commits made to the current branch. You are literally _pushing_ your changes into the remote. | +| Remote | This is the version of a repository or branch that is hosted on a server. Remote versions can be connected to local clones so that changes can be synced. | + + +## The git button in the Cloud IDE + +You can perform git tasks with the git button in the Cloud IDE. The following are descriptions of each git button command and what they do: + + +| Name | Actions | +| --- | --- | +| Abort merge | This option allows you to cancel a merge that had conflicts. Be careful with this action because all changes will be reset and this operation can't be reverted, so make sure to commit or save all your changes before you start a merge. | +| Change branch | This option allows you to change between branches (checkout). | +| Commit | A commit is an individual change to a file (or set of files). When you make a commit to save your work, Git creates a unique ID (a.k.a. the "SHA" or "hash") that allows you to keep record of the specific changes committed along with who made them and when. Commits usually contain a commit message which is a brief description of what changes were made. When you make changes to your code in the future, you'll need to commit them as well. | +| Create new branch | This allows you to branch off of your base branch and edit your project. You’ll notice after initializing your project that the main branch will be read-only. This is because any changes to code cannot and should not be made directly in the base branch. A new branch should be created in order to make any changes to your project. | +| Initialize your project | This is done when first setting up your project. Initializing a project creates all required directories and files within an empty repository by using the dbt starter project.

Note: This option will not display if your repo isn't completely empty (i.e. includes a README file).

Once you click **Initialize your project**, click **Commit** to finish setting up your project. | +| Open pull request | This allows you to open a pull request in Git for peers to review changes before merging into the base branch. | +| Pull changes from master/main | This option is available if you are on any local branch that is behind the remote version of the base branch or the remote version of the branch that you're currently on. | +| Pull from remote | This option is available if you’re on the local base branch and changes have recently been pushed to the remote version of the branch. Pulling in changes from the remote repo allows you to pull in the most recent version of the base branch. | +| Reclone Your Repository | Reclone your repository directly from the Cloud IDE. You can reset your repository back to a fresh clone from your remote. To do this, click on the bottom right-hand side green **Ready** text, then click **Reclone Repo**. | +| Refresh git state | This enables you to pull new branches from a different remote branch to your local branch with just one command. | + + +## Merge conflicts + +Merge conflicts often occur when multiple users are concurrently making edits to the same section in the same file. This makes it difficult for Git to determine which change should be kept. + +Refer to [resolve merge conflicts](/docs/collaborate/git/resolve-merge-conflicts) to learn how to resolve merge conflicts. + +## The .gitignore file + +dbt Labs recommends that you exclude files so they're not tracked by Git and won't slow down your dbt project. + +You can do this with a special file named [.gitignore](https://github.com/dbt-labs/dbt-starter-project/blob/main/.gitignore) which is automatically included in your dbt project after you initialize it in dbt Cloud. The `.gitignore` file must be placed at the root of your dbt project. diff --git a/website/docs/docs/collaborate/manage-access/about-access.md b/website/docs/docs/collaborate/manage-access/about-access.md new file mode 100644 index 00000000000..844f49e6500 --- /dev/null +++ b/website/docs/docs/collaborate/manage-access/about-access.md @@ -0,0 +1,150 @@ +--- +title: "About access" +id: "about-access" +--- + +## Overview + +dbt Cloud administrators can use dbt Cloud's permissioning model to control +user-level access in a dbt Cloud account. This access control comes in two flavors: +License-based and Role-based. + +- **License-based Access Controls:** User are configured with account-wide + license types. These licenses control the specific parts of the dbt Cloud application + that a given user can access. +- **Role-based Access Control (RBAC):** Users are assigned to _groups_ that have + specific permissions on specific projects or the entire account. A user may be + a member of multiple groups, and those groups may have permissions on multiple + projects. + +## License-based access control + +Each user on an account is assigned a license type when the user is first +invited to a given account. This license type may change over time, but a +user can only have one type of license at any given time. + +A user's license type controls the features in dbt Cloud that the user is able +to access. dbt Cloud's two license types are: + - **Read Only** + - **Developer** + +For more information on these license types, see [Seats & Users](cloud-seats-and-users). +At a high level, Developers may be granted _any_ permissions, whereas Read Only +users will have read-only permissions applied to all dbt Cloud resources +regardless of the role-based permissions that the user is assigned. + +## Role-based access control + +:::info dbt Cloud Enterprise + +Role-based access control is a feature of the dbt Cloud Enterprise plan + +::: + +Role-based access control allows for fine-grained permissioning in the dbt Cloud +application. With role-based access control, users can be assigned varying +permissions to different projects within a dbt Cloud account. For teams on the +Enterprise tier, role-based permissions can be generated dynamically from +configurations in an [Identity Provider](sso-overview). + +Role-based permissions are applied to _groups_ and pertain to _projects_. The +assignable permissions themselves are granted via _permission sets_. + + +### Groups + +A group is a collection of users. Users may belong to multiple groups. Members +of a group inherit any permissions applied to the group itself. + +Users can be added to a dbt Cloud group based on their group memberships in the +configured [Identity Provider](sso-overview) for the account. In this way, dbt +Cloud administrators can manage access to dbt Cloud resources via identity +management software like Azure AD, Okta, or GSuite. See _SSO Mappings_ below for +more information. + +You can view the groups in your account or create new groups from the **Team > Groups** +page in your Account Settings. + + + + +### SSO Mappings + +SSO Mappings connect Identity Provider (IdP) group membership to dbt Cloud group +membership. When a user logs into dbt Cloud via a supported identity provider, +their IdP group memberships are synced with dbt Cloud. Upon logging in +successfully, the user's group memberships (and therefore, permissions) are +adjusted accordingly within dbt Cloud automatically. + +:::tip Creating SSO Mappings + +While dbt Cloud supports mapping multiple IdP groups to a single dbt Cloud +group, we recommend using a 1:1 mapping to make administration as simple as +possible. Consider using the same name for your dbt Cloud groups and your IdP +groups. + +::: + + +### Permission Sets + +Permission sets are predefined collections of granular permissions. Permission +sets combine low-level permission grants into high-level roles that can be +assigned to groups. Some examples of existing permission sets are: + - Account Admin + - Git Admin + - Job Admin + - Job Viewer + - ...and more + +For a full list of enterprise permission sets, see [Enterprise Permissions](/docs/collaborate/manage-access/enterprise-permissions). +These permission sets are available for assignment to groups and control the ability +for users in these groups to take specific actions in the dbt Cloud application. + +In the following example, the _dbt Cloud Owners_ group is configured with the +**Account Admin** permission set on _All Projects_ and the **Job Admin** permission +set on the _Internal Analytics_ project. + + + + +### Manual assignment + + + +- New in version 1.1.23 (March, 2021) + + + +dbt Cloud administrators can manually assign users to groups independently of +IdP attributes. If a dbt Cloud group is configured _without_ any +SSO Mappings, then the group will be _unmanaged_ and dbt Cloud will not adjust +group membership automatically when users log into dbt Cloud via an identity +provider. This behavior may be desirable for teams that have connected an identity +provider, but have not yet configured SSO Mappings between dbt Cloud and the +IdP. + +If an SSO Mapping is added to an _unmanaged_ group, then it will become +_managed_, and dbt Cloud may add or remove users to the group automatically at +sign-in time based on the user's IdP-provided group membership information. + + +## FAQs +- **When are IdP group memberships updated for SSO Mapped groups?** Group memberships + are updated every time a user logs into dbt Cloud via a supported SSO provider. If + you've changed group memberships in your identity provider or dbt Cloud, ask your + users to log back into dbt Cloud for these group memberships to be synchronized. + +- **Can I set up SSO without RBAC?** Yes, see the documentation on + [Manual Assignment](#manual-assignment) above for more information on using + SSO without RBAC. + +- **Can I configure a user's License Type based on IdP Attributes?** Yes, see + the docs on [managing license types](/cloud-seats-and-users#managing-license-types) + for more information. diff --git a/website/docs/docs/dbt-cloud/dbt-cloud-enterprise/audit-log.md b/website/docs/docs/collaborate/manage-access/audit-log.md similarity index 98% rename from website/docs/docs/dbt-cloud/dbt-cloud-enterprise/audit-log.md rename to website/docs/docs/collaborate/manage-access/audit-log.md index f179c0c1f84..e64969050a3 100644 --- a/website/docs/docs/dbt-cloud/dbt-cloud-enterprise/audit-log.md +++ b/website/docs/docs/collaborate/manage-access/audit-log.md @@ -1,13 +1,13 @@ --- -title: "Using the audit log for dbt Cloud Enterprise" +title: "The audit log for dbt Cloud Enterprise" id: audit-log description: "You can troubleshoot possible issues and provide security audits by reviewing event activity in your organization." -sidebar_label: "Using the audit log" +sidebar_label: "Audit log" --- To review actions performed by people in your organization, dbt provides logs of audited user and system events. The dbt Cloud audit log lists events triggered in your organization within the last 90 days. -Use the audit log to quickly review the actions performed by members of your organization. The audit log includes details such as who performed the action, what the action was, and when it was performed. You can use these details to troubleshoot access issues, perform security audits, or analyze specific events. +Use the audit log to quickly review the actions performed by members of your organization. The audit log includes details such as who performed the action, what the action was, and when it was performed. You can use these details to troubleshoot access issues, perform security audits, or analyze specific events. You must be an **Account Admin** to access the audit log and this feature is only available on Enterprise plans. diff --git a/website/docs/docs/dbt-cloud/access-control/cloud-seats-and-users.md b/website/docs/docs/collaborate/manage-access/cloud-seats-and-users.md similarity index 89% rename from website/docs/docs/dbt-cloud/access-control/cloud-seats-and-users.md rename to website/docs/docs/collaborate/manage-access/cloud-seats-and-users.md index 681a7f47367..d768e7c6e57 100644 --- a/website/docs/docs/dbt-cloud/access-control/cloud-seats-and-users.md +++ b/website/docs/docs/collaborate/manage-access/cloud-seats-and-users.md @@ -1,6 +1,6 @@ --- title: "Seats and Users" -id: "cloud-seats-and-users" +id: "seats-and-users" --- ## Overview @@ -10,7 +10,7 @@ different types of seat licenses in dbt Cloud: _Developer_ and _Read Only_. The type of license a user is assigned controls which capabilities of dbt Cloud the user is permitted to access. Users with a Developer license can be -granted access to the Deployment and [Development](the-dbt-ide) functionality +granted access to the Deployment and [Development](/docs/get-started/develop-in-the-cloud) functionality in dbt Cloud, whereas users with Read Only licenses are intended to view the [artifacts](docs/dbt-cloud/using-dbt-cloud/artifacts) created in a dbt Cloud account. @@ -20,8 +20,8 @@ in dbt Cloud, whereas users with Read Only licenses are intended to view the | Use Jobs | ✅ | ❌ | | Manage Account | ✅ | ❌ | | API Access | ✅ | ❌ | -| Use [Source Freshness](cloud-snapshotting-source-freshness) | ✅ | ✅ | -| Use [Docs](cloud-generating-documentation) | ✅ | ✅ | +| Use [Source Freshness](/docs/deploy/source-freshness) | ✅ | ✅ | +| Use [Docs](/docs/collaborate/build-and-view-your-docs) | ✅ | ✅ | ## Included seats @@ -66,7 +66,7 @@ change. **Note:** This feature is only available on the Enterprise plan. If your account is connected to an Identity Provider (IdP) for [Single Sign -On](dbt-cloud-enterprise/sso-overview), you can automatically map IdP user +On](/docs/collaborate/manage-access/sso-overview), you can automatically map IdP user groups to specific license types in dbt Cloud. To configure license mappings, navigate to the Account Settings > Team > License Mappings page. From here, you can create or edit SSO mappings for both Read Only and Developer @@ -96,5 +96,5 @@ Usage notes: ## Granular permissioning The dbt Cloud Enterprise plan supports Role-Based access controls for -configuring granular in-app permissions. See [access control](access-control-overview) +configuring granular in-app permissions. See [access control](/docs/collaborate/manage-access/about-access) for more information on Enterprise permissioning. diff --git a/website/docs/docs/dbt-cloud/access-control/enterprise-permissions.md b/website/docs/docs/collaborate/manage-access/enterprise-permissions.md similarity index 99% rename from website/docs/docs/dbt-cloud/access-control/enterprise-permissions.md rename to website/docs/docs/collaborate/manage-access/enterprise-permissions.md index bebbfe34b9a..4033b70900a 100644 --- a/website/docs/docs/dbt-cloud/access-control/enterprise-permissions.md +++ b/website/docs/docs/collaborate/manage-access/enterprise-permissions.md @@ -1,5 +1,5 @@ --- -title: "Enterprise Permissions" +title: "Enterprise permissions" id: "enterprise-permissions" description: "Permission sets for Enterprise plans." --- @@ -177,7 +177,7 @@ Click the gear icon to the top right and select **Account Settings**. From the * -1. Select an existing group or create a new group to add RBAC. Name the group (this can be any name you like, but it's recommended to keep it consistent with the SSO groups). If you have configured SSO with SAML 2.0, you may have to use the GroupID instead of the name of the group. +1. Select an existing group or create a new group to add RBAC. Name the group (this can be any name you like, but it's recommended to keep it consistent with the SSO groups). If you have configured SSO with SAML 2.0, you may have to use the GroupID instead of the name of the group. 2. Configure the SSO provider groups you want to add RBAC by clicking **Add** in the **SSO** section. These fields are case sensitive and must match the source group formatting. 3. Configure the permissions for users within those groups by clicking **Add** in the **Access** section of the window. diff --git a/website/docs/docs/dbt-cloud/access-control/access-control-overview.md b/website/docs/docs/collaborate/manage-access/licenses-and-groups.md similarity index 97% rename from website/docs/docs/dbt-cloud/access-control/access-control-overview.md rename to website/docs/docs/collaborate/manage-access/licenses-and-groups.md index 913b3e2fb32..da59601f508 100644 --- a/website/docs/docs/dbt-cloud/access-control/access-control-overview.md +++ b/website/docs/docs/collaborate/manage-access/licenses-and-groups.md @@ -1,6 +1,6 @@ --- -title: "Access Control" -id: "access-control-overview" +title: "Licenses and groups" +id: "licenses-and-groups" --- ## Overview @@ -100,7 +100,7 @@ assigned to groups. Some examples of existing permission sets are: - Job Viewer - ...and more -For a full list of enterprise permission sets, see [Enterprise Permissions](/docs/dbt-cloud/access-control/enterprise-permissions). +For a full list of enterprise permission sets, see [Enterprise Permissions](/docs/collaborate/manage-access/enterprise-permissions). These permission sets are available for assignment to groups and control the ability for users in these groups to take specific actions in the dbt Cloud application. diff --git a/website/docs/docs/dbt-cloud/access-control/self-service-permissions.md b/website/docs/docs/collaborate/manage-access/self-service-permissions.md similarity index 97% rename from website/docs/docs/dbt-cloud/access-control/self-service-permissions.md rename to website/docs/docs/collaborate/manage-access/self-service-permissions.md index dc70619da64..0d6375452aa 100644 --- a/website/docs/docs/dbt-cloud/access-control/self-service-permissions.md +++ b/website/docs/docs/collaborate/manage-access/self-service-permissions.md @@ -1,5 +1,5 @@ --- -title: "Self-Service Permissions" +title: "Self-service permissions" id: "self-service-permissions" --- ## Overview @@ -24,7 +24,7 @@ Users configured with Read Only license types will experience a restricted set o ## Owner and Member Groups in dbt Cloud Enterprise -By default, new users are added to the Member and Owner groups when they onboard to a new dbt Cloud account. Member and Owner groups are included with every new dbt Cloud account because they provide access for administrators to add users and groups, and to apply permission sets. +By default, new users are added to the Member and Owner groups when they onboard to a new dbt Cloud account. Member and Owner groups are included with every new dbt Cloud account because they provide access for administrators to add users and groups, and to apply permission sets. You will need owner and member groups to help with account onboarding, but these groups can create confusion when initially setting up SSO and RBAC for dbt Cloud Enterprise accounts as described in the [Enterprise Permissions](enterprise-permissions) guide. Owner and Member groups are **account level** groups, so their permissions override any project-level permissions you wish to apply. diff --git a/website/docs/docs/dbt-cloud/cloud-configuring-dbt-cloud/cloud-setting-up-bigquery-oauth.md b/website/docs/docs/collaborate/manage-access/set-up-bigquery-oauth.md similarity index 87% rename from website/docs/docs/dbt-cloud/cloud-configuring-dbt-cloud/cloud-setting-up-bigquery-oauth.md rename to website/docs/docs/collaborate/manage-access/set-up-bigquery-oauth.md index 21f385837f5..e807431245a 100644 --- a/website/docs/docs/dbt-cloud/cloud-configuring-dbt-cloud/cloud-setting-up-bigquery-oauth.md +++ b/website/docs/docs/collaborate/manage-access/set-up-bigquery-oauth.md @@ -1,5 +1,6 @@ --- -title: "Setting up BigQuery OAuth" +title: "Set up BigQuery OAuth" +id: "set-up-bigquery-oauth" --- :::info Enterprise Feature @@ -14,11 +15,11 @@ dbt Cloud supports developer [OAuth](https://cloud.google.com/bigquery/docs/auth To set up BigQuery OAuth in dbt Cloud, a BigQuery admin must: -1. [Create a BigQuery OAuth 2.0 client ID and secret](/cloud-setting-up-bigquery-oauth#creating-a-bigquery-oauth-20-client-id-and-secret) in BigQuery. -2. [Configure the connection](/cloud-setting-up-bigquery-oauth#configure-the-connection-in-dbt-cloud) in dbt Cloud. +1. [Create a BigQuery OAuth 2.0 client ID and secret](#creating-a-bigquery-oauth-20-client-id-and-secret) in BigQuery. +2. [Configure the connection](#configure-the-connection-in-dbt-cloud) in dbt Cloud. To use BigQuery in the dbt Cloud IDE, all developers must: -1. [Authenticate to BigQuery](/cloud-setting-up-bigquery-oauth#authenticating-to-bigquery) in the their profile credentials. +1. [Authenticate to BigQuery](#authenticating-to-bigquery) in the their profile credentials. ### Creating a BigQuery OAuth 2.0 client ID and secret @@ -44,7 +45,7 @@ Fill in the application details as follows: If you're a dbt Cloud single tenant customer, you need to replace `cloud.getdbt.com` with the hostname of your dbt Cloud instance. -Then click **Create** to create the BigQuery OAuth app and see the app client ID and secret values. These values are available even if you close the app screen, so this isn't the only chance you have to save them. +Then click **Create** to create the BigQuery OAuth app and see the app client ID and secret values. These values are available even if you close the app screen, so this isn't the only chance you have to save them. @@ -53,7 +54,7 @@ Then click **Create** to create the BigQuery OAuth app and see the app client ID ### Configure the Connection in dbt Cloud Now that you have an OAuth app set up in BigQuery, you'll need to add the client ID and secret to dbt Cloud. To do so: - go to [Settings](https://cloud.getdbt.com/next/settings/profile) - - on the left, select **Projects** under **Account Settings** + - on the left, select **Projects** under **Account Settings** - choose your project from the list - select **Connection** to edit the connection details - add the client ID and secret from the BigQuery OAuth app under the **OAuth2.0 Settings** section @@ -68,7 +69,7 @@ Once the BigQuery OAuth app is set up for a dbt Cloud project, each dbt Cloud us - select **Authenticate BigQuery Account** -You will then be redirected to BigQuery and asked to approve the drive, cloud platform, and BigQuery scopes, unless the connection is less privileged. +You will then be redirected to BigQuery and asked to approve the drive, cloud platform, and BigQuery scopes, unless the connection is less privileged. -Select **Allow**. This redirects you back to dbt Cloud. You should now be an authenticated BigQuery user, ready to use the dbt Cloud IDE. \ No newline at end of file +Select **Allow**. This redirects you back to dbt Cloud. You should now be an authenticated BigQuery user, ready to use the dbt Cloud IDE. diff --git a/website/docs/docs/dbt-cloud/dbt-cloud-enterprise/setting-up-snowflake-sso.md b/website/docs/docs/collaborate/manage-access/set-up-snowflake-oauth.md similarity index 93% rename from website/docs/docs/dbt-cloud/dbt-cloud-enterprise/setting-up-snowflake-sso.md rename to website/docs/docs/collaborate/manage-access/set-up-snowflake-oauth.md index 2b1bad5a563..677c01c93cd 100644 --- a/website/docs/docs/dbt-cloud/dbt-cloud-enterprise/setting-up-snowflake-sso.md +++ b/website/docs/docs/collaborate/manage-access/set-up-snowflake-oauth.md @@ -1,6 +1,6 @@ --- -title: "Setting up Snowflake OAuth" -id: "setting-up-enterprise-snowflake-oauth" +title: "Set up Snowflake OAuth" +id: "set-up-snowflake-oauth" --- :::info Enterprise Feature @@ -52,7 +52,7 @@ Additional configuration options may be specified for the security integration a The Database Admin is responsible for creating a Snowflake Connection in dbt Cloud. This Connection is configured using a Snowflake Client ID and Client Secret. When configuring a Connection in dbt Cloud, select the "Allow SSO Login" checkbox. Once this checkbox is selected, you will be prompted to enter an OAuth Client ID and OAuth Client Secret. These values can be determined by running the following query in Snowflake: ``` -with +with integration_secrets as ( select parse_json(system$show_oauth_client_secrets('DBT_CLOUD')) as secrets @@ -61,11 +61,11 @@ integration_secrets as ( select secrets:"OAUTH_CLIENT_ID"::string as client_id, secrets:"OAUTH_CLIENT_SECRET"::string as client_secret -from +from integration_secrets; ``` -Enter the Client ID and Client Secret into dbt Cloud to complete the creation of your Connection. +Enter the Client ID and Client Secret into dbt Cloud to complete the creation of your Connection. @@ -82,20 +82,20 @@ Once a user has authorized dbt Cloud with Snowflake via their identity provider, **NOTE**: The lifetime of the refresh token is dictated by the OAUTH_REFRESH_TOKEN_VALIDITY parameter supplied in the “create security integration” statement. When a user’s refresh token expires, the user will need to re-authorize with Snowflake to continue development in dbt Cloud. ### Setting up multiple dbt Cloud projects with Snowflake 0Auth -If you are planning to set up the same Snowflake account to different dbt Cloud projects, you can use the same security integration for all of the projects. +If you are planning to set up the same Snowflake account to different dbt Cloud projects, you can use the same security integration for all of the projects. -### FAQs +### FAQs #### How do I use the Blocked Roles List with dbt Cloud? ### Troubleshooting #### Invalid consent request -When clicking on the `Connect Snowflake Account` successfully redirects you to the Snowflake login page, but you receive an `Invalid consent request` error. This could mean: -* Your user might not have access to the Snowflake role defined on the development credentials in dbt Cloud. Double-check that you have access to that role and if the role name has been correctly entered in as Snowflake is case sensitive. -* You're trying to use a role that is in the [BLOCKED_ROLES_LIST](https://docs.snowflake.com/en/user-guide/oauth-partner.html#blocking-specific-roles-from-using-the-integration), such as `ACCOUNTADMIN`. +When clicking on the `Connect Snowflake Account` successfully redirects you to the Snowflake login page, but you receive an `Invalid consent request` error. This could mean: +* Your user might not have access to the Snowflake role defined on the development credentials in dbt Cloud. Double-check that you have access to that role and if the role name has been correctly entered in as Snowflake is case sensitive. +* You're trying to use a role that is in the [BLOCKED_ROLES_LIST](https://docs.snowflake.com/en/user-guide/oauth-partner.html#blocking-specific-roles-from-using-the-integration), such as `ACCOUNTADMIN`. #### Server error 500 -If you experience a 500 server error when redirected from Snowflake to dbt Cloud, double check that you have whitelisted [dbt Cloud's IP addresses](https://docs.getdbt.com/docs/dbt-cloud/cloud-configuring-dbt-cloud/connecting-your-database) on a Snowflake account level. +If you experience a 500 server error when redirected from Snowflake to dbt Cloud, double check that you have whitelisted [dbt Cloud's IP addresses](/docs/deploy/regions) on a Snowflake account level. Enterprise customers who have single-tenant deployments will have a different range of IP addresses (network CIDR ranges) to whitelist. diff --git a/website/docs/docs/dbt-cloud/dbt-cloud-enterprise/setting-up-enterprise-sso-with-azure-active-directory.md b/website/docs/docs/collaborate/manage-access/set-up-sso-azure-active-directory.md similarity index 96% rename from website/docs/docs/dbt-cloud/dbt-cloud-enterprise/setting-up-enterprise-sso-with-azure-active-directory.md rename to website/docs/docs/collaborate/manage-access/set-up-sso-azure-active-directory.md index 58aca1f5b10..5bf838b7dad 100644 --- a/website/docs/docs/dbt-cloud/dbt-cloud-enterprise/setting-up-enterprise-sso-with-azure-active-directory.md +++ b/website/docs/docs/collaborate/manage-access/set-up-sso-azure-active-directory.md @@ -1,6 +1,7 @@ --- -title: "Setting up SSO with Azure AD" -id: "setting-up-enterprise-sso-with-azure-active-directory" +title: "Set up SSO with Azure Active Directory" +id: "set-up-sso-azure-active-directory" +sidebar_label: "Set up SSO with Azure AD" --- :::info Enterprise Feature @@ -71,7 +72,7 @@ the Redirect URI in the steps above, then skip ahead to step 8. -### Azure <-> dbt Cloud User and Group mapping +### Azure <-> dbt Cloud User and Group mapping The Azure users and groups you will create in the following steps are mapped to groups created in dbt Cloud based on the group name. Reference the docs on [enterprise permissions](enterprise-permissions) for additional information on how users, groups, and permission sets are configured in dbt Cloud. @@ -89,7 +90,7 @@ Once you've registered the application, the next step is to assign users to it. :::info User assignment required? Under **Properties** check the toggle setting for **User assignment required?** and confirm it aligns to your requirements. Most customers will want this toggled to **Yes** so that only users/groups explicitly assigned to dbt Cloud will be able to sign in. If this setting is toggled to **No** any user will be able to access the application if they have a direct link to the application per [Azure AD Documentation](https://docs.microsoft.com/en-us/azure/active-directory/manage-apps/assign-user-or-group-access-portal#configure-an-application-to-require-user-assignment) -::: +::: ### Configuring permissions @@ -162,16 +163,15 @@ by navigating to the URL: `https://cloud.getdbt.com/enterprise-login/` ::: -*Note:* If your dbt account is a VPC deployment, your login URL will use the domain supplied to you by your dbt Labs account team, instead of the domain `cloud.getdbt.com`. +*Note:* If your dbt account is a VPC deployment, your login URL will use the domain supplied to you by your dbt Labs account team, instead of the domain `cloud.getdbt.com`. ## Setting up RBAC Now you have completed setting up SSO with Azure AD, the next steps will be to set up -[RBAC groups](/docs/dbt-cloud/access-control/enterprise-permissions) to complete your access control configuration. +[RBAC groups](/docs/collaborate/manage-access/enterprise-permissions) to complete your access control configuration. ## Troubleshooting Tips Ensure that the domain name under which user accounts exist in Azure matches the domain you supplied in [Supplying credentials](#supplying-credentials) when you configured SSO. - diff --git a/website/docs/docs/dbt-cloud/dbt-cloud-enterprise/setting-up-sso-with-google-gsuite.md b/website/docs/docs/collaborate/manage-access/set-up-sso-google-workspace.md similarity index 96% rename from website/docs/docs/dbt-cloud/dbt-cloud-enterprise/setting-up-sso-with-google-gsuite.md rename to website/docs/docs/collaborate/manage-access/set-up-sso-google-workspace.md index f70b55c2921..9c343953c5f 100644 --- a/website/docs/docs/dbt-cloud/dbt-cloud-enterprise/setting-up-sso-with-google-gsuite.md +++ b/website/docs/docs/collaborate/manage-access/set-up-sso-google-workspace.md @@ -1,6 +1,6 @@ --- -title: "Setting up SSO with GSuite" -id: "setting-up-sso-with-google-gsuite" +title: "Set up SSO with Google Workspace" +id: "set-up-sso-google-workspace" --- :::info Enterprise Feature @@ -13,10 +13,10 @@ dbt Cloud Enterprise supports Single-Sign On (SSO) via Google GSuite. You will n permissions to create and manage a new Google OAuth2 application, as well as access to enable the Google Admin SDK. Gsuite is a component within Google Cloud Platform (GCP), so you will also need access to a login with permissions -to manage the GSuite application within a GCP account. +to manage the GSuite application within a GCP account. Some customers choose to use different cloud providers for User and Group permission setup -than for hosting infrastructure. For example, it's certainly possible to use GSuite to +than for hosting infrastructure. For example, it's certainly possible to use GSuite to manage login information and Multifactor Authentication (MFA) configuration while hosting data workloads on AWS. @@ -131,7 +131,7 @@ into the dbt Cloud application at `https://cloud.getdbt.com/enterprise-login/` body should be a JSON string in the format: Every query will rely on a *jobID*. You can get the jobID by clicking into the relevant job in dbt Cloud and observing the URL. In this example URL, the jobID would be 917: `https://cloud.getdbt.com/#/accounts/1/projects/665/jobs/917/` -There are several illustrative example queries in this documentation (examples of queries on the Model node, [here](/docs/dbt-cloud/dbt-cloud-api/metadata/schema/metadata-schema-model). +There are several illustrative example queries in this documentation (examples of queries on the Model node, [here](/docs/dbt-cloud-apis/metadata-schema-model). ## GraphiQL You can also experiment and run queries directly in the [GraphiQL interface](https://metadata.cloud.getdbt.com/graphiql), which is convenient for exploration. On the right hand side, there is a document explorer where you can see all possible nodes and fields. Below is an example of what a query looks like in GraphiQL. Note that you must authenticate via bearer auth with your token. diff --git a/website/docs/docs/dbt-cloud/dbt-cloud-api/metadata/schema/schema-metadata-exposure.mdx b/website/docs/docs/dbt-cloud-apis/schema-metadata-exposure.mdx similarity index 97% rename from website/docs/docs/dbt-cloud/dbt-cloud-api/metadata/schema/schema-metadata-exposure.mdx rename to website/docs/docs/dbt-cloud-apis/schema-metadata-exposure.mdx index 95991a19304..5297cc7da53 100644 --- a/website/docs/docs/dbt-cloud/dbt-cloud-api/metadata/schema/schema-metadata-exposure.mdx +++ b/website/docs/docs/dbt-cloud-apis/schema-metadata-exposure.mdx @@ -5,7 +5,7 @@ id: "metadata-schema-exposure" import { ArgsTable, SchemaTable } from "./schema"; -The exposure object allows you to query information about a particular exposure. You can learn more about exposures [here](/docs/building-a-dbt-project/exposures). +The exposure object allows you to query information about a particular exposure. You can learn more about exposures [here](/docs/build/exposures). ### Arguments diff --git a/website/docs/docs/dbt-cloud/dbt-cloud-api/metadata/schema/schema-metadata-exposures.mdx b/website/docs/docs/dbt-cloud-apis/schema-metadata-exposures.mdx similarity index 96% rename from website/docs/docs/dbt-cloud/dbt-cloud-api/metadata/schema/schema-metadata-exposures.mdx rename to website/docs/docs/dbt-cloud-apis/schema-metadata-exposures.mdx index e4d9f54f53e..54ec4bbc905 100644 --- a/website/docs/docs/dbt-cloud/dbt-cloud-api/metadata/schema/schema-metadata-exposures.mdx +++ b/website/docs/docs/dbt-cloud-apis/schema-metadata-exposures.mdx @@ -5,7 +5,7 @@ id: "metadata-schema-exposures" import { ArgsTable, SchemaTable } from "./schema"; -The exposures object allows you to query information about all exposures in a given job. You can learn more about exposures [here](/docs/building-a-dbt-project/exposures). +The exposures object allows you to query information about all exposures in a given job. You can learn more about exposures [here](/docs/build/exposures). ### Arguments diff --git a/website/docs/docs/dbt-cloud/dbt-cloud-api/metadata/schema/schema-metadata-metric.mdx b/website/docs/docs/dbt-cloud-apis/schema-metadata-metric.mdx similarity index 89% rename from website/docs/docs/dbt-cloud/dbt-cloud-api/metadata/schema/schema-metadata-metric.mdx rename to website/docs/docs/dbt-cloud-apis/schema-metadata-metric.mdx index 1b7d371ffa3..46a1e79abba 100644 --- a/website/docs/docs/dbt-cloud/dbt-cloud-api/metadata/schema/schema-metadata-metric.mdx +++ b/website/docs/docs/dbt-cloud-apis/schema-metadata-metric.mdx @@ -18,7 +18,7 @@ Below we show some illustrative example queries and outline the schema (all poss ### Example Queries #### Metric information -The example query below outputs information about a metric. Note that you can also add any field from the Model endpoint -- here we are simply selecting name. This includes schema, database, uniqueId, columns and more -- find documentation [here](https://docs.getdbt.com/docs/dbt-cloud/dbt-cloud-api/metadata/schema/metadata-schema-model). +The example query below outputs information about a metric. Note that you can also add any field from the Model endpoint -- here we are simply selecting name. This includes schema, database, uniqueId, columns and more -- find documentation [here](/docs/dbt-cloud-apis/metadata-schema-model). ```graphql diff --git a/website/docs/docs/dbt-cloud/dbt-cloud-api/metadata/schema/schema-metadata-metrics.mdx b/website/docs/docs/dbt-cloud-apis/schema-metadata-metrics.mdx similarity index 83% rename from website/docs/docs/dbt-cloud/dbt-cloud-api/metadata/schema/schema-metadata-metrics.mdx rename to website/docs/docs/dbt-cloud-apis/schema-metadata-metrics.mdx index 48a882318c2..b9077e228bd 100644 --- a/website/docs/docs/dbt-cloud/dbt-cloud-api/metadata/schema/schema-metadata-metrics.mdx +++ b/website/docs/docs/dbt-cloud-apis/schema-metadata-metrics.mdx @@ -51,7 +51,7 @@ The example query returns information about all metrics in this job. ``` ### Fields -metrics has access to the *same fields* as the [metric node](/docs/dbt-cloud/dbt-cloud-api/metadata/schema/metadata-schema-metric). The difference is that metrics can output a list, so instead of querying for fields for one specific metric, you can query for those parameters for all metrics in a run. +metrics has access to the *same fields* as the [metric node](/docs/dbt-cloud-apis/metadata-schema-metric). The difference is that metrics can output a list, so instead of querying for fields for one specific metric, you can query for those parameters for all metrics in a run. When querying for `metrics`, the following fields are available: diff --git a/website/docs/docs/dbt-cloud/dbt-cloud-api/metadata/schema/schema-metadata-model.mdx b/website/docs/docs/dbt-cloud-apis/schema-metadata-model.mdx similarity index 100% rename from website/docs/docs/dbt-cloud/dbt-cloud-api/metadata/schema/schema-metadata-model.mdx rename to website/docs/docs/dbt-cloud-apis/schema-metadata-model.mdx diff --git a/website/docs/docs/dbt-cloud/dbt-cloud-api/metadata/schema/schema-metadata-modelByEnv.mdx b/website/docs/docs/dbt-cloud-apis/schema-metadata-modelByEnv.mdx similarity index 100% rename from website/docs/docs/dbt-cloud/dbt-cloud-api/metadata/schema/schema-metadata-modelByEnv.mdx rename to website/docs/docs/dbt-cloud-apis/schema-metadata-modelByEnv.mdx diff --git a/website/docs/docs/dbt-cloud/dbt-cloud-api/metadata/schema/schema-metadata-models.mdx b/website/docs/docs/dbt-cloud-apis/schema-metadata-models.mdx similarity index 85% rename from website/docs/docs/dbt-cloud/dbt-cloud-api/metadata/schema/schema-metadata-models.mdx rename to website/docs/docs/dbt-cloud-apis/schema-metadata-models.mdx index 802e5d03a24..00bef5e1197 100644 --- a/website/docs/docs/dbt-cloud/dbt-cloud-api/metadata/schema/schema-metadata-models.mdx +++ b/website/docs/docs/dbt-cloud-apis/schema-metadata-models.mdx @@ -46,7 +46,7 @@ The example query below finds all models in this schema, and their respective ex ### Fields -Models has access to the *same fields* as the [Model node](/docs/dbt-cloud/dbt-cloud-api/metadata/schema/metadata-schema-model). The difference is that Models can output a list, so instead of querying for fields for one specific model, you can query for those parameters for all models within a jobID, database, etc. +Models has access to the *same fields* as the [Model node](/docs/dbt-cloud-apis/metadata-schema-model). The difference is that Models can output a list, so instead of querying for fields for one specific model, you can query for those parameters for all models within a jobID, database, etc. When querying for `models`, the following fields are available: diff --git a/website/docs/docs/dbt-cloud/dbt-cloud-api/metadata/schema/schema-metadata-seed.mdx b/website/docs/docs/dbt-cloud-apis/schema-metadata-seed.mdx similarity index 100% rename from website/docs/docs/dbt-cloud/dbt-cloud-api/metadata/schema/schema-metadata-seed.mdx rename to website/docs/docs/dbt-cloud-apis/schema-metadata-seed.mdx diff --git a/website/docs/docs/dbt-cloud/dbt-cloud-api/metadata/schema/schema-metadata-seeds.mdx b/website/docs/docs/dbt-cloud-apis/schema-metadata-seeds.mdx similarity index 100% rename from website/docs/docs/dbt-cloud/dbt-cloud-api/metadata/schema/schema-metadata-seeds.mdx rename to website/docs/docs/dbt-cloud-apis/schema-metadata-seeds.mdx diff --git a/website/docs/docs/dbt-cloud/dbt-cloud-api/metadata/schema/schema-metadata-snapshots.mdx b/website/docs/docs/dbt-cloud-apis/schema-metadata-snapshots.mdx similarity index 82% rename from website/docs/docs/dbt-cloud/dbt-cloud-api/metadata/schema/schema-metadata-snapshots.mdx rename to website/docs/docs/dbt-cloud-apis/schema-metadata-snapshots.mdx index 7d061ff0e0c..19b94c1462b 100644 --- a/website/docs/docs/dbt-cloud/dbt-cloud-api/metadata/schema/schema-metadata-snapshots.mdx +++ b/website/docs/docs/dbt-cloud-apis/schema-metadata-snapshots.mdx @@ -38,7 +38,7 @@ The example query returns information about all snapshots in this job. ``` ### Fields -Snapshots has access to the *same fields* as the [Snapshot node](/docs/dbt-cloud/dbt-cloud-api/metadata/schema/metadata-schema-snapshots). The difference is that Snapshots can output a list, so instead of querying for fields for one specific snapshot, you can query for those parameters for all snapshots within a jobID, database, etc. +Snapshots has access to the *same fields* as the [Snapshot node](/docs/dbt-cloud-apis/metadata-schema-snapshots). The difference is that Snapshots can output a list, so instead of querying for fields for one specific snapshot, you can query for those parameters for all snapshots within a jobID, database, etc. When querying for `snapshots`, the following fields are available: diff --git a/website/docs/docs/dbt-cloud/dbt-cloud-api/metadata/schema/schema-metadata-source.mdx b/website/docs/docs/dbt-cloud-apis/schema-metadata-source.mdx similarity index 100% rename from website/docs/docs/dbt-cloud/dbt-cloud-api/metadata/schema/schema-metadata-source.mdx rename to website/docs/docs/dbt-cloud-apis/schema-metadata-source.mdx diff --git a/website/docs/docs/dbt-cloud/dbt-cloud-api/metadata/schema/schema-metadata-sources.mdx b/website/docs/docs/dbt-cloud-apis/schema-metadata-sources.mdx similarity index 85% rename from website/docs/docs/dbt-cloud/dbt-cloud-api/metadata/schema/schema-metadata-sources.mdx rename to website/docs/docs/dbt-cloud-apis/schema-metadata-sources.mdx index 3c851ba25cf..e124e621baa 100644 --- a/website/docs/docs/dbt-cloud/dbt-cloud-api/metadata/schema/schema-metadata-sources.mdx +++ b/website/docs/docs/dbt-cloud-apis/schema-metadata-sources.mdx @@ -45,7 +45,7 @@ The example query below finds all sources in this schema, and their respective s ``` ### Fields -Sources has access to the *same fields* as the [Source node](/docs/dbt-cloud/dbt-cloud-api/metadata/schema/metadata-schema-source). The difference is that Sources can output a list, so instead of querying for fields for one specific source, you can query for those parameters for all sources within a jobID, database, etc. +Sources has access to the *same fields* as the [Source node](/docs/dbt-cloud-apis/metadata-schema-source). The difference is that Sources can output a list, so instead of querying for fields for one specific source, you can query for those parameters for all sources within a jobID, database, etc. When querying for `sources`, the following fields are available: diff --git a/website/docs/docs/dbt-cloud/dbt-cloud-api/metadata/schema/schema-metadata-test.mdx b/website/docs/docs/dbt-cloud-apis/schema-metadata-test.mdx similarity index 100% rename from website/docs/docs/dbt-cloud/dbt-cloud-api/metadata/schema/schema-metadata-test.mdx rename to website/docs/docs/dbt-cloud-apis/schema-metadata-test.mdx diff --git a/website/docs/docs/dbt-cloud/dbt-cloud-api/metadata/schema/schema-metadata-tests.mdx b/website/docs/docs/dbt-cloud-apis/schema-metadata-tests.mdx similarity index 100% rename from website/docs/docs/dbt-cloud/dbt-cloud-api/metadata/schema/schema-metadata-tests.mdx rename to website/docs/docs/dbt-cloud-apis/schema-metadata-tests.mdx diff --git a/website/docs/docs/dbt-cloud/dbt-cloud-api/metadata/schema/schema.jsx b/website/docs/docs/dbt-cloud-apis/schema.jsx similarity index 100% rename from website/docs/docs/dbt-cloud/dbt-cloud-api/metadata/schema/schema.jsx rename to website/docs/docs/dbt-cloud-apis/schema.jsx diff --git a/website/docs/docs/dbt-cloud/dbt-cloud-api/service-tokens.md b/website/docs/docs/dbt-cloud-apis/service-tokens.md similarity index 72% rename from website/docs/docs/dbt-cloud/dbt-cloud-api/service-tokens.md rename to website/docs/docs/dbt-cloud-apis/service-tokens.md index b91fa9511fb..f4d3191756a 100644 --- a/website/docs/docs/dbt-cloud/dbt-cloud-api/service-tokens.md +++ b/website/docs/docs/dbt-cloud-apis/service-tokens.md @@ -13,7 +13,7 @@ You can use service account tokens for system-level integrations that do not run * Enterprise plans can apply any permission sets available to service tokens. * Team plans can apply Account Admin, Member, Job Admin, Read-Only, and Metadata permissions sets to service tokens. -You can assign as many permission sets as needed to one token. For more on permissions sets, see "[Enterprise Permissions](docs/dbt-cloud/access-control/enterprise-permissions)." +You can assign as many permission sets as needed to one token. For more on permissions sets, see "[Enterprise Permissions](/docs/collaborate/manage-access/enterprise-permissions)." ## Generating service account tokens @@ -34,7 +34,7 @@ You can assign service account tokens any permission set available in dbt Cloud. The following permissions can be assigned to a service account token on a Team plan. **Account Admin**
-Account Admin service tokens have full `read + write` access to an account, so please use them with caution. A Team plan refers to this permission set as an "Owner role." For more on these permissions, see [Account Viewer](docs/dbt-cloud/access-control/enterprise-permissions#account-admin). +Account Admin service tokens have full `read + write` access to an account, so please use them with caution. A Team plan refers to this permission set as an "Owner role." For more on these permissions, see [Account Admin](/docs/collaborate/manage-access/enterprise-permissions#account-admin). **Metadata Only**
Metadata only service tokens can authorize requests to the metadata API. @@ -43,47 +43,47 @@ Metadata only service tokens can authorize requests to the metadata API. Job admin service tokens can authorize requests for viewing, editing, and creating environments, triggering runs, and viewing historical runs. **Member**
-Member service tokens can authorize requests for viewing and editing resources, triggering runs, and inviting members to the account. Tokens assigned the Member permission set will have the same permissions as a Member user. For more information about Member users, see "[Self-service permissions](/dbt-cloud/access-control/self-service-permissions)". +Member service tokens can authorize requests for viewing and editing resources, triggering runs, and inviting members to the account. Tokens assigned the Member permission set will have the same permissions as a Member user. For more information about Member users, see "[Self-service permissions](/docs/collaborate/manage-access/self-service-permissions)". **Read-only**
Read-only service tokens can authorize requests for viewing a read-only dashboard, viewing generated documentation, and viewing source freshness reports. ### Enterprise plans using service account tokens -The following permissions can be assigned to a service account token on an Enterprise plan. For more details about these permissions, see "[Enterprise permissions](/docs/dbt-cloud/access-control/enterprise-permissions)." +The following permissions can be assigned to a service account token on an Enterprise plan. For more details about these permissions, see "[Enterprise permissions](/docs/collaborate/manage-access/enterprise-permissions)." **Account Admin**
-Account Admin service tokens have full `read + write` access to an account, so please use them with caution. For more on these permissions, see [Account Viewer](docs/dbt-cloud/access-control/enterprise-permissions#account-admin). +Account Admin service tokens have full `read + write` access to an account, so please use them with caution. For more on these permissions, see [Account Viewer](/docs/collaborate/manage-access/enterprise-permissions#account-admin). **Metadata Only**
Metadata only service tokens can authorize requests to the metadata API. **Job Admin**
-Job Admin service tokens can authorize request for viewing, editing, and creating environments, triggering runs, and viewing historical runs. For more on these permissions, see [Account Viewer](docs/dbt-cloud/access-control/enterprise-permissions#job-admin). +Job Admin service tokens can authorize request for viewing, editing, and creating environments, triggering runs, and viewing historical runs. For more on these permissions, see [Account Viewer](/docs/collaborate/manage-access/enterprise-permissions#job-admin). **Account Viewer**
-Account Viewer service tokens have read only access to dbt Cloud accounts. For more on these permissions, see [Account Viewer](docs/dbt-cloud/access-control/enterprise-permissions#account-viewer) on the Enterprise Permissions page. +Account Viewer service tokens have read only access to dbt Cloud accounts. For more on these permissions, see [Account Viewer](/docs/collaborate/manage-access/enterprise-permissions#account-viewer) on the Enterprise Permissions page. **Admin**
-Admin service tokens have unrestricted access to projects in dbt Cloud accounts. You have the option to grant that permission all projects in the account or grant the permission only on specific projects. For more on these permissions, see [Admin Service](docs/dbt-cloud/access-control/enterprise-permissions#admin-service) on the Enterprise Permissions page. +Admin service tokens have unrestricted access to projects in dbt Cloud accounts. You have the option to grant that permission all projects in the account or grant the permission only on specific projects. For more on these permissions, see [Admin Service](/docs/collaborate/manage-access/enterprise-permissions#admin-service) on the Enterprise Permissions page. **Git Admin**
-Git admin service tokens have all the permissions listed in [Git admin](/docs/dbt-cloud/access-control/enterprise-permissions#git-admin) on the Enterprise Permissions page. +Git admin service tokens have all the permissions listed in [Git admin](/docs/collaborate/manage-access/enterprise-permissions#git-admin) on the Enterprise Permissions page. **Database Adminn**
-Database admin service tokens have all the permissions listed in [Database admin](/docs/dbt-cloud/access-control/enterprise-permissions#database-admin) on the Enterprise Permissions page. +Database admin service tokens have all the permissions listed in [Database admin](/docs/collaborate/manage-access/enterprise-permissions#database-admin) on the Enterprise Permissions page. **Team Admin**
-Team admin service tokens have all the permissions listed in [Team admin](/docs/dbt-cloud/access-control/enterprise-permissions#team-admin) on the Enterprise Permissions page. +Team admin service tokens have all the permissions listed in [Team admin](/docs/collaborate/manage-access/enterprise-permissions#team-admin) on the Enterprise Permissions page. **Job Viewer**
-Job viewer admin service tokens have all the permissions listed in [Job viewer](/docs/dbt-cloud/access-control/enterprise-permissions#job-viewer) on the Enterprise Permissions page. +Job viewer admin service tokens have all the permissions listed in [Job viewer](/docs/collaborate/manage-access/enterprise-permissions#job-viewer) on the Enterprise Permissions page. **Developer**
-Developer service tokens have all the permissions listed in [Developer](/docs/dbt-cloud/access-control/enterprise-permissions#developer) on the Enterprise Permissions page. +Developer service tokens have all the permissions listed in [Developer](/docs/collaborate/manage-access/enterprise-permissions#developer) on the Enterprise Permissions page. **Analyst**
-Analyst admin service tokens have all the permissions listed in [Analyst](/docs/dbt-cloud/access-control/enterprise-permissions#analyst) on the Enterprise Permissions page. +Analyst admin service tokens have all the permissions listed in [Analyst](/docs/collaborate/manage-access/enterprise-permissions#analyst) on the Enterprise Permissions page. **Stakeholder**
-Stakeholder service tokens have all the permissions listed in [Stakeholder](/docs/dbt-cloud/access-control/enterprise-permissions#stakeholder) on the Enterprise Permissions page. +Stakeholder service tokens have all the permissions listed in [Stakeholder](/docs/collaborate/manage-access/enterprise-permissions#stakeholder) on the Enterprise Permissions page. diff --git a/website/docs/docs/dbt-cloud/dbt-cloud-api/user-tokens.md b/website/docs/docs/dbt-cloud-apis/user-tokens.md similarity index 100% rename from website/docs/docs/dbt-cloud/dbt-cloud-api/user-tokens.md rename to website/docs/docs/dbt-cloud-apis/user-tokens.md diff --git a/website/docs/docs/dbt-cloud/cloud-configuring-dbt-cloud.md b/website/docs/docs/dbt-cloud/cloud-configuring-dbt-cloud.md deleted file mode 100644 index abb432d11d1..00000000000 --- a/website/docs/docs/dbt-cloud/cloud-configuring-dbt-cloud.md +++ /dev/null @@ -1,14 +0,0 @@ ---- -title: "Setup" -id: "cloud-configuring-dbt-cloud" ---- - -The following sections will help you set up your dbt Cloud account: - -- [Connecting your database](connecting-your-database) -- [Using a dbt Cloud managed repository](cloud-using-a-managed-repository) -- [Connecting your GitHub Account](cloud-installing-the-github-application) -- [Importing a project by git URL](cloud-import-a-project-by-git-url) -- [Access Control](/docs/dbt-cloud/access-control/access-control-overview) -- [Self-Service Permissions](/docs/dbt-cloud/access-control/self-service-permissions) -- [Choosing a dbt version](cloud-choosing-a-dbt-version) diff --git a/website/docs/docs/dbt-cloud/cloud-configuring-dbt-cloud/cloud-choosing-a-dbt-version.md b/website/docs/docs/dbt-cloud/cloud-configuring-dbt-cloud/cloud-choosing-a-dbt-version.md index b95997df31d..02f29adbd0b 100644 --- a/website/docs/docs/dbt-cloud/cloud-configuring-dbt-cloud/cloud-choosing-a-dbt-version.md +++ b/website/docs/docs/dbt-cloud/cloud-configuring-dbt-cloud/cloud-choosing-a-dbt-version.md @@ -38,7 +38,7 @@ We will continue to update this table so that customers know when we plan to sto Accounts had until the end of June 2022 to upgrade to dbt 1.0 or later. Pre-dbt 1.0 versions will no longer receive patch fixes, and our support team will no longer assist with dbt version specific help on non-supported versions of dbt. Additionally, jobs running dbt versions prior to 1.0 may experience service disruptions before the end of the year and may be removed from the dbt Cloud context by year end. You will receive additional notification before any planned disruption to your production jobs. ::: -Starting in v1.0, dbt Cloud will ensure that you're always using the latest compatible patch release of `dbt-core` and plugins, including all the latest fixes. You may also choose to try prereleases of those patch releases before they are generally available. +Starting in v1.0, dbt Cloud will ensure that you're always using the latest compatible patch release of `dbt-core` and plugins, including all the latest fixes. You may also choose to try prereleases of those patch releases before they are generally available. + +For more on version support and future releases, see [Understanding dbt Core versions](core-versions). + +#### What will actually happen on the end of support date? + +1 year post a minor version release of v1.X, we will try to run our users' projects on the latest release of dbt if they have not already upgraded their projects themselves. In a post dbt v1.0 world, there won't be breaking changes between minor versions of dbt, so we might be reasonably successful at upgrading our users' versions for them. However, our strong preference is for accounts to try to manage the upgrade process themselves which is a more cautious way to prevent failures to their production pipelines. We will give accounts consistent communication that they're hitting the end of their supported window, so they can plan accordingly. + +#### What should you be doing today? + +You should **upgrade to v1.0 as soon as you can** - and we recommend that you proceed **slowly and steadily**. + +Why? Because attempting to upgrade 6 minor versions at one time (v0.15.0 —> v0.21.0) implies 6x the potential for breaking changes, versus upgrading a single minor version. + +Refactoring code is much easier when you're updating a well-defined, constrained surface area. Doing things incrementally is the way to go. + +Additionally upgrading to more recent versions of dbt Core will enable better performance and more features in dbt Cloud. Below is a compatability matrix between dbt versions and dbt Cloud features. Hopefully this provides more motivation to always update your environments and jobs to run the latest version of dbt. + + + +| dbt Cloud Feature | dbt Core Version Needed | +| ------------- | -------------- | +| [Environment variable secret scrubbing](/docs/dbt-cloud/using-dbt-cloud/cloud-environment-variables#handling-secrets)| v1.0+ | +| DAG in the IDE | v0.20.0+| +| [Metadata API](/docs/dbt-cloud-apis/metadata-api) |v0.19.0+| +| [Dashboard status tiles](/docs/dbt-cloud/using-dbt-cloud/cloud-dashboard-status-tiles) | v0.19.0+ | +| [Slim CI](/docs/dbt-cloud/using-dbt-cloud/cloud-enabling-continuous-integration-with-github#slim-ci) | v0.18.0+ | + +#### Need help upgrading? + +If you want more advice on how to upgrade your dbt projects, check out our [migration guides](/guides/migration/versions/) and our [upgrading Q&A page](docs/dbt-cloud/cloud-configuring-dbt-cloud/cloud-upgrading-dbt-versions). + + +## Upgrading legacy versions under 1.0 + +This Q&A guide should help you figure out what changes you might need to make to successfully upgrade your version of dbt Core in dbt Cloud. As a reminder, we recommend everyone upgrade to the most recent version of dbt, as we will not support all versions of dbt in Cloud indefinitely. We document which versions of dbt Core we support [here](docs/dbt-cloud/cloud-configuring-dbt-cloud/cloud-choosing-a-dbt-version#supported-versions). + +There aren't many breaking changes between minor versions, and it may be the case that you don't need to change any code to upgrade to a newer version of dbt in dbt Cloud. There are only breaking changes between minor versions of dbt before dbt 1.0. Minor releases starting with dbt 1.0, do not have breaking code changes. If there are no code changes needed, all you have to do is [change the settings](/docs/dbt-cloud/cloud-configuring-dbt-cloud/cloud-choosing-a-dbt-version.md) in your environment or job to run a more recent version of dbt. #### Changes between minor versions of dbt that will affect your project @@ -232,7 +307,7 @@ If you believe your project might be affected, read more details in the migratio #### Testing your changes before upgrading Once you have an idea about what code changes you'll need to make, you can start implementing them. We recommend that you create a separate dbt project, **Upgrade Project**, to test your changes before making them live in your main dbt project. In your **Upgrade Project**, connect to the same repository that you use for your main dbt project, but this time, set the development environment [settings](docs/dbt-cloud/cloud-configuring-dbt-cloud/cloud-choosing-a-dbt-version) to run the latest version of dbt Core. Next check out a branch `dbt-version-upgrade`, make the appropriate updates to your project (if needed), and see if your dbt project compiles and runs with the new version of dbt in the IDE. If jumping directly to the latest version of dbt is too far of a leap for your project, try iteratively getting your project to work on each successive minor version. There are years of development and a handful of breaking changes between two distant versions of dbt (e.g. 0.14 --> 1.0). There are far fewer between two subsequent versions of dbt, which is why upgrading regularly is important. -Once you have your project compiling and running on the latest version of dbt in the development environment for your `dbt-version-upgrade` branch, try replicating one of your production jobs to run off your branch's code. You can do this by creating a new deployment environment for testing, setting the custom branch to 'ON' and referencing your `dbt-version-upgrade` branch. You'll also need to set the dbt version in this environment to the latest dbt Core version. +Once you have your project compiling and running on the latest version of dbt in the development environment for your `dbt-version-upgrade` branch, try replicating one of your production jobs to run off your branch's code. You can do this by creating a new deployment environment for testing, setting the custom branch to 'ON' and referencing your `dbt-version-upgrade` branch. You'll also need to set the dbt version in this environment to the latest dbt Core version. @@ -240,4 +315,3 @@ Once you have your project compiling and running on the latest version of dbt in Then add a job to the new testing environment that replicates one of the production jobs your team relies on. If that job runs smoothly, you should be all set to merge your branch into main and change your development and deployment environments in your main dbt project to run off the newest version of dbt Core. - diff --git a/website/docs/docs/dbt-cloud/deployments/airgapped.md b/website/docs/docs/deploy/airgapped.md similarity index 100% rename from website/docs/docs/dbt-cloud/deployments/airgapped.md rename to website/docs/docs/deploy/airgapped.md diff --git a/website/docs/docs/dbt-cloud/deployments/architecture.md b/website/docs/docs/deploy/architecture.md similarity index 98% rename from website/docs/docs/dbt-cloud/deployments/architecture.md rename to website/docs/docs/deploy/architecture.md index 53026b580cb..2db65c53ea2 100644 --- a/website/docs/docs/dbt-cloud/deployments/architecture.md +++ b/website/docs/docs/deploy/architecture.md @@ -1,6 +1,6 @@ --- -id: deployment-architecture title: Architecture +id: architecture --- This page is intended to help both practitioners seeking to understand the architecture and data flow of the hosted dbt Cloud product. @@ -40,7 +40,7 @@ The following two sections describe the network architectures for dbt Cloud depl #### Hosted Network Architecture -The following diagram shows the network architecture for the hosted _Multi Tenant_ and _Single Tenant_ deployment types. While many of the specifications differ between the Multi Tenant and Single Tenant offerings the basic types of components illustrated below are mostly the same. Read below for more information on each of the components and how they might differ between the two deployment models. +The following diagram shows the network architecture for the hosted _Multi Tenant_ and _Single Tenant_ deployment types. While many of the specifications differ between the Multi Tenant and Single Tenant offerings the basic types of components illustrated below are mostly the same. Read below for more information on each of the components and how they might differ between the two deployment models. @@ -50,5 +50,5 @@ The following diagram shows the network architecture for the hosted _Multi Tenan - **EC2**: The hosted dbt Cloud deployments leverage a cluster of [AWS EC2](https://aws.amazon.com/ec2/) worker nodes to run the dbt Cloud application. - **EBS**: In order to store application data, dbt Cloud leverages [AWS Elastic Block Store](https://aws.amazon.com/ebs/) mounted to the EC2 instances described above. - **EFS**: An [AWS Elastic File System](https://aws.amazon.com/efs/) is provisioned for hosted deployments to store and manage local files from the dbt Cloud IDE. -- **S3**: [AWS Simple Storage Service (S3)](https://aws.amazon.com/s3/) is used to store dbt Cloud application logs and artifacts (such as those generated from dbt job runs). +- **S3**: [AWS Simple Storage Service (S3)](https://aws.amazon.com/s3/) is used to store dbt Cloud application logs and artifacts (such as those generated from dbt job runs). - **RDS**: The hosted dbt Cloud application leverages [AWS Postgres RDS](https://aws.amazon.com/rds/postgresql/) to store application information such as accounts, users, environments, etc. Note that as explained in the [Data Warehouse Interaction](#data-warehouse-interaction) section above, no data from an associated warehouse is ever stored in this database. diff --git a/website/docs/docs/dbt-cloud/using-dbt-cloud/cloud-enabling-continuous-integration-with-github.md b/website/docs/docs/deploy/cloud-ci-job.md similarity index 80% rename from website/docs/docs/dbt-cloud/using-dbt-cloud/cloud-enabling-continuous-integration-with-github.md rename to website/docs/docs/deploy/cloud-ci-job.md index 3f4a112ed7d..da32eec4b98 100644 --- a/website/docs/docs/dbt-cloud/using-dbt-cloud/cloud-enabling-continuous-integration-with-github.md +++ b/website/docs/docs/deploy/cloud-ci-job.md @@ -1,14 +1,14 @@ --- -title: "Enabling Continuous Integration (CI)" -id: "cloud-enabling-continuous-integration" -description: "You can enable CI to test every single change prior to deploying the code to production just like in a software development workflow." +title: "dbt Cloud CI job" +id: "cloud-ci-job" +description: "You can enable continuous integration (CI) to test every single change prior to deploying the code to production just like in a software development workflow." --- ## Overview -dbt Cloud makes it easy to test every single code change you make prior to deploying that new logic into production. Once you've connected your [GitHub account](cloud-installing-the-github-application), [GitLab account](connecting-gitlab), or [Azure DevOps account](connecting-azure-devops), you can configure jobs to run when new pull requests are opened against your dbt repo. +dbt Cloud makes it easy to test every single code change you make prior to deploying that new logic into production. Once you've connected your [GitHub account](/docs/collaborate/git/connect-github), [GitLab account](/docs/collaborate/git/connect-gitlab), or [Azure DevOps account](/docs/collaborate/git/connect-azure-devops), you can configure jobs to run when new pull requests are opened against your dbt repo. -dbt Cloud will build the models affected by the new pull request code change in a temp schema, which acts as a quasi-staging environment, and will also run the tests that you've written for these models as a check. When the CI job completes, the run status will be shown directly in the pull request. This makes it possible to deploy new code to production with confidence. +dbt Cloud will build the models affected by the new pull request code change in a temp schema, which acts as a quasi-staging environment, and will also run the tests that you've written for these models as a check. When the continuous integration (CI) job completes, the run status will be shown directly in the pull request. This makes it possible to deploy new code to production with confidence. :::info Draft Pull Requests @@ -23,11 +23,11 @@ GitLab Webhooks are available to only GitLab users who have a paid or self-hoste ::: :::info Common Errors -If you previously configured your dbt project by providing a generic git URL that clones using SSH, you need to [reconfigure the project](cloud-enabling-continuous-integration#reconnecting-your-dbt-project-to-use-dbt-clouds-native-integration-with-github-gitlab-or-azure-devops) to connect through dbt Cloud's native integration with GitHub, GitLab, or Azure DevOps instead. +If you previously configured your dbt project by providing a generic git URL that clones using SSH, you need to [reconfigure the project](/docs/deploy/cloud-ci-job#reconnecting-your-dbt-project-to-use-dbt-clouds-native-integration-with-github-gitlab-or-azure-devops) to connect through dbt Cloud's native integration with GitHub, GitLab, or Azure DevOps instead. ::: -## Understanding dbt Cloud Slim CI -When a [dbt Cloud CI job is set up](cloud-enabling-continuous-integration#configuring-a-dbt-cloud-ci-job), dbt Cloud will listen for webhooks from GitHub, GitLab, or Azure DevOps indicating that a new PR has been opened or updated with new commits. When one of these webhooks is received, dbt Cloud will enqueue a new run of the CI job. Crucially, this run will build into a temporary schema using the prefix `dbt_cloud_pr_`. This schema isolation acts as a quasi-staging environment, so that you can see the builds resulting from the code associated with the PR's commit sha. The unique schema name can be found in the run details for the given run, as shown below. +## Understanding dbt Cloud Slim CI +When a [dbt Cloud CI job is set up](/docs/deploy/cloud-ci-job#configuring-a-dbt-cloud-ci-job), dbt Cloud will listen for webhooks from GitHub, GitLab, or Azure DevOps indicating that a new PR has been opened or updated with new commits. When one of these webhooks is received, dbt Cloud will enqueue a new run of the CI job. Crucially, this run will build into a temporary schema using the prefix `dbt_cloud_pr_`. This schema isolation acts as a quasi-staging environment, so that you can see the builds resulting from the code associated with the PR's commit sha. The unique schema name can be found in the run details for the given run, as shown below. @@ -59,14 +59,14 @@ There are a few components that define a Slim CI job. #### Deferral and State Comparison -When creating a job in dbt Cloud, you can set your execution settings to defer to a previous run state. Use the dropdown menu to select which *production* job you want to defer to. +When creating a job in dbt Cloud, you can set your execution settings to defer to a previous run state. Use the dropdown menu to select which *production* job you want to defer to. -When a job is selected, dbt Cloud will look at the artifacts from that job's most recent successful run. dbt will then use those artifacts to determine the set of new and modified resources. +When a job is selected, dbt Cloud will look at the artifacts from that job's most recent successful run. dbt will then use those artifacts to determine the set of new and modified resources. -In your job commands, you can signal to dbt to run only on these modified resources and their children by including the `state:modified+` argument. +In your job commands, you can signal to dbt to run only on these modified resources and their children by including the `state:modified+` argument. As example: @@ -79,7 +79,7 @@ Because dbt Cloud manages deferral and state environment variables, there is no To learn more about state comparison and deferral in dbt, read the docs on [state](understanding-state). -#### Using a webhook trigger +#### Using a webhook trigger In the **Triggers** section of the jobs settings, switch to the **Webhooks** tab, and then check the box next to **Run on Pull Requests?** as shown below. @@ -138,7 +138,7 @@ If your temporary PR schemas aren't dropping after a merge or close of the PR, i
You have overridden the generate_schema_name macro
-
To resolve this, change your macro so that the temporary PR schema name contains the default prefix and review the guidance below: +
To resolve this, change your macro so that the temporary PR schema name contains the default prefix and review the guidance below:

• ✅ Temporary PR schema name contains the prefix dbt_cloud_pr_ (like dbt_cloud_pr_123_456_marketing)

• ❌ Temporary PR schema name doesn't contain the prefix dbt_cloud_pr_ (like marketing).

@@ -163,9 +163,9 @@ Make the necessary changes to your project and double-check if the temporary PR ### Reconnecting your dbt project to use dbt Cloud's native integration with GitHub, GitLab, or Azure DevOps -If your dbt project relies the generic git clone method that clones using SSH and deploy keys to connect to your dbt repo, you need to disconnect your repo and reconnect it using the native GitHub, GitLab, or Azure DevOps integration in order to enable dbt Cloud Slim CI. +If your dbt project relies the generic git clone method that clones using SSH and deploy keys to connect to your dbt repo, you need to disconnect your repo and reconnect it using the native GitHub, GitLab, or Azure DevOps integration in order to enable dbt Cloud Slim CI. -First, make sure you have the [native GitHub authentication](cloud-installing-the-github-application), [native GitLab authentication](connecting-gitlab), or [native Azure DevOps authentication](connecting-azure-devops) set up depending on which git provider you use. After you have gone through those steps, head to **Account Settings**, select **Projects** and click on the project you'd like to reconnect through native GitHub, GitLab, or Azure DevOps auth. Then click on the repository link. +First, make sure you have the [native GitHub authentication](/docs/collaborate/git/connect-github), [native GitLab authentication](/docs/collaborate/git/connect-gitlab), or [native Azure DevOps authentication](/docs/collaborate/git/connect-azure-devops) set up depending on which git provider you use. After you have gone through those steps, head to **Account Settings**, select **Projects** and click on the project you'd like to reconnect through native GitHub, GitLab, or Azure DevOps auth. Then click on the repository link. Once you're in the repository page, click **Edit** and then click **Disconnect Repository** at the bottom. @@ -200,4 +200,3 @@ fatal: reference is not a tree: e845be54e6dc72342d5a8f814c8b3316ee220312 ``` Double-check that your PR isn't trying to merge using a commit that belongs to a fork of the repository attached to your dbt project. - diff --git a/website/docs/docs/dbt-cloud/using-dbt-cloud/cloud-dashboard-status-tiles.md b/website/docs/docs/deploy/dashboard-status-tiles.md similarity index 87% rename from website/docs/docs/dbt-cloud/using-dbt-cloud/cloud-dashboard-status-tiles.md rename to website/docs/docs/deploy/dashboard-status-tiles.md index 564305834ec..e02c9b421ec 100644 --- a/website/docs/docs/dbt-cloud/using-dbt-cloud/cloud-dashboard-status-tiles.md +++ b/website/docs/docs/deploy/dashboard-status-tiles.md @@ -1,11 +1,11 @@ --- title: "Dashboard status tiles" -id: "cloud-dashboard-status-tiles" +id: "dashboard-status-tiles" description: "Embed Status Tiles in your dashboards to provide consumers with contextual information about the quality and freshness of data." --- ## Overview -In dbt Cloud, the [Metadata API](dbt-cloud/dbt-cloud-api/metadata/metadata-overview) can power Dashboard Status Tiles. A Dashboard Status Tile is placed on a dashboard (specifically: anywhere you can embed an iFrame) to give insight into the quality and freshness of the data feeding into that dashboard. This is done via dbt [exposures](building-a-dbt-project/exposures). +In dbt Cloud, the [Metadata API](dbt-cloud/dbt-cloud-api/metadata//docs/dbt-cloud-apis/metadata-api) can power Dashboard Status Tiles. A Dashboard Status Tile is placed on a dashboard (specifically: anywhere you can embed an iFrame) to give insight into the quality and freshness of the data feeding into that dashboard. This is done via dbt [exposures](/docs/build/exposures). ## Functionality The dashboard status tile looks like this: @@ -19,13 +19,13 @@ The data freshness check fails if any sources feeding into the exposure are stal Clicking into **see details** from the Dashboard Status Tile takes you to a landing page where you can learn more about the specific sources, models, and tests feeding into this exposure. ## Setup -First, be sure to enable [source freshness](dbt-cloud/using-dbt-cloud/cloud-snapshotting-source-freshness) in the job that generates this exposure. +First, be sure to enable [source freshness](dbt-cloud/using-dbt-cloud//docs/deploy/source-freshness) in the job that generates this exposure. In order to set up your dashboard status tile, here is what you need: 1. **Metadata Token.** You can learn how to set up a metadata only token [here](dbt-cloud/dbt-cloud-api/service-tokens). -2. **Exposure name.** You can learn more about how to set up exposures [here](building-a-dbt-project/exposures). +2. **Exposure name.** You can learn more about how to set up exposures [here](/docs/build/exposures). 3. **jobID.** Remember that you can select your jobId directly from the URL when looking at the relevant job in dbt Cloud. diff --git a/website/docs/docs/running-a-dbt-project/running-dbt-in-production.md b/website/docs/docs/deploy/deployment-overview.md similarity index 63% rename from website/docs/docs/running-a-dbt-project/running-dbt-in-production.md rename to website/docs/docs/deploy/deployment-overview.md index 9bcb57cdec7..04663d49b67 100644 --- a/website/docs/docs/running-a-dbt-project/running-dbt-in-production.md +++ b/website/docs/docs/deploy/deployment-overview.md @@ -1,32 +1,26 @@ --- -title: "About running dbt in production" -id: "running-dbt-in-production" +title: "About deployments" +id: "deployments" --- - -Running dbt in production means **setting up a system to run a dbt job on a schedule**, rather than running dbt commands manually from the command line. These production dbt jobs should create the tables and views that your business intelligence tools and end users query. Before continuing, make sure you understand dbt's approach to [managing environments](managing-environments). - -:::info dbt commands in production - -We've written a guide for the dbt commands we run in production, over on [Discourse](https://discourse.getdbt.com/t/what-are-the-dbt-commands-you-run-in-your-production-deployment-of-dbt/366). - -::: +Running dbt in production means setting up a system to run a _dbt job on a schedule_, rather than running dbt commands manually from the command line. Your production dbt jobs should create the tables and views that your business intelligence tools and end users query. Before continuing, make sure you understand dbt's approach to [managing environments](/docs/collaborate/environments). In addition to setting up a schedule, there are other considerations when setting up dbt to run in production: -* The complexity involved in creating a new dbt job, or editing an existing one. -* Setting up notifications if a step within your job returns an error code (e.g. a model cannot be built, or a test fails). +* The complexity involved in creating a new dbt job or editing an existing one. +* Setting up notifications if a step within your job returns an error code (for example, a model can't be built or a test fails). * Accessing logs to help debug any issues. -* Pulling the latest version of your git repo before running dbt (i.e. continuous deployment). -* Running your dbt project before merging code into master (i.e. continuous integration). +* Pulling the latest version of your git repo before running dbt (continuous deployment). +* Running your dbt project before merging code into master (continuous integration). * Allowing access for team members that need to collaborate on your dbt project. - -## Ways to run dbt in production -If you don't want to run dbt commands manually on the command line, you can use dbt Cloud, Airflow, Prefect, Dagster, automation server, or Cron to run dbt jobs on a schedule. -### dbt Cloud +## Run dbt in production + +If you want to run dbt jobs on a schedule, you can use tools such as dbt Cloud, Airflow, Prefect, Dagster, automation server, or Cron. + +## dbt Cloud -We've built [dbt Cloud](https://www.getdbt.com/signup/) to empower data teams to easily run dbt in production. If you're interested in trying out dbt Cloud, you can [sign up for an account](https://cloud.getdbt.com/signup/). +We've built dbt Cloud to empower data teams to easily run dbt in production. If you're interested in trying out dbt Cloud, you can [sign up for an account](https://cloud.getdbt.com/signup/). dbt Cloud enables you to: - run your jobs on a schedule @@ -34,7 +28,16 @@ dbt Cloud enables you to: - configure error notifications - render your project's documentation -### Airflow +In general, the dbt Cloud application deployment models fall into two categories: **Multi Tenant** and **Single Tenant**. These deployments are hosted on infrastructure managed by dbt Labs. Both models leverage AWS infrastructure as described in the [Architecture](/docs/deploy/architecture) section. + +For more information on these deployment models, refer to: + +- [Multi Tenant](/docs/deploy/multi-tenant) +- [Single Tenant](/docs/deploy/single-tenant) + +If you’re interested in learning more about an Enterprise plan, please [contact us](mailto:sales@getdbt.com). + +## Airflow If your organization is using [Airflow](https://airflow.apache.org/), there are a number of ways you can run your dbt jobs, including: @@ -47,7 +50,7 @@ If your organization is using [Airflow](https://airflow.apache.org/), there are For more details on both of these methods, including example implementations, check out [this guide](https://www.astronomer.io/guides/airflow-dbt). -### Prefect +## Prefect If your organization is using [Prefect](https://www.prefect.io), use the [DbtShellTask](https://docs.prefect.io/api/latest/tasks/dbt.html#dbtshelltask) to schedule, execute and monitor your dbt runs. @@ -55,14 +58,18 @@ Alternatively, you can use the supported [ShellTask](https://docs.prefect.io/api You can also trigger dbt Cloud jobs with the [DbtCloudRunJob](https://docs.prefect.io/api/latest/tasks/dbt.html#dbtcloudrunjob) task. Running this task will generate a markdown artifact viewable in the Prefect UI. The artifact will contain links to the dbt artifacts generate as a result of the job run. -### Dagster +## Dagster If your organization is using [Dagster](https://dagster.io/), you can use the [dagster_dbt](https://docs.dagster.io/_apidocs/libraries/dagster-dbt) library to integrate dbt commands into your pipelines. This library supports the execution of dbt through dbt Cloud, dbt CLI and the dbt RPC server. Running dbt from Dagster automatically aggregates metadata about your dbt runs. Check out the [example pipeline](https://dagster.io/blog/dagster-dbt) for details. -### Automation servers +## Automation servers Automation servers, like CodeDeploy, GitLab CI/CD ([video](https://youtu.be/-XBIIY2pFpc?t=1301)), Bamboo and Jenkins, can be used to schedule bash commands for dbt. They also provide a UI to view logging to the command line, and integrate with your git repository. -### Cron +## Cron Cron is a decent way to schedule bash commands. However, while it may seem like an easy route to schedule a job, writing code to take care of all of the additional features associated with a production deployment often makes this route more complex compared to other options listed here. + +## Related docs +- [What are the dbt commands you run in your production deployment of dbt?](https://discourse.getdbt.com/t/what-are-the-dbt-commands-you-run-in-your-production-deployment-of-dbt/366) +>>>>>>> next diff --git a/website/docs/docs/dbt-cloud/using-dbt-cloud/cloud-notifications.md b/website/docs/docs/deploy/job-notifications.md similarity index 95% rename from website/docs/docs/dbt-cloud/using-dbt-cloud/cloud-notifications.md rename to website/docs/docs/deploy/job-notifications.md index b243a0de260..f6efb0223ed 100644 --- a/website/docs/docs/dbt-cloud/using-dbt-cloud/cloud-notifications.md +++ b/website/docs/docs/deploy/job-notifications.md @@ -1,5 +1,6 @@ --- -title: "Configuring notifications" +title: "Job notifications" +id: "job-notifications" description: "Set up notifications in dbt Cloud to receive Email or Slack alerts for job run status." --- @@ -10,7 +11,7 @@ Setting up notifications in dbt Cloud will allow you to receive alerts via Email ### Email There are two options for setting up email notifications. As a **user**, you can set up email notifications for yourself under your Profile. As an **admin**, you can set up notifications on behalf of your team members. - + 1. Click the gear in the top right and select **Notification settings**. 2. **As a user:** Select **Edit** and select the type of Notification (Succeeds, Fails, or Is Cancelled) for each Job for which you would like to be notified, or diff --git a/website/docs/docs/dbt-cloud/using-dbt-cloud/cloud-using-a-custom-cron-schedule.md b/website/docs/docs/deploy/job-triggers.md similarity index 92% rename from website/docs/docs/dbt-cloud/using-dbt-cloud/cloud-using-a-custom-cron-schedule.md rename to website/docs/docs/deploy/job-triggers.md index a0883b5e8cf..bf6f6ac06d5 100644 --- a/website/docs/docs/dbt-cloud/using-dbt-cloud/cloud-using-a-custom-cron-schedule.md +++ b/website/docs/docs/deploy/job-triggers.md @@ -1,6 +1,6 @@ --- -title: "Setting custom cron schedules" -id: "cloud-using-a-custom-cron-schedule" +title: "Job triggers" +id: "job-triggers" description: "You can use cron syntax to specify when you want to run a job." --- @@ -21,7 +21,7 @@ If you need help coming up with the right cron syntax, we recommend using a tool A custom cron schedule can be specified in the Job Settings page when you edit a job: -1. Select a job. +1. Select a job. 2. Click **Settings**. 3. Click **Edit**. 4. In the Triggers section, activate the **Run on schedule** option. diff --git a/website/docs/docs/dbt-cloud/deployments/multi-tenant.md b/website/docs/docs/deploy/multi-tenant.md similarity index 93% rename from website/docs/docs/dbt-cloud/deployments/multi-tenant.md rename to website/docs/docs/deploy/multi-tenant.md index 89a94c41418..22bcc5add1b 100644 --- a/website/docs/docs/dbt-cloud/deployments/multi-tenant.md +++ b/website/docs/docs/deploy/multi-tenant.md @@ -1,6 +1,6 @@ --- -id: multi-tenant-deployment -title: Multi Tenant (SaaS) +title: Multi tenant +id: multi-tenant --- The Multi Tenant (SaaS) deployment environment refers to the SaaS dbt Cloud application hosted by dbt Labs. This is the most commonly used deployment and is completely managed and maintained by dbt Labs, the makers of dbt. As a SaaS product, a user can quickly [create an account](https://www.getdbt.com/signup/) and get started using the product. The deployment is hosted in AWS and will always contain the latest software updates and bug fixes. diff --git a/website/docs/docs/deploy/regions.md b/website/docs/docs/deploy/regions.md new file mode 100644 index 00000000000..004ed9c70aa --- /dev/null +++ b/website/docs/docs/deploy/regions.md @@ -0,0 +1,19 @@ +--- +title: "Regions" +id: "regions" +description: "Available regions" +--- + +dbt Cloud is hosted in the multiple regions and will always connect to your data platform from the below IP addresses. Be sure to allow traffic from these IPs in your firewall, and include them in any database grants. + +[dbt Cloud Enterprise](https://www.getdbt.com/pricing/) plans can choose to have their account hosted in any of the below regions. Organizations **must** choose a single region per dbt Cloud account. If you need to run dbt Cloud in multiple regions, we recommend using multiple dbt Cloud accounts. + + +| Region | Location | Access URL | IP addresses | Developer plan | Team plan | Enterprise plan | +|--------|----------|------------|--------------|-----------------|------------|------------------| +| North America | us-east-1 (N. Virginia) | cloud.getdbt.com | 52.45.144.63
54.81.134.249
52.22.161.231 | ✅ | ✅ | ✅ | +| EMEA | eu-central-1 (Frankfurt) | emea.dbt.com | 3.123.45.39
3.126.140.248
3.72.153.148 | ❌ | ❌ | ✅ | +| Virtual Private dbt | Customized | Customized | Ask [Support](/guides/legacy/getting-help#dbt-cloud-support) for your IPs | ❌ | ❌ | ✅ | + + + diff --git a/website/docs/docs/dbt-cloud/deployments/single-tenant.md b/website/docs/docs/deploy/single-tenant.md similarity index 96% rename from website/docs/docs/dbt-cloud/deployments/single-tenant.md rename to website/docs/docs/deploy/single-tenant.md index 92945c50eaf..7ed1ddac904 100644 --- a/website/docs/docs/dbt-cloud/deployments/single-tenant.md +++ b/website/docs/docs/deploy/single-tenant.md @@ -1,6 +1,6 @@ --- -id: single-tenant-deployment -title: Single Tenant +title: Single tenant +id: single-tenant --- The Single Tenant deployment environment provides a hosted alternative to the Multi Tenant (SaaS) dbt Cloud environment. While still managed and maintained by dbt Labs, the Single Tenant environment provides dedicated infrastructure with one or more instances of dbt Cloud that can only be accessed by a single customer. This is accomplished by spinning up all the necessary infrastructure with a re-usable Infrastructure as Code (IaC) deployment built with [Terraform](https://www.terraform.io/). The Single Tenant infrastructure lives in a dedicated AWS account and can be customized with certain configurations such as Firewall rules to limit ingress traffic or hosting in a specific AWS Region. diff --git a/website/docs/docs/dbt-cloud/using-dbt-cloud/cloud-snapshotting-source-freshness.md b/website/docs/docs/deploy/source-freshness.md similarity index 87% rename from website/docs/docs/dbt-cloud/using-dbt-cloud/cloud-snapshotting-source-freshness.md rename to website/docs/docs/deploy/source-freshness.md index d314b570d2b..5056e258eda 100644 --- a/website/docs/docs/dbt-cloud/using-dbt-cloud/cloud-snapshotting-source-freshness.md +++ b/website/docs/docs/deploy/source-freshness.md @@ -1,18 +1,18 @@ --- title: "Source freshness" -id: "cloud-snapshotting-source-freshness" +id: "source-freshness" description: "Validate that data freshness meets expectations and alert if stale." --- ## Data Source Freshness -dbt Cloud provides a helpful interface around dbt's [source data freshness](using-sources#snapshotting-source-data-freshness) calculations. When a dbt Cloud job is configured to snapshot source data freshness, dbt Cloud will render a user interface showing you the state of the most recent snapshot. This interface is intended to help you determine if your source data freshness is meeting the SLAs that you've defined for your organization. +dbt Cloud provides a helpful interface around dbt's [source data freshness](/docs/build/sources#snapshotting-source-data-freshness) calculations. When a dbt Cloud job is configured to snapshot source data freshness, dbt Cloud will render a user interface showing you the state of the most recent snapshot. This interface is intended to help you determine if your source data freshness is meeting the SLAs that you've defined for your organization. ### Enabling source freshness snapshots -First, make sure to configure your sources to [snapshot freshness information](using-sources#snapshotting-source-data-freshness). +First, make sure to configure your sources to [snapshot freshness information](/docs/build/sources#snapshotting-source-data-freshness). diff --git a/website/docs/docs/running-a-dbt-project/using-the-cli.md b/website/docs/docs/get-started/about-the-cli.md similarity index 79% rename from website/docs/docs/running-a-dbt-project/using-the-cli.md rename to website/docs/docs/get-started/about-the-cli.md index a12c50cde40..cc3639d933f 100644 --- a/website/docs/docs/running-a-dbt-project/using-the-cli.md +++ b/website/docs/docs/get-started/about-the-cli.md @@ -1,5 +1,6 @@ --- -title: "Using the CLI" +title: "About the CLI" +id: "about-the-cli" --- dbt ships with a Command Line Interface (CLI) for running your dbt project. This way of running dbt a dbt project is free and open source. @@ -9,6 +10,8 @@ To use the CLI, your workflow generally looks like: * **Run your project from the command line:** * macOS ships with a default Terminal program, however you can also use iTerm or the command line prompt within a code editor to execute dbt commands +The CLI is also available for dbt Cloud. Additional components must be installed for the CLI to communicate via dbt Cloud APIs. For more information, visit the [dbt Cloud CLI GitHub repository](https://github.com/data-mie/dbt-cloud-cli) + :::info How we set up our computers for working on dbt projects We've written a [guide](https://discourse.getdbt.com/t/how-we-set-up-our-computers-for-working-on-dbt-projects/243) for our recommended setup when running dbt projects using the CLI. diff --git a/website/docs/docs/dbt-cloud/cloud-configuring-dbt-cloud/connecting-your-database.md b/website/docs/docs/get-started/connect-your-database.md similarity index 91% rename from website/docs/docs/dbt-cloud/cloud-configuring-dbt-cloud/connecting-your-database.md rename to website/docs/docs/get-started/connect-your-database.md index e10b2bd1e2c..f71b9cfdc92 100644 --- a/website/docs/docs/dbt-cloud/cloud-configuring-dbt-cloud/connecting-your-database.md +++ b/website/docs/docs/get-started/connect-your-database.md @@ -1,30 +1,23 @@ --- -title: "Connecting your database" -id: "connecting-your-database" +title: "Connect your database" +id: "connect-your-database" --- You can connect to your database in dbt Cloud by clicking the gear in the top right and then selecting **Account Settings**. From the Account Settings page, click **+ New Project**. ## IP Restrictions -dbt Cloud will always connect to your warehouse from the following IP addresses. -Be sure to allow traffic from these IPs in your firewall, and include them in -any database grants. - -| Region/Deployment | IP Addresses | -| ------ | ----------- | -| US (cloud.getdbt.com) | 52.45.144.63
54.81.134.249
52.22.161.231 | -| EMEA (emea.dbt.com) | 3.123.45.39
3.126.140.248
3.72.153.148 | -| Virtual Private dbt | Ask [Support](https://docs.getdbt.com/guides/legacy/getting-help#dbt-cloud-support) for your IPs | +dbt Cloud will always connect to your data platform from the IP addresses specified in the [Regions](/docs/deploy/regions) page +Be sure to allow traffic from these IPs in your firewall, and include them in any database grants. -- November 2020 — add the IPs `54.81.134.249` and `52.22.161.231` +- November 2020 — add the IPs `54.81.134.249` and `52.22.161.231` - September 2022 — Add EMEA IPs -Allowing these IP addresses only enables the connection to your . However, you might want to send API requests from your restricted network to the dbt Cloud API. For example, you could use the API to send a POST request that [triggers a job to run](https://docs.getdbt.com/dbt-cloud/api-v2#operation/triggerRun). Using the dbt Cloud API requires that you allow the `cloud.getdbt.com` subdomain. For more on the dbt Cloud architecture, see "[Deployment architecture](deployment-architecture)." +Allowing these IP addresses only enables the connection to your . However, you might want to send API requests from your restricted network to the dbt Cloud API. For example, you could use the API to send a POST request that [triggers a job to run](https://docs.getdbt.com/dbt-cloud/api-v2#operation/triggerRun). Using the dbt Cloud API requires that you allow the `cloud.getdbt.com` subdomain. For more on the dbt Cloud architecture, see "[Deployment architecture](/docs/deploy/architecture)." ## Connecting to Postgres, Redshift, and AlloyDB @@ -52,7 +45,7 @@ The following fields are required when creating a Snowflake connection: | Field | Description | Examples | | ----- | ----------- | -------- | -| Account | The Snowflake account to connect to. Take a look [here](snowflake-profile#account) to determine what the account field should look like based on your region.| | +| Account | The Snowflake account to connect to. Take a look [here](/reference/warehouse-setups/snowflake-setup#account) to determine what the account field should look like based on your region.| | | Role | A mandatory field indicating what role should be assumed after connecting to Snowflake | `transformer` | | Database | The logical database to connect to and run queries against. | `analytics` | | Warehouse | The virtual warehouse to use for running queries. | `transforming` | @@ -105,7 +98,7 @@ In order to successfully fill in the Private Key field, you **must** include the The OAuth auth method permits dbt Cloud to run development queries on behalf of a Snowflake user without the configuration of Snowflake password in dbt Cloud. For -more information on configuring a Snowflake OAuth connection in dbt Cloud, please see [the docs on setting up Snowflake OAuth](setting-up-enterprise-snowflake-oauth). +more information on configuring a Snowflake OAuth connection in dbt Cloud, please see [the docs on setting up Snowflake OAuth](/docs/collaborate/manage-access/set-up-snowflake-oauth). ## Connecting to BigQuery @@ -156,7 +149,7 @@ As an end user, if your organization has set up BigQuery OAuth, you can link a p ### ODBC dbt Cloud supports connecting to Databricks using -[a Cluster](https://docs.databricks.com/clusters/index.html) or +[a Cluster](https://docs.databricks.com/clusters/index.html) or [a SQL Endpoint](https://docs.databricks.com/sql/admin/sql-endpoints.html). Depending on how you connect to Databricks, either one of the `Cluster` or `Endpoint` configurations must be provided, but setting _both_ values is not diff --git a/website/docs/dbt-cli/configure-your-profile.md b/website/docs/docs/get-started/connection-profiles.md similarity index 98% rename from website/docs/dbt-cli/configure-your-profile.md rename to website/docs/docs/get-started/connection-profiles.md index 1f025fe13a8..b1614a0deeb 100644 --- a/website/docs/dbt-cli/configure-your-profile.md +++ b/website/docs/docs/get-started/connection-profiles.md @@ -1,5 +1,6 @@ --- -title: "Configuring your profile" +title: "Connection profiles" +id: "connection-profiles" description: "Configure your profile using the command line." --- @@ -96,7 +97,7 @@ Use the [debug](debug) command to check whether you can successfully connect to ## Understanding targets in profiles -dbt supports multiple targets within one profile to encourage the use of separate development and production environments as discussed in [Managing Environments](managing-environments). +dbt supports multiple targets within one profile to encourage the use of separate development and production environments as discussed in [Managing Environments](/docs/collaborate/environments). A typical profile for an analyst using dbt locally will have a target named `dev`, and have this set as the default. @@ -136,7 +137,7 @@ In development, a pattern we’ve found to work well is to name the schema in yo Note that there’s no need to create your target schema beforehand – dbt will check if the schema already exists when it runs, and create it if it doesn’t. -While the target schema represents the default schema that dbt will use, it may make sense to split your models into separate schemas, which can be done by using [custom schemas](using-custom-schemas). +While the target schema represents the default schema that dbt will use, it may make sense to split your models into separate schemas, which can be done by using [custom schemas](/docs/build/custom-schemas). ## Understanding threads diff --git a/website/docs/docs/get-started/dbt-cloud-features.md b/website/docs/docs/get-started/dbt-cloud-features.md new file mode 100644 index 00000000000..0211dbd2790 --- /dev/null +++ b/website/docs/docs/get-started/dbt-cloud-features.md @@ -0,0 +1,81 @@ +--- +title: "dbt Cloud features" +id: "dbt-cloud-features" +--- + + +:::info Join our Cloud IDE beta + +Learn about what you can do with our [Cloud IDE beta](/docs/docs/get-started/develop-in-the-cloud#develop-in-the-cloud-ide-beta). Please [submit your expression of interest](https://docs.google.com/forms/d/e/1FAIpQLSdlU65gqTZPyGAUc16SkxqTc50NO9vdq_KGx1Mjm_4FB_97FA/viewform) to join our Cloud IDE beta group. + +::: + +The dbt Cloud [integrated development environment (IDE)](/docs/get-started/develop-in-the-cloud) allows you to build, test, run, and version control your dbt projects directly from your browser. The IDE is the fastest and most reliable way to deploy dbt, and provides a real-time editing and execution environment for your dbt project — no command line required. Anyone can use the IDE, from new dbt developers to seasoned practitioners. + +With the Cloud IDE, you can: + +- Write modular SQL models with select statements and the [ref()](/reference/dbt-jinja-functions/ref). +- Compile dbt code into SQL and execute it against your database directly. +- Test every model before deploying them to production. +- Generate and view documentation of your dbt project. +- Leverage [git and version-control your code](/docs/collaborate/git/version-control-basics) from your browser with a couple of clicks. +- Visualize a directed acyclic graph (DAG), [and more](/docs/get-started/dbt-cloud-tips) +- Use dark mode when you develop in the Cloud IDE. + + +### IDE features +The dbt Cloud IDE includes features that make it easier for you to develop, build, compile, run, and test your data models. Check out some of the features below to learn more: + +**Find and replace** + +Press Command-F or Ctrl-F to open the find and replace bar in the upper right corner of the current file in the IDE. The IDE highlights your search results in the current file and code outline. You can use the up and down arrows to see the match highlighted in the current file when there are multiple matches. To replace the text with something else, use the left arrow. + +**Search across files** + +You can quickly search over all files in the IDE on your current project. To search, open the search bar by pressing Command-O or Ctrl-O to find text across all files in your current project. and write your file name. You can view the results under the search text, which are grouped into files containing the match. You can click on the results to view it in the IDE. + +**Keyboard shortcuts** + +There are default keyboard shortcuts that can help make development more productive and easier for everyone. Press Fn-F1 to view a list of all of them. + +**File explorer** + +The File explorer on the left side of the IDE allows you to organize your project and manage your files and folders. Click the three dot menu associated with the file or folder to create, rename, and delete it. + +### Features available in the Cloud IDE beta + +**Format files** + +Format your files with a click of a button, powered by [sqlfmt](http://sqlfmt.com/). + +**File state indicators** + +We have added file state indicators to make it clear when changes or actions have been made. The indicators M, U, and • appear to the right of your file or folder name and indicate the actions performed: + * Unsaved (•) — The IDE detects unsaved changes to your file/folder + * Modification (M) — The IDE detects a modification of existing files/folders have saved changes file or folder + * Untracked (U) — The IDE detects changes made to new files or renamed files + +**Build, test, and run code** + +Build, test, and run your project with a click of a button, or using the Cloud IDE command bar. + +**Drag and drop** + +You can also drag and drop files located in the file explorer. Use the file breadcrumb on the top of the IDE for quick, linear navigation. You can access adjacent files in the same file by right clicking on the breadcrumb file. + +**Organize tabs** + +You can move your tabs around to reorganize your work in the IDE. You can also right click on a tab to view and select a list of actions to take. + +**Multiple selections** + +You can make multiple selections for quick and simultaneous edits. The below commands are a common way to add more cursors and allow you to insert cursors below or above with ease. + + * Option-Command-Down arrow + * Option-Command-Up arrow + * Press Option and click on an area + +## Related docs +- [dbt Cloud tips](/docs/get-started/dbt-cloud-tips) +- [Develop in the Cloud](docs/get-started/develop-in-the-cloud) +- [Guides](/docs/get-started/getting-started/overview) diff --git a/website/docs/docs/get-started/dbt-cloud-tips.md b/website/docs/docs/get-started/dbt-cloud-tips.md new file mode 100644 index 00000000000..f341311c799 --- /dev/null +++ b/website/docs/docs/get-started/dbt-cloud-tips.md @@ -0,0 +1,75 @@ +--- +title: "dbt Cloud tips" +id: dbt-cloud-tips +description: "Check out any dbt Cloud and IDE-related tips." +sidebar_label: "dbt Cloud tips" +--- + +# dbt Cloud tips + +The Cloud IDE is fully equipped with keyboard shortcuts, features, and development tips to help you to work like a dbt Cloud power user! Use this Cloud IDE cheat sheet to help you save time and quickly reference. + +## Most popular + +**Search across files** + +You can quickly search over all files in the IDE on your current project. To search, open the search bar by pressing Command-O to find text across all files in your current project and write your filename. You can view the results under the search text, which are grouped into files containing the match. You can click on the results to view them in the IDE. + +**Command bar and status** + +You can run commands from the command bar at the bottom of the IDE. Use the [rich model selection syntax](/docs/reference/node-selection/syntax) to [run dbt commands](/docs/reference/dbt-commands) directly within dbt Cloud. You can also view the history, status, and logs of previous runs by clicking **Runs**. + +The status icon on the lower right corner of the IDE gives you an indicator of the health of your project. You can identify errors by clicking on the status icon for more details or by clicking **Restart the IDE**. + +**Find and replace** + +Press Command-F or Control-F to open the find-and-replace bar in the upper right corner of the current file in the IDE. The IDE highlights your search results in the current file and code outline. You can use the up and down arrows to see the match highlighted in the current file when there are multiple matches. To replace the text with something else, use the left arrow. + +**DAG in the IDE** + +Double-click a node in the directed acyclic graph (DAG) to open that file in a new tab. Click **Expand** on the upper right side of the DAG and use node selection syntax (`select` or `exclude`) to view a subset of your DAG. + +## IDE Keyboard shortcuts + +There are default keyboard shortcuts that can help make development more productive and easier for everyone. + +- Command-O or Control-O to select a file to open +- Press Fn-F1 to view a list of the other editor shortcuts +- Command-Enter or Control-Enter to Preview +- Command-Shift-Enter or Control-Shift-Enter to Compile + +## Package tips + +- Use the [dbt_codegen](https://hub.getdbt.com/dbt-labs/codegen/latest/) package to help you generate YML files for your models and sources and SQL files for your staging models. +- The [dbt_utils](https://hub.getdbt.com/dbt-labs/dbt_utils/latest/) package contains macros useful for daily development. For example, `date_spine` generates a table with all dates between the ones provided as parameters. +- The [dbt_project_evaluator](https://hub.getdbt.com/dbt-labs/dbt_project_evaluator/latest) package compares your dbt project against a list of our best practices and provides suggestions and guidelines on how to update your models. +- The [dbt_expectations](https://hub.getdbt.com/calogica/dbt_expectations/latest) package contains many tests beyond those built into dbt Core. +- The [dbt_audit_helper](https://hub.getdbt.com/#:~:text=adwords-,audit_helper,-codegen) package lets you compare the output of 2 queries. Use it when refactoring existing logic to ensure that the new results are identical. +- The [dbt_artifacts](https://hub.getdbt.com/brooklyn-data/dbt_artifacts/latest) package saves information about your dbt runs directly to your data platform so that you can track the performance of models over time. +- The [dbt_meta_testing](https://hub.getdbt.com/tnightengale/dbt_meta_testing/latest) package checks that your dbt project is sufficiently tested and documented. + +## Advanced tips + +- Use your folder structure as your primary selector method. `dbt build marts.marketing` is simpler and more resilient than relying on tagging every model. +- Think about jobs in terms of build cadences and SLAs. Run models that have hourly, daily, or weekly build cadences together. +- Use the [where config](/docs/reference/resource-configs/where) for tests to test an assertion on a subset of records. +- [store_failures](/docs/reference/resource-configs/store_failures) lets you examine records that cause tests to fail, so you can either repair the data or change the test as needed. +- Use [severity](/docs/reference/resource-configs/severity) thresholds to set an acceptable number of failures for a test. +- Use [incremental_strategy](/docs/building-a-dbt-project/building-models/configuring-incremental-models#configuring-incremental-strategy) in your incremental model config to implement the most effective behavior depending on the volume of your data and reliability of your unique keys. +- Set `vars` in your `dbt_project.yml` to define global defaults for certain conditions, which you can then override using the `--vars` flag in your commands. +- Use [for loops](/docs/get-started/learning-more/using-jinja#use-a-for-loop-in-models-for-repeated-sql) in Jinja to [DRY](/docs.getdbt.com/terms/dry) up repetitive logic, such as selecting a series of columns that all require the same transformations and naming patterns to be applied. +- Instead of relying on post-hooks, use the [grants config](/docs/reference/resource-configs/grants) to apply permission grants in the warehouse resiliently. +- Define [source-freshness](/docs/building-a-dbt-project/using-sources#snapshotting-source-data-freshness) thresholds on your sources to avoid running transformations on data that has already been processed. +- Use the `+` operator on the left of a model `dbt build +model_name` to run a model and all of its upstream dependencies. Use the `+` operator on the right of the model `dbt build model_name+` to run a model and everything downstream that depends on it. +- Use `dir_name` to run all models in a package or directory. +- Use the `@` operator on the left of a model in a non-state-aware CI setup to test it. This operator runs all of a selection’s parents and children, and also runs the parents of its children, which in a fresh CI schema will likely not exist yet. +- Use the [--exclude flag](/docs/reference/node-selection/exclude) to remove a subset of models out of a selection. +- Use [state and deferral](/docs/dbt-cloud/using-dbt-cloud/cloud-enabling-continuous-integration#deferral-and-state-comparison) to create a slim CI setup. +- Use the [--full-refresh](/docs/reference/commands/run#refresh-incremental-models) flag to rebuild an incremental model from scratch. +- Use [seeds](/docs/building-a-dbt-project/seeds) to create manual lookup tables, like zip codes to states or marketing UTMs to campaigns. `dbt seed` will build these from CSVs into your warehouse and make them `ref` able in your models. +- Use [target.name](/docs/build/custom-schemas#an-alternative-pattern-for-generating-schema-names) to pivot logic based on what environment you’re using. For example, to build into a single development schema while developing, but use multiple schemas in production. + +## Related docs + +- [Guides](/docs/get-started/getting-started/overview) +- [Develop in the Cloud](/docs/get-started/develop-in-the-cloud) diff --git a/website/docs/docs/get-started/develop-in-the-cloud.md b/website/docs/docs/get-started/develop-in-the-cloud.md new file mode 100644 index 00000000000..97ae4027b2e --- /dev/null +++ b/website/docs/docs/get-started/develop-in-the-cloud.md @@ -0,0 +1,250 @@ +--- +title: "Develop in the Cloud" +id: develop-in-the-cloud +description: "Develop, test, run, and build in the Cloud IDE." +sidebar_label: "Develop in the Cloud" +--- + +The dbt Cloud integrated development environment (IDE) is a single interface for building, testing, running, and version-controlling dbt projects from your browser. With the Cloud IDE, you can compile dbt code into SQL and run it against your database directly. + +The IDE leverages the open-source [dbt-rpc](/docs/reference/commands/rpc) plugin to recompile only the changes made in your project. + +## Prerequisites + +To develop in the Cloud IDE, make sure you have the following: + +- Your dbt project must be compatible with dbt version 0.15.0 or higher. The dbt IDE is powered by the [dbt-rpc](/docs/reference/commands/rpc) which was overhauled in dbt v0.15.0 +- You must have a [dbt Cloud account](https://cloud.getdbt.com/) and [Developer seat license](/docs/dbt-cloud/access-control/cloud-seats-and-users) +- You must have a git repository set up and your git provider must have `write` access enabled. See [Connecting your GitHub Account](/docs/dbt-cloud/cloud-configuring-dbt-cloud/cloud-installing-the-github-application) and [Importing a project by git URL](/docs/dbt-cloud/cloud-configuring-dbt-cloud/cloud-import-a-project-by-git-url) for detailed setup instructions +- Your dbt project must be connected to a [data platform](/docs/dbt-cloud/cloud-configuring-dbt-cloud/connecting-your-database) +- You must have a [**development environment** and **development credentials**](/docs/get-started/develop-in-the-cloud#set-up-and-access-the-cloud-ide) set up +- The environment must be on dbt version 1.0 or higher + + +## Set up and access the Cloud IDE + +:::info📌 + +New to dbt? Check out our [Getting Started guide](/docs/get-started/getting-started/overview) to build your first dbt project in the Cloud IDE! + +::: + +In order to start experiencing the great features of the Cloud IDE, you need to first set up your **Development environment** and **Development credentials.** + +If you’re new to dbt, you will automatically add this during the project setup. However, if you have an existing dbt Cloud account, you may need to create a development environment and credentials manually to use the Cloud IDE. + +Review the steps below to set up your development environment and credentials: + + +**Development environment** + +1. Create a development environment and choose **Deploy** and then **Environments** from the top left. Click **Create Environment**. + + + +2. Enter an environment name that would help you identify it among your other environments (for example, `Nate's Development Environment`). +3. Choose **Development** as the **Environment Type**. +4. You can also select which **dbt Version** to use at this time. For compatibility reasons, we recommend that you select the same dbt version that you plan to use in your deployment environment. +5. Click **Save** to finish creating your **Development environment**. + + + + + +**Developer credentials** + +The IDE uses developer credentials to connect to your data platform. These developer credentials should be specific to your user and they should *not* be super user credentials or the same credentials that you use for your production deployment of dbt. + +Follow the below steps to set up your developer credentials: + +1. Go to the [**Credentials**](https://cloud.getdbt.com/next/settings/profile#credentials) section. + +2. Select the relevant project in the list. + +3. Click **Edit** on the bottom right of the page + +4. Enter your developer credentials and then click **Save.** + +Great job, you should now be able to access the Cloud IDE by clicking **Develop** on the navigation to start developing! + + + +### Access the Cloud IDE + +Now that you've set up your development environment and credentails, you should be able to access the Cloud IDE: + +1. Log in with your [dbt Cloud account](https://cloud.getdbt.com/). If you don't have one, [sign up](https://www.getdbt.com/signup/) for an account for free. +2. Click **Develop** at the top of the page +3. Make sure you've already initialized your project +4. Start developing and familiarize yourself with the IDE! + + +## Build, compile, and run projects + +You can *build*, *compile*, *run* *, and test* dbt projects by using the command bar. The Cloud IDE will update in real-time when you run models, tests, seeds, and operations. + +If a model or test fails, you can review the logs to find and fix the issue. + +You can also use dbt's [rich model selection syntax](/docs.getdbt.com/reference/node-selection/syntax) to [run dbt commands](/docs/reference/dbt-commands) directly within dbt Cloud. + +## Build and view your project's docs + +The dbt Cloud IDE makes it possible to view documentation for your dbt project while your code is still in development. With this workflow, you can inspect and verify what your project's generated documentation will look like before your changes are released to production. + +To generate your project’s documentation (docs) in the IDE, run `dbt docs generate` in the command bar. This command generates the docs for your dbt project as it currently exists in development. + +After you generate a successful run, you can view your documentation for your dbt project in real time by clicking **View Docs** or the book icon on above the file tree. + +You can view the latest version of your documentation rendered in a new browser window, and inspect and verify what your project's documentation will look like before you deploy your changes to production. + + +## Develop in the Cloud IDE (beta) + +:::info Join our beta + + +If you’d like to try the dbt Cloud IDE beta, available for multi-tenant instances, please [sign up](https://docs.google.com/forms/d/e/1FAIpQLSdlU65gqTZPyGAUc16SkxqTc50NO9vdq_KGx1Mjm_4FB_97FA/viewform) to join the beta. To learn more about the beta features, you can read this section. + +::: + +### Prerequisites + +To develop in dbt Cloud IDE (beta), you need to meet these requirements: + +- Your dbt project must be compatible with dbt v0.15.0. The dbt IDE is powered by the [dbt-rpc](/reference/commands/rpc) which was overhauled in dbt v0.15.0 +- You must have a [Developer License](/docs/dbt-cloud/access-control/cloud-seats-and-users) +- - Your dbt project must be connected to a [data platform](/docs/dbt-cloud/cloud-configuring-dbt-cloud/connecting-your-database) +- You must have a [development environment and development credentials](#set-up-and-access-the-cloud-ide) set up +- The environment must be on dbt version 1.0 or higher +- Currently only multi-tenant instances of dbt Cloud can develop in the updated beta version of the Cloud IDE + * Single-tenant instances will soon be able to opt into this Beta release. +- Your dbt repository (in dbt Cloud) must have write access enabled + * See [Connecting your GitHub Account](/docs/dbt-cloud/cloud-configuring-dbt-cloud/cloud-installing-the-github-application) and [Importing a project by git URL](/docs/dbt-cloud/cloud-configuring-dbt-cloud/cloud-import-a-project-by-git-url) for detailed setup instructions + + +The dbt Cloud IDE beta brings the startup and interaction time for dbt project development down from minutes to seconds, includes reliable performance and delightful enhancements to help you develop more efficiently! + +### Start up and work retention + + + +
Start up process Work retention
+ +There are three start-up states when using or launching the Cloud IDE: + +- Creation start — This is the state where you are starting the IDE for the first time. You can also view this as a *cold start* (see below), and you can expect this state to take longer because the git repository is being cloned. +- Cold start — This is the process of starting a new develop session, which will be available for you for three hours. The environment automatically turns off three hours after the last activity with the rpc server. This includes compile, preview, or any dbt invocation, however, it *does not* include editing and saving a file. +- Hot start — This is the state of resuming an existing or active develop session within three hours of the last activity. + + + + + +The Cloud IDE needs explicit action to save your changes. There are three ways your work is stored: + +- Unsaved, local code — Any code you write is automatically available from your browser’s storage. You can see your changes but will lose them if you switch branches or browsers (another device or browser). +- Saved but uncommitted code — When you save a file, the data gets stored in your local storage (EFS storage). If you switch branches but don’t *commit* your saved changes, you will lose your changes. +- Committed code — This is stored in the branch with git provider and you are able to check out other (remote) branches. + + +
+ +### New Cloud IDE beta features + +#### Format + +You can format/preview/compile or build your dbt project, as well as see the DAG. The new **Format** button formats your file and is powered by [sqlfmt](http://sqlfmt.com/). + +#### Multiple selections + +You can make multiple selections for quick and simultaneous edits. The below commands are a common way to add more cursors and allow you to insert cursors below or above with ease. + +- Option-Command-Down arrow +- Option-Command-Up arrow +- Press Option and click on an area + + + +#### Drag and drop + +You can also drag and drop files located in the file explorer. Use the file breadcrumb on the top of the IDE for quick, linear navigation. You can access adjacent files in the same file by right clicking on the breadcrumb file. + + + +#### Organize tabs + +You can move your tabs around to reorganize your work in the IDE. You can also right click on a tab to view and select a list of actions to take. + + + +#### Run projects + +You can also build, run, and test dbt projects directly in the Cloud IDE with a click of a button, using the **Build** feature. You can also use dbt's [rich model selection syntax](reference/node-selection/syntax) to [run dbt commands](/reference/dbt-commands) directly within dbt Cloud. + +The IDE updates in real time as models, tests, seeds, and operations are run. If a model or test fails, you can review the logs to find and fix the issue. + + + +#### Lineage tab + +The visual in the Lineage tab adds more context to your dependencies and directional flow. + +You get to see how models are used as building blocks from left to right to transform your data from crude or normalized raw sources, into cleaned-up modular derived pieces, and finally into the final outputs on the far right of the DAG, ready to be used by the analyst in infinite combinations to present it in ways to help clients, customers, and organizations make better decisions. + +You can access files in the lineage tab by double clicking on a particular model. + +#### Command bar + status + +You can enter and run commands from the command bar at the bottom of the IDE. Use the [rich model selection syntax](reference/node-selection/syntax) to [run dbt commands](/reference/dbt-commands) directly within dbt Cloud. You can also view the history, status, and logs of previous runs by clicking **History**. + +The status icon on the lower right corner of the IDE gives you an indicator of the health of your project. You can identify errors by clicking on the status icon for more details or by clicking **Restart the IDE**. + +#### File state indicators + +The file state indicators to make it clear when changes or actions have been made. The indicators **M**, **U**, and **•** appear to the right of your file or folder name and indicate the actions performed: + +- Unsaved (•) — The IDE detects unsaved changes to your file/folder +- Modification (M) — The IDE detects a modification of existing files/folders have saved changes file or folder +- Untracked (U) — The IDE detects changes made to new files or renamed files + + +## Related docs + +- [What is dbt?](/docs/introduction#dbt-features) +- [dbt Learn courses](https://courses.getdbt.com/collections) +- [dbt Cloud features](/docs/get-started/dbt-cloud-features) +- [Version control basics](/docs/collaborate/git/version-control-basics) +- [dbt Commands](/docs/reference/dbt-commands) + + +## Related questions + +
+ Is there a cost to using the Cloud IDE? +
+
Not at all! You can use dbt Cloud when you sign up for the Free Developer plan, which comes with one developer seat. If you’d like to access more features or have more developer seats, you can upgrade your account to the Team or Enterprise plan. See dbt pricing plans for more details.
+
+
+
+ Can I be a contributor to dbt Cloud? +
+
Anyone can contribute to the dbt project. And whether it's a dbt package, a plugin, dbt-core, or this documentation site, contributing to the open source code that supports the dbt ecosystem is a great way to level yourself up as a developer, and give back to the community. See Contributing for details on what to expect when contributing to the dbt open source software (OSS).
+
+
+
+ What is the difference between developing on the Cloud IDE and on the CLI? +
+
There are two main ways to develop with dbt: using the web-based IDE in dbt Cloud or using the command-line interface (CLI) in dbt Core:

+ — + dbt Cloud IDE dbt Cloud is a web-based application that allows you to develop dbt projects with the IDE, includes a purpose-built scheduler, and provides an easier way to share your dbt documentation with your team. The IDE is a faster and more reliable way to deploy your dbt models and provides a real-time editing and execution environment for your dbt project.

+ — + dbt Core CLI The command line interface (CLI) uses dbt Core, an open-source software that’s freely available. You can build your dbt project in a code editor, like Jetbrains or VSCode, and run dbt commands from the command line. +
+
+
+
+ What type of support is provided with dbt Cloud? +
+
The global dbt Support team is available to help dbt Cloud users by email or in-product live chat. Developer and Team accounts offer 24x5 support, while Enterprise customers have priority access and options for custom coverage.

If you have project-related or modeling questions, review our Support page or dbt Community Slack to get help as well.
+
+
diff --git a/website/docs/dbt-cli/install/docker.md b/website/docs/docs/get-started/docker-install.md similarity index 93% rename from website/docs/dbt-cli/install/docker.md rename to website/docs/docs/get-started/docker-install.md index 9597ed3c56d..46b1cb22b5e 100644 --- a/website/docs/dbt-cli/install/docker.md +++ b/website/docs/docs/get-started/docker-install.md @@ -1,5 +1,5 @@ --- -title: "Use Docker to install dbt" +title: "Install with Docker" description: "You can use Docker to install dbt and adapter plugins from the command line." --- @@ -7,11 +7,11 @@ dbt Core and all adapter plugins maintained by dbt Labs are available as [Docker Using a prebuilt Docker image to install dbt Core in production has a few benefits: it already includes dbt-core, one or more database adapters, and pinned versions of all their dependencies. By contrast, `pip install dbt-core dbt-` takes longer to run, and will always install the latest compatible versions of every dependency. -You might also be able to use Docker to install and develop locally if you don't have a Python environment set up. Note that running dbt in this manner can be significantly slower if your operating system differs from the system that built the Docker image. If you're a frequent local developer, we recommend that you install dbt Core via [Homebrew](homebrew) or [pip](pip) instead. +You might also be able to use Docker to install and develop locally if you don't have a Python environment set up. Note that running dbt in this manner can be significantly slower if your operating system differs from the system that built the Docker image. If you're a frequent local developer, we recommend that you install dbt Core via [Homebrew](/docs/develop/homebrew-install) or [pip](/docs/develop/pip-install) instead. ### Prerequisites -* You've installed Docker. For more information, see the [Docker](https://docs.docker.com/) site. -* You understand which database adapter(s) you need. For more information, see [About dbt adapters](/dbt-cli/install/overview#about-dbt-adapters). +* You've installed Docker. For more information, see the [Docker](https://docs.docker.com/) site. +* You understand which database adapter(s) you need. For more information, see [About dbt adapters](/docs/get-started/installation#about-dbt-adapters). * You understand how dbt Core is versioned. For more information, see [About dbt Core versions](core-versions). * You have a general understanding of the dbt, dbt workflow, developing locally in the command line interface (CLI). For more information, see [About dbt](/docs/introduction#how-do-i-use-dbt). diff --git a/website/docs/guides/getting-started/learning-more/getting-started-dbt-core.md b/website/docs/docs/get-started/getting-started-dbt-core.md similarity index 92% rename from website/docs/guides/getting-started/learning-more/getting-started-dbt-core.md rename to website/docs/docs/get-started/getting-started-dbt-core.md index 32213e2c9b2..e552c7c54a5 100644 --- a/website/docs/guides/getting-started/learning-more/getting-started-dbt-core.md +++ b/website/docs/docs/get-started/getting-started-dbt-core.md @@ -2,16 +2,16 @@ title: "Getting started with dbt Core" id: getting-started-dbt-core description: "Connecting your warehouse to dbt Core using the CLI." -sidebar_label: "Getting started with dbt Core" +sidebar_label: "Getting started" --- -When you use dbt Core to work with dbt, you will be editing files locally using a code editor, and running projects using the dbt command line interface (dbt CLI). If you'd rather edit files and run projects using the web-based Integrated Development Environment (IDE), you should refer to [Getting set up in dbt Cloud](/guides/getting-started/getting-set-up). +When you use dbt Core to work with dbt, you will be editing files locally using a code editor, and running projects using the dbt command line interface (dbt CLI). If you'd rather edit files and run projects using the web-based Integrated Development Environment (IDE), you should refer to [Getting set up in dbt Cloud](/docs/get-started/getting-started/set-up-dbt-cloud). ## Prerequisites * To use the dbt CLI, it's important that you know some basics of the Terminal. In particular, you should understand `cd`, `ls` and `pwd` to navigate through the directory structure of your computer easily. -* Install dbt Core using the [installation instructions](/dbt-cli/install/overview) for your operating system. -* Complete [Setting up (in BigQuery)](/guides/getting-started/getting-set-up/setting-up-bigquery#setting-up) and [Loading data (BigQuery)](/guides/getting-started/getting-set-up/setting-up-bigquery#loading-data). +* Install dbt Core using the [installation instructions](/docs/get-started/installation) for your operating system. +* Complete [Setting up (in BigQuery)](/docs/get-started/getting-started/getting-set-up/setting-up-bigquery#setting-up) and [Loading data (BigQuery)](/docs/get-started/getting-started/getting-set-up/setting-up-bigquery#loading-data). * [Create a GitHub account](https://github.com/join) if you don't already have one. ## Create a starter project @@ -25,7 +25,7 @@ The following steps use [GitHub](https://github.com/) as the Git provider for th 1. [Create a new GitHub repository](https://github.com/new) named `dbt-tutorial`. 2. Select **Public** so the repository can be shared with others. You can always make it private later. 3. Leave the default values for all other settings. -4. Click **Create repository**. +4. Click **Create repository**. 5. Save the commands from "…or create a new repository on the command line" to use later in [Commit your changes](#commit-your-changes). ### Create a project @@ -117,7 +117,7 @@ When developing locally, dbt connects to your using ```terminal $ dbt debug - > Connection test: OK connection ok + > Connection test: OK connection ok ```
@@ -166,14 +166,14 @@ Commit your changes so that the repository contains the latest code. ## Build your first models -Now that you set up your sample project, you can get to the fun part — [building models](building-models)! You will take a sample query and turn it into a model in your dbt project. +Now that you set up your sample project, you can get to the fun part — [building models](/docs/build/sql-models)! You will take a sample query and turn it into a model in your dbt project. ### Checkout a new git branch Check out a new git branch to work on new code: 1. Create a new branch by using the `checkout` command and passing the `-b` flag: - + ```terminal $ git checkout -b add-customers-model > Switched to a new branch `add-customer-model` @@ -258,4 +258,4 @@ You need to commit the changes you made to the project so that the repository ha ## Schedule a job -We recommend using dbt Cloud to schedule a job. For more information about using dbt Core to schedule a job, see [dbt airflow](/blog/dbt-airflow-spiritual-alignment) blog post or [Running a dbt project](/docs/running-a-dbt-project/running-dbt-in-production). +We recommend using dbt Cloud to schedule a job. For more information about using dbt Core to schedule a job, see [dbt airflow](/blog/dbt-airflow-spiritual-alignment) blog post or [deployments](/docs/deploy/deployments). diff --git a/website/docs/guides/getting-started/add-a-seed.md b/website/docs/docs/get-started/getting-started/add-a-seed.md similarity index 100% rename from website/docs/guides/getting-started/add-a-seed.md rename to website/docs/docs/get-started/getting-started/add-a-seed.md diff --git a/website/docs/guides/getting-started/building-your-first-project.md b/website/docs/docs/get-started/getting-started/building-your-first-project.md similarity index 100% rename from website/docs/guides/getting-started/building-your-first-project.md rename to website/docs/docs/get-started/getting-started/building-your-first-project.md diff --git a/website/docs/guides/getting-started/building-your-first-project/build-your-first-models.md b/website/docs/docs/get-started/getting-started/building-your-first-project/build-your-first-models.md similarity index 86% rename from website/docs/guides/getting-started/building-your-first-project/build-your-first-models.md rename to website/docs/docs/get-started/getting-started/building-your-first-project/build-your-first-models.md index 9ccda2e6b3c..e344078d0eb 100644 --- a/website/docs/guides/getting-started/building-your-first-project/build-your-first-models.md +++ b/website/docs/docs/get-started/getting-started/building-your-first-project/build-your-first-models.md @@ -4,7 +4,7 @@ id: build-your-first-models description: "Now that you've set up the starter project, you can get to the fun part — building models!" --- -Now that you set up your sample project and had a successful run, you can get to the fun part — [building models](building-models)! You will take a sample query and turn it into a model in your dbt project. A model in dbt is a select statement. +Now that you set up your sample project and had a successful run, you can get to the fun part — [building models](/docs/build/sql-models)! You will take a sample query and turn it into a model in your dbt project. A model in dbt is a select statement. ## Checkout a new git branch @@ -53,6 +53,6 @@ In the future, you would connect your business intelligence (BI) tools to these ## Next steps -Once you build your first model, you're ready to [test and document your project](guides/getting-started/building-your-first-project/test-and-document-your-project). +Once you build your first model, you're ready to [test and document your project](/docs/get-started/getting-started/building-your-first-project/test-and-document-your-project). diff --git a/website/docs/guides/getting-started/building-your-first-project/schedule-a-job.md b/website/docs/docs/get-started/getting-started/building-your-first-project/schedule-a-job.md similarity index 91% rename from website/docs/guides/getting-started/building-your-first-project/schedule-a-job.md rename to website/docs/docs/get-started/getting-started/building-your-first-project/schedule-a-job.md index e9b172565c1..04839ebe8f1 100644 --- a/website/docs/guides/getting-started/building-your-first-project/schedule-a-job.md +++ b/website/docs/docs/get-started/getting-started/building-your-first-project/schedule-a-job.md @@ -58,8 +58,8 @@ You can improve your dbt skills with these fun exercises: * If you want a more in-depth learning experience, we recommend taking the [dbt Fundamentals on our dbt Learn online courses site](https://courses.getdbt.com/courses/fundamentals). -Here are some ways to [learn more](learning-more) essential dbt skills: +Here are some ways to learn more essential dbt skills: -* Learn how to use Jinja in your project by reading the [Jinja tutorial](using-jinja). -* Learn how to [connect to dbt Core using the CLI](getting-started-dbt-core). -* Refactor [legacy SQL to dbt SQL](refactoring-legacy-sql). +* Learn how to use Jinja in your project by reading the [Jinja tutorial](/docs/get-started/learning-more/using-jinja). +* Learn how to [connect to dbt Core using the CLI](/docs/get-started/getting-started-dbt-core). +* Refactor [legacy SQL to dbt SQL](/docs/get-started/learning-more/refactoring-legacy-sql). diff --git a/website/docs/guides/getting-started/building-your-first-project/test-and-document-your-project.md b/website/docs/docs/get-started/getting-started/building-your-first-project/test-and-document-your-project.md similarity index 87% rename from website/docs/guides/getting-started/building-your-first-project/test-and-document-your-project.md rename to website/docs/docs/get-started/getting-started/building-your-first-project/test-and-document-your-project.md index 016880e1601..db7fa7f3ec0 100644 --- a/website/docs/guides/getting-started/building-your-first-project/test-and-document-your-project.md +++ b/website/docs/docs/get-started/getting-started/building-your-first-project/test-and-document-your-project.md @@ -21,6 +21,6 @@ description: Let's test and document our models to build trust in our data. ## Next steps -Once you test and document your project, you're ready to [Schedule a job](guides/getting-started/building-your-first-project/schedule-a-job). +Once you test and document your project, you're ready to [Schedule a job](/docs/get-started/getting-started/building-your-first-project/schedule-a-job). diff --git a/website/docs/guides/getting-started/create-a-project.md b/website/docs/docs/get-started/getting-started/create-a-project.md similarity index 93% rename from website/docs/guides/getting-started/create-a-project.md rename to website/docs/docs/get-started/getting-started/create-a-project.md index 57df4d90b15..9ecd487d527 100644 --- a/website/docs/guides/getting-started/create-a-project.md +++ b/website/docs/docs/get-started/getting-started/create-a-project.md @@ -15,4 +15,4 @@ You can work with dbt in two ways: To use the CLI, it's important that you know some basics of your terminal. In particular, you should understand `cd`, `ls` and `pwd` to navigate through the directory structure of your computer easily. As such, if you are new to programming, we recommend using **dbt Cloud** for this guide. -If you wish to use the CLI, please follow the [installation instructions](/dbt-cli/install/overview) for your operating system. +If you wish to use the CLI, please follow the [installation instructions](/docs/get-started/installation) for your operating system. diff --git a/website/docs/docs/get-started/getting-started/getting-set-up.md b/website/docs/docs/get-started/getting-started/getting-set-up.md new file mode 100644 index 00000000000..3ef1731bc38 --- /dev/null +++ b/website/docs/docs/get-started/getting-started/getting-set-up.md @@ -0,0 +1,20 @@ +--- +title: About setting up dbt Cloud +id: set-up-dbt-cloud +description: "Set up a sample project to get you started using dbt Cloud." +sidebar_label: "About set up" +--- + +Learn how to set up dbt Cloud using a sample project and one of the most common data platforms. You can select from [BigQuery](/docs/get-started/getting-started/getting-set-up/setting-up-bigquery), [Databricks](/docs/get-started/getting-started/getting-set-up/setting-up-databricks), [Redshift](/docs/get-started/getting-started/getting-set-up/setting-up-redshift), or [Snowflake](/docs/get-started/getting-started/getting-set-up/setting-up-snowflake). If you're not sure, then try [BigQuery](/docs/get-started/getting-started/getting-set-up/setting-up-bigquery). + +This guide will show you how to set up dbt and perform some key tasks. These tasks will illustrate how dbt establishes standard practices for your work: + +* Set up a warehouse with sample data +* Connect the warehouse to dbt +* Add a Git repository to dbt +* Execute a dbt transformation using `dbt run` +* Schedule a job or transformation + +If you want a more in-depth learning experience, we recommend taking the dbt Fundamentals on our [dbt Learn online courses site](https://courses.getdbt.com/). + +If you'd rather edit and run files locally using the dbt command line interface (dbt CLI) to connect to dbt Core, then you can refer to [Getting started using dbt Core](/docs/get-started/getting-started-dbt-core). diff --git a/website/docs/guides/getting-started/getting-set-up/setting-up-bigquery.md b/website/docs/docs/get-started/getting-started/getting-set-up/setting-up-bigquery.md similarity index 98% rename from website/docs/guides/getting-started/getting-set-up/setting-up-bigquery.md rename to website/docs/docs/get-started/getting-started/getting-set-up/setting-up-bigquery.md index 01d2d1aa5b7..d9794821f39 100644 --- a/website/docs/guides/getting-started/getting-set-up/setting-up-bigquery.md +++ b/website/docs/docs/get-started/getting-started/getting-set-up/setting-up-bigquery.md @@ -3,7 +3,7 @@ title: "Set up and connect BigQuery" id: setting-up-bigquery description: "Set up BigQuery with sample data and connect to dbt Cloud." sidebar_label: "Set up and connect BigQuery" -pagination_next: guides/getting-started/building-your-first-project/build-your-first-models +pagination_next: docs/get-started/getting-started/building-your-first-project/build-your-first-models --- ## Introduction diff --git a/website/docs/guides/getting-started/getting-set-up/setting-up-databricks.md b/website/docs/docs/get-started/getting-started/getting-set-up/setting-up-databricks.md similarity index 98% rename from website/docs/guides/getting-started/getting-set-up/setting-up-databricks.md rename to website/docs/docs/get-started/getting-started/getting-set-up/setting-up-databricks.md index 05253abecbc..3d43d312565 100644 --- a/website/docs/guides/getting-started/getting-set-up/setting-up-databricks.md +++ b/website/docs/docs/get-started/getting-started/getting-set-up/setting-up-databricks.md @@ -3,8 +3,8 @@ title: "Set up and connect Databricks" id: setting-up-databricks description: "Set up Databricks with sample data and connect to dbt Cloud." sidebar_label: "Set up and connect Databricks" -pagination_prev: guides/getting-started/getting-set-up -pagination_next: guides/getting-started/building-your-first-project/build-your-first-models +pagination_prev: docs/get-started/getting-started/set-up-dbt-cloud +pagination_next: docs/get-started/getting-started/building-your-first-project/build-your-first-models --- ## Introduction diff --git a/website/docs/guides/getting-started/getting-set-up/setting-up-redshift.md b/website/docs/docs/get-started/getting-started/getting-set-up/setting-up-redshift.md similarity index 98% rename from website/docs/guides/getting-started/getting-set-up/setting-up-redshift.md rename to website/docs/docs/get-started/getting-started/getting-set-up/setting-up-redshift.md index 78c5f499cf0..85300aca8ce 100644 --- a/website/docs/guides/getting-started/getting-set-up/setting-up-redshift.md +++ b/website/docs/docs/get-started/getting-started/getting-set-up/setting-up-redshift.md @@ -3,8 +3,8 @@ title: "Set up and connect Redshift" id: setting-up-redshift description: "Set up Redshift with sample data and connect to dbt Cloud." sidebar_label: "Set up and connect Redshift" -pagination_prev: guides/getting-started/getting-set-up -pagination_next: guides/getting-started/building-your-first-project/build-your-first-models +pagination_prev: docs/get-started/getting-started/set-up-dbt-cloud +pagination_next: docs/get-started/getting-started/building-your-first-project/build-your-first-models --- ## Introduction diff --git a/website/docs/guides/getting-started/getting-set-up/setting-up-snowflake.md b/website/docs/docs/get-started/getting-started/getting-set-up/setting-up-snowflake.md similarity index 97% rename from website/docs/guides/getting-started/getting-set-up/setting-up-snowflake.md rename to website/docs/docs/get-started/getting-started/getting-set-up/setting-up-snowflake.md index de11ac74ab7..86ad73d3d47 100644 --- a/website/docs/guides/getting-started/getting-set-up/setting-up-snowflake.md +++ b/website/docs/docs/get-started/getting-started/getting-set-up/setting-up-snowflake.md @@ -3,8 +3,8 @@ title: "Set up and connect Snowflake" id: setting-up-snowflake description: "Set up Snowflake with sample data and connect to dbt Cloud." sidebar_label: "Set up and connect Snowflake" -pagination_prev: guides/getting-started/getting-set-up -pagination_next: guides/getting-started/building-your-first-project/build-your-first-models +pagination_prev: docs/get-started/getting-started/set-up-dbt-cloud +pagination_next: docs/get-started/getting-started/building-your-first-project/build-your-first-models --- ## Introduction @@ -175,7 +175,7 @@ There are two ways to connect dbt Cloud and Snowflake. The first option is Partn ### Option 1: Connect dbt Cloud and Snowflake with partner connect -1. With your Snowflake account up and running with data, we’re ready to connect it with dbt Cloud. We’re going to use [Snowflake Partner Connect](https://docs.snowflake.com/en/user-guide/ecosystem-partner-connect.html) to set up your dbt Cloud account and project. Using Partner Connect will allow you to create a complete dbt account with your [Snowflake connection](https://docs.getdbt.com/docs/dbt-cloud/cloud-configuring-dbt-cloud/connecting-your-database#connecting-to-snowflake), [a managed repository](https://docs.getdbt.com/docs/dbt-cloud/cloud-configuring-dbt-cloud/cloud-using-a-managed-repository), [environments](https://docs.getdbt.com/docs/guides/managing-environments), and credentials. +1. With your Snowflake account up and running with data, we’re ready to connect it with dbt Cloud. We’re going to use [Snowflake Partner Connect](https://docs.snowflake.com/en/user-guide/ecosystem-partner-connect.html) to set up your dbt Cloud account and project. Using Partner Connect will allow you to create a complete dbt account with your [Snowflake connection](https://docs.getdbt.com/docs/dbt-cloud/cloud-configuring-dbt-cloud/connecting-your-database#connecting-to-snowflake), [a managed repository](/docs/collaborate/git/managed-repository), [environments](/docs/build/custom-schemas#managing-environments), and credentials. 2. There’s a couple of ways you can access the Partner Connect page depending on if you’re navigating in the classic Snowflake UI or the new UI. * **Snowflake Classic UI:** If you’re using the classic version of the Snowflake UI, you can click the Partner Connect button in the top bar of your account. From there, click on the dbt tile to open up the connect box. diff --git a/website/docs/docs/get-started/getting-started/overview.md b/website/docs/docs/get-started/getting-started/overview.md new file mode 100644 index 00000000000..635b80a0155 --- /dev/null +++ b/website/docs/docs/get-started/getting-started/overview.md @@ -0,0 +1,34 @@ +--- +title: About getting started +id: overview +sidebar_label: "About getting started" +description: "Create your first dbt project using a SQL query." +--- +
+ + + +Before you begin, you will need: + +* Warehouse with sample data. If you don't have this, you can use the [BigQuery project](/docs/get-started/getting-started/getting-set-up/setting-up-bigquery), which leverages public data sets. +* Basic understanding of Git. +* Basic understanding of SQL. + + +
+ + + + + +
+ +
diff --git a/website/docs/dbt-cli/install/homebrew.md b/website/docs/docs/get-started/homebrew-install.md similarity index 92% rename from website/docs/dbt-cli/install/homebrew.md rename to website/docs/docs/get-started/homebrew-install.md index 5556f2d82d5..2a7e22a4cd9 100644 --- a/website/docs/dbt-cli/install/homebrew.md +++ b/website/docs/docs/get-started/homebrew-install.md @@ -1,5 +1,5 @@ --- -title: "Use Homebrew to install dbt" +title: "Install with Homebrew" description: "You can use Homebrew to install dbt Core and adapter plugins from the command line." --- @@ -16,7 +16,7 @@ If that sounds like you, great! Homebrew makes it significantly easier to instal - Installation with Homebrew can take longer than installing with other methods, because `brew` takes care of more setup behind the scenes - If you're using an M1 Mac, we recommend that you install dbt via Homebrew with [Rosetta](https://support.apple.com/en-us/HT211861). This is necessary for certain dependencies that are only supported on Intel processors. -If you're someone who prefers to manage Python environments yourself, such as having multiple versions of Python to switch between, we recommend you install dbt Core via [`pip` instead](install/pip). +If you're someone who prefers to manage Python environments yourself, such as having multiple versions of Python to switch between, we recommend you install dbt Core via [`pip` instead](/docs/develop/pip-install). ### Installing with Homebrew @@ -36,7 +36,7 @@ brew install dbt-postgres Everywhere below that you see ``, replace it with the adapter name you're using. -**Note**: If you're using an adapter that isn't available as a Homebrew formula, we recommend you use [pip](install/pip) instead. +**Note**: If you're using an adapter that isn't available as a Homebrew formula, we recommend you use [pip](/docs/develop/pip-install) instead. ### Upgrading dbt and your adapter diff --git a/website/docs/dbt-cli/install/overview.md b/website/docs/docs/get-started/installation-overview.md similarity index 60% rename from website/docs/dbt-cli/install/overview.md rename to website/docs/docs/get-started/installation-overview.md index 8d90e0c2462..cfb03a6b2cc 100644 --- a/website/docs/dbt-cli/install/overview.md +++ b/website/docs/docs/get-started/installation-overview.md @@ -1,15 +1,15 @@ --- -id: "overview" -title: "How to install dbt" +title: "Installation overview" +id: "installation" description: "You can install dbt Core using a few different tested methods." --- You can install dbt Core on the command line by using one of these recommended methods: -- [Use Homebrew to install dbt](install/homebrew) (recommended for MacOS + most popular plugins) -- [Use pip to install dbt](install/pip) -- [Use a Docker image to install dbt](install/docker) -- [Install dbt from source](install/from-source) +- [Use Homebrew to install dbt](/docs/get-started/homebrew-install) (recommended for MacOS + most popular plugins) +- [Use pip to install dbt](/docs/get-started/pip-install) +- [Use a Docker image to install dbt](/docs/get-started/docker-install) +- [Install dbt from source](/docs/get-started/source-install) ## About dbt adapters diff --git a/website/docs/guides/getting-started/learning-more/refactoring-legacy-sql.md b/website/docs/docs/get-started/learning-more/refactoring-legacy-sql.md similarity index 99% rename from website/docs/guides/getting-started/learning-more/refactoring-legacy-sql.md rename to website/docs/docs/get-started/learning-more/refactoring-legacy-sql.md index b6a79aed5e8..37e58c7f32d 100644 --- a/website/docs/guides/getting-started/learning-more/refactoring-legacy-sql.md +++ b/website/docs/docs/get-started/learning-more/refactoring-legacy-sql.md @@ -38,7 +38,7 @@ To get going, you'll copy your legacy SQL query into your dbt project, by saving Once you've copied it over, you'll want to `dbt run` to execute the query and populate the in your warehouse. -> If this is your first time running dbt, you may want to start with the [Introduction to dbt](/docs/introduction) and the earlier sections of the [Getting Started guide](/guides/getting-started/) before diving into refactoring. +> If this is your first time running dbt, you may want to start with the [Introduction to dbt](/docs/introduction) and the earlier sections of the [Getting Started guide](/docs/get-started/getting-started/) before diving into refactoring. This step may sound simple, but if you're porting over an existing set of SQL transformations to a new SQL dialect, you will need to consider how your legacy SQL dialect differs from your new SQL flavor, and you may need to modify your legacy code to get it to run at all. diff --git a/website/docs/guides/getting-started/learning-more/using-jinja.md b/website/docs/docs/get-started/learning-more/using-jinja.md similarity index 97% rename from website/docs/guides/getting-started/learning-more/using-jinja.md rename to website/docs/docs/get-started/learning-more/using-jinja.md index 43cf95059a4..0476b6aebc3 100644 --- a/website/docs/guides/getting-started/learning-more/using-jinja.md +++ b/website/docs/docs/get-started/learning-more/using-jinja.md @@ -150,7 +150,7 @@ group by 1 Getting whitespace control right is often a lot of trial and error! We recommend that you prioritize the readability of your model code over the readability of the compiled code, and only do this as an extra polish. ## Use a macro to return payment methods -Here, we've hardcoded the list of payment methods in our model. We may need to access this list from another model. A good solution here is to use a [variable](using-variables), but for the purpose of this tutorial, we're going to instead use a macro! +Here, we've hardcoded the list of payment methods in our model. We may need to access this list from another model. A good solution here is to use a [variable](/docs/build/project-variables), but for the purpose of this tutorial, we're going to instead use a macro! [Macros](jinja-macros#macros) in Jinja are pieces of code that can be called multiple times – they are analogous to a function in Python, and are extremely useful if you find yourself repeating code across multiple models. @@ -311,7 +311,7 @@ Macros let analysts bring software engineering principles to the SQL they write. A number of useful dbt macros have already been written in the [dbt-utils package](https://github.com/dbt-labs/dbt-utils). For example, the [get_column_values](https://github.com/dbt-labs/dbt-utils#get_column_values-source) macro from dbt-utils could be used instead of the `get_column_values` macro we wrote ourselves (saving us a lot of time, but at least we learnt something along the way!). -Install the [dbt-utils](https://hub.getdbt.com/dbt-labs/dbt_utils/latest/) package in your project (docs [here](package-management)), and then update your model to use the macro from the package instead: +Install the [dbt-utils](https://hub.getdbt.com/dbt-labs/dbt_utils/latest/) package in your project (docs [here](/docs/build/packages)), and then update your model to use the macro from the package instead: diff --git a/website/docs/dbt-cli/install/pip.md b/website/docs/docs/get-started/pip-install.md similarity index 87% rename from website/docs/dbt-cli/install/pip.md rename to website/docs/docs/get-started/pip-install.md index 1c7c4c486a3..b2c00152f52 100644 --- a/website/docs/dbt-cli/install/pip.md +++ b/website/docs/docs/get-started/pip-install.md @@ -1,9 +1,9 @@ --- -title: "Use pip to install dbt" +title: "Install with pip" description: "You can use pip to install dbt Core and adapter plugins from the command line." --- -You need to use `pip` to install dbt Core on Windows or Linux operating systems. You should use [Homebrew](install/homebrew) for installing dbt Core on a MacOS. +You need to use `pip` to install dbt Core on Windows or Linux operating systems. You should use [Homebrew](/docs/develop/homebrew-install) for installing dbt Core on a MacOS. You can install dbt Core and plugins using `pip` because they are Python modules distributed on [PyPI](https://pypi.org/project/dbt/). We recommend using virtual environments when installing with `pip`. @@ -42,7 +42,7 @@ pip install --upgrade dbt- ### Install dbt-core only -If you're building a tool that integrates with dbt Core, you may want to install the core library alone, without a database adapter. Note that you won't be able to use dbt as a CLI tool. Also, be advised that dbt Core's [Python API is currently unstable and undocumented](dbt-api). +If you're building a tool that integrates with dbt Core, you may want to install the core library alone, without a database adapter. Note that you won't be able to use dbt as a CLI tool. ```shell pip install dbt-core diff --git a/website/docs/docs/get-started/run-your-dbt-projects.md b/website/docs/docs/get-started/run-your-dbt-projects.md new file mode 100644 index 00000000000..be7c30f53dd --- /dev/null +++ b/website/docs/docs/get-started/run-your-dbt-projects.md @@ -0,0 +1,23 @@ +--- +title: "Run your dbt projects" +id: "run-your-dbt-projects" +--- +You can run your dbt projects with [dbt Cloud](/docs/develop/dbt-cloud-features) and [dbt Core](https://github.com/dbt-labs/dbt-core). dbt Cloud is a hosted application where you can develop directly from a web browser. dbt Core is an open source project where you can develop from the command line. + +Among other features, dbt Cloud provides a development environment to help you build, test, run, and [version control](/docs/collaborate/git-version-control) your project faster. It also includes an easier way to share your [dbt project's documentation](/docs/collaborate/build-and-view-your-docs) with your team. These development tasks are directly built into dbt Cloud for an _integrated development environment_ (IDE). Refer to [Develop in the Cloud](/docs/develop/develop-in-the-cloud) for more details. + +With dbt Core, you can run your dbt projects from the command line. The command line interface (CLI) is available from your computer's terminal application such as Terminal and iTerm. When using the command line, you can run commands and do other work from the current working directory on your computer. Before running the dbt project from the command line, make sure you are working in your dbt project directory. Learning terminal commands such as `cd` (change directory), `ls` (list directory contents), and `pwd` (present working directory) can help you navigate the directory structure on your system. + +When running your project from dbt Core or dbt Cloud, the commands you commonly use are: + +- [dbt run](/reference/commands/run) — Runs the models you defined in your project +- [dbt build](/reference/commands/build) — Builds and tests your selected resources such as models, seeds, snapshots, and tests +- [dbt test](/reference/commands/test) — Executes the tests you defined for your project + +For information on all dbt commands and their arguments (flags), see the [dbt command reference](/reference/dbt-commands). If you want to list all dbt commands from the command line, run `dbt --help`. To list a dbt command’s specific arguments, run `dbt COMMAND_NAME --help` . + +## Related docs + +- [How we set up our computers for working on dbt projects](https://discourse.getdbt.com/t/how-we-set-up-our-computers-for-working-on-dbt-projects/243) +- [Model selection syntax](/reference/node-selection/syntax) +- [Cloud IDE features](/docs/develop/dbt-cloud-features#ide-features) diff --git a/website/docs/dbt-cli/install/from-source.md b/website/docs/docs/get-started/source-install.md similarity index 97% rename from website/docs/dbt-cli/install/from-source.md rename to website/docs/docs/get-started/source-install.md index fe07d2a90ce..1f6b506815e 100644 --- a/website/docs/dbt-cli/install/from-source.md +++ b/website/docs/docs/get-started/source-install.md @@ -1,6 +1,5 @@ --- -title: "Install dbt from source" -id: "from-source" +title: "Install from source" description: "You can install dbt Core from its GitHub code source." --- diff --git a/website/docs/docs/introduction.md b/website/docs/docs/introduction.md index 73d33aa8e20..e52a389c15e 100644 --- a/website/docs/docs/introduction.md +++ b/website/docs/docs/introduction.md @@ -3,188 +3,65 @@ title: "What is dbt?" id: "introduction" --- -dbt enables analytics engineers to transform data in their warehouses by simply writing select statements. dbt handles turning these select statements into tables and views. +## About dbt -dbt does the `T` in (Extract, Load, Transform) processes – it doesn’t extract or load data, but it’s extremely good at transforming data that’s already loaded into your warehouse. + -The role of dbt within a modern data stack is discussed in more detail [here](https://blog.fishtownanalytics.com/what-exactly-is-dbt-47ba57309068). +dbt compiles and runs your analytics code against your data platform, enabling you and your team to collaborate on a single source of truth for metrics, insights, and business definitions. This single source of truth, combined with the ability to define tests for your data, reduces errors when logic changes, and alerts you when issues arise. -dbt also enables analysts to work more like software engineers, in line with the dbt [Viewpoint](viewpoint). +Read more about why we want to enable analysts to work more like software engineers in [The dbt Viewpoint](/community/resources/viewpoint). -## How do I use dbt? +## dbt optimizes your workflow -### dbt Projects -A dbt project is a directory of `.sql` and .`yml` files. The directory must contain at a minimum: -* Models: A model is a single `.sql` file. Each model contains a single `select` statement that either transforms raw data into a dataset that is ready for analytics, or, more often, is an intermediate step in such a transformation. -* A project file: a `dbt_project.yml` file which configures and defines your dbt project. +- Avoid writing boilerplate  and by managing transactions, dropping tables, and managing schema changes. Write business logic with just a SQL `select` statement, or a Python DataFrame, that returns the dataset you need, and dbt takes care of . +- Build up reusable, or modular, data models that can be referenced in subsequent work instead of starting at the raw data with every analysis. +- Dramatically reduce the time your queries take to run: Leverage metadata to find long-running models that you want to optimize and use [incremental models](/docs/build/incremental-models) which dbt makes easy to configure and use. +- Write er code by leveraging [macros](/docs/build/jinja-macros), [hooks](/docs/build/hooks-operations), and [package management](/docs/build/packages). -Projects typically contain a number of other resources as well, including tests, snapshots, and seed files (see [below](#what-else-can-dbt-do)). +## dbt provides more reliable analysis -Whether you are starting a project from scratch, or if your organization already has a dbt project, see the docs on [projects](projects) for more information on getting started. +- No longer copy and paste SQL, which can lead to errors when logic changes. Instead, build reusable data models that get pulled into subsequent models and analysis. Change a model once and that change will propagate to all its dependencies. +- Publish the canonical version of a particular data model, encapsulating all complex business logic. All analysis on top of this model will incorporate the same business logic without needing to reimplement it. +- Use mature source control processes like branching, pull requests, and code reviews. +- Write data quality tests quickly and easily on the underlying data. Many analytic errors are caused by edge cases in the data: testing helps analysts find and handle those edge cases. -:::info Check out our sample dbt project +## dbt products -Want to check out a sample project? Have a look at our [Jaffle Shop](https://github.com/dbt-labs/jaffle_shop) project on GitHub! +You can access dbt using dbt Core or dbt Cloud. dbt Cloud is built around dbt Core, but it also provides: -::: +- Web-based UI so it’s more accessible +- Hosted environment so it’s faster to get up and running +- Differentiated features, such as metadata, in-app job scheduler, observability, integrations with other tools, integrated development environment (IDE), and more. -### Database Connections -dbt connects to your to run data transformation queries. As such, you’ll need a data warehouse with source data loaded in it to use dbt. dbt natively supports connections to Snowflake, BigQuery, Redshift and Postgres data warehouses, and there’s a number of community-supported adapters for other warehouses (see [Supported Data Platforms](supported-data-platforms)). +You can learn about plans and pricing on [www.getdbt.com]([https://www.getdbt.com/pricing/](https://www.getdbt.com/pricing/)). -When you define your connection, you’ll also be able to specify the target schema where dbt should create your models as tables and views. See [Managing environments](managing-environments) for more information on picking target schema names. +### dbt Cloud +dbt Cloud is the fastest and most reliable way to deploy dbt. Develop, test, schedule, and investigate data models all in one web-based UI. Read more about [Getting started with dbt Cloud](/docs/get-started/getting-started/set-up-dbt-cloud) and [dbt Cloud features](/docs/get-started/dbt-cloud-features). -### dbt Commands -A command is an instruction to execute dbt which compiles and runs SQL against the database. +### dbt Core -When you issue a dbt command, such as `run`, dbt: +dbt Core is an open-source tool that enables data teams to transform data using analytics engineering best practices. You can install and use dbt Core on the command line. Read more about [Getting started with dbt Core](/docs/get-started/getting-started-dbt-core). -1. Determines the order to execute the models in your project in. -2. Generates the required to build the model, as per the model's ** -3. Executes the compiled queries against your data warehouse, using the credentials specified in the *target* defined in your *profile*. Executing these queries creates relations in the target schema in your data warehouse. These relations contain transformed data, ready for analysis. +## The power of dbt -A list of commands can be found in the [Command reference](dbt-commands) section of these docs. - -## What does the workflow for using dbt look like? -There’s two main ways of working with dbt -- using the web-based Integrated Development Environment (IDE) in dbt Cloud, or using the Command Line Interface (CLI). - -### Developing in dbt Cloud -To get started with a project and connection, follow the onboarding flow. Use the web editor to build your project and execute dbt commands. If you don't have one already, you can sign up for a [free account](https://www.getdbt.com/signup). - -### Developing locally with the Command Line Interface (CLI) -To use the CLI: - -1. Follow [these instructions](dbt-cli/install/overview) to install the dbt CLI -2. [Set up a profile](configure-your-profile) to connect to your data warehouse -3. Build your dbt project in a code editor, like Atom or VSCode -4. Execute commands using your terminal - -:::info Developing locally? - -If you’re developing your dbt project locally, we recommend checking out [this article](https://discourse.getdbt.com/t/how-we-set-up-our-computers-for-working-on-dbt-projects/243) to understand how we set up our computers. - -::: - -## What makes dbt so powerful? As a dbt user, your main focus will be on writing models (i.e. select queries) that reflect core business logic – there’s no need to write boilerplate code to create tables and views, or to define the order of execution of your models. Instead, dbt handles turning these models into objects in your warehouse for you. -**dbt handles boilerplate code to materialize queries as relations.** -For each model you create, you can easily configure a *materialization*. - -A materialization represents a build strategy for your select query – the code behind a materialization is robust, boilerplate SQL that wraps your select query in a statement to create a new, or update an existing, relation. - -dbt ships with the following built-in materializations: -* `view` (default): The model is built as a view in the database. -* `table`: The model is built as a table in the database. -* `ephemeral`: The model is not directly built in the database, but is instead pulled into dependent models as common expressions. -* `incremental`: The model is initially built as a table, and in subsequent runs, dbt inserts new rows and updates changed rows in the table. - -Custom materializations can also be built if required. - -**dbt determines the order of model execution.** -Often when transforming data, it makes sense to do so in a staged approach. dbt provides a mechanism to implement transformations in stages through the [ref](ref) function. - -Rather than selecting from existing tables and views in your warehouse, you can select from _another model_, like so: - - - -```sql -select - orders.id, - orders.status, - sum(case when payments.payment_method = 'bank_transfer' then payments.amount else 0 end) as bank_transfer_amount, - sum(case when payments.payment_method = 'credit_card' then payments.amount else 0 end) as credit_card_amount, - sum(case when payments.payment_method = 'gift_card' then payments.amount else 0 end) as gift_card_amount, - sum(amount) as total_amount - -from {{ ref('base_orders') }} as orders -left join {{ ref('base_payments') }} as payments on payments.order_id = orders.id -``` - - - -When compiled to executable SQL, dbt will replace the model specified in the `ref` function with the relation name. - -Importantly, dbt also uses the `ref` function to determine the sequence in which to execute the models – in the above example, `base_orders` and `base_payments` need to be built prior to building the `orders` model. - - - -dbt builds a directed acyclic graph (DAG) based on the interdependencies between models – each node of the graph represents a model, and edges between the nodes are defined by `ref` functions, where a model specified in a `ref` function is recognized as a predecessor of the current model. - -When dbt runs, models are executed in the order specified by the DAG – there’s no need to explicitly define the order of execution of your models. Building models in staged transformations also reduces the need to repeat SQL, as a single transformation (for example, renaming a column) can be shared as a predecessor for a number of downstream models. - -For more information see [Ref](ref). - -:::info Want to see a DAG visualization for your project? - -Check out the [Documentation Website](documentation) docs - -::: - -## What else can dbt do? -dbt has a number of additional features that make it even more powerful, including: - - -**Code compiler:** -In dbt, SQL files can contain Jinja, a lightweight templating language. Using Jinja in SQL provides a way to use control structures (e.g. `if` statements and `for` loops) in your queries. It also enables repeated SQL to be shared through `macros`. - -The power of using Jinja in your queries is discussed in [Using Jinja](using-jinja). - - -**Documentation:** -dbt provides a mechanism to write, version-control, and share documentation for your dbt models. Descriptions (in plain text, or markdown) can be written for each model and field. - -These descriptions, along with additional implicit information (for example, the model lineage, or the field data type and tests applied), can be generated as a website and shared with your wider team, providing an easily referenceable databook for anyone that interacts with dbt models. - -For more information see [Documentation](documentation). - -**Tests:** -SQL can be difficult to test, since the underlying data is frequently changing. dbt provides a way to improve the integrity of the SQL in each model by making assertions about the results generated by a model. Out of the box, you can test whether a specified column in a model only contains: - -* Non-null values -* Unique values -* Values that have a corresponding value in another model (e.g. a `customer_id` for an `order` corresponds to an `id` in the `customers` model) -* Values from a specified list - -Tests can be easily extended to suit business logic specific to your organization – any assertion that you can make about your model in the form of a select query can be turned into a test. - -To learn more about writing tests for your models, see [Testing](building-a-dbt-project/tests). - - -**Package management:** -dbt ships with a package manager, which allows analysts to use and publish both public and private repositories of dbt code which can then be referenced by others. - -This means analysts can leverage libraries that provide commonly-used macros like [dbt_utils](https://github.com/dbt-labs/dbt-utils), or dataset-specific projects for software services like [Snowplow](https://github.com/dbt-labs/snowplow) and [Stripe](https://github.com/dbt-labs/stripe), to hit the ground running. - -For more information, see [Package Management](package-management). - - -**Seed file loader:** -Often in analytics, raw values need to be mapped to a more readable value (e.g. converting a country-code to a country name) or enriched with static, or infrequently changing data (e.g. using revenue targets set each year to assess your actuals). - -These data sources, known as seed files, can be saved as a CSV file in your `project` and loaded into your data warehouse through use of the `seed` command. - -The documentation for the seed command can be found [here](seeds). - - -**Data snapshots:** -Often, records in a data source are mutable, in that they change over time. This can be difficult to handle in analytics if you want to reconstruct historic values. - -dbt provides a mechanism to snapshot raw data for a point in time, through use of [snapshots](snapshots). - - -**Understand raw data sources:** -Since dbt selects from raw data already loaded in your data warehouse, it's useful to understand the role of these tables and schemas within your warehouse. Defining raw data as a Source in dbt allows you to: -* Document and test the data that is loaded into your warehouse -* Check the freshness of your data against specified limits, to help identify upstream issues. -* Understand which models depend on each data source. - -Check out the [documentation on Sources](using-sources). - - -## Who should use dbt? -dbt is appropriate for anyone who interacts with a data warehouse. It can be used by data engineers, data analysts and data scientists, or anyone that knows how to write select queries in SQL. - -For dbt users that are new to programming, you may also need to spend some time getting to know the basics of the command line, and familiarizing yourself with git. - -To make full use of dbt, it may also be beneficial to know some programming basics, such as `for` loops and `if` statements, to use Jinja effectively in your models. +| Feature | Description | +|-----------------------|-------------| +| Handle boilerplate code to materialize queries as relations | For each model you create, you can easily configure a *materialization*. A materialization represents a build strategy for your select query – the code behind a materialization is robust, boilerplate SQL that wraps your select query in a statement to create a new, or update an existing, relation. Read more about [Materializations](/docs/build/materializations).| +| Use a code compiler | SQL files can contain Jinja, a lightweight templating language. Using Jinja in SQL provides a way to use control structures in your queries. For example, `if` statements and `for` loops. It also enables repeated SQL to be shared through `macros`. Read more about [Macros](/docs/build/jinja-macros).| +| Determine the order of model execution | Often, when transforming data, it makes sense to do so in a staged approach. dbt provides a mechanism to implement transformations in stages through the [ref function](/reference/dbt-jinja-functions/ref). Rather than selecting from existing tables and views in your warehouse, you can select from another model.| +| Document your dbt project | dbt provides a mechanism to write, version-control, and share documentation for your dbt models. You can write descriptions (in plain text or markdown) for each model and field. In dbt Cloud, you can auto-generate the documentation when your dbt project runs. Read more about the [Documentation](/docs/collaborate/documentation).| +| Test your models | Tests provide a way to improve the integrity of the SQL in each model by making assertions about the results generated by a model. Read more about writing tests for your models [Testing](/docs/build/tests)| +| Manage packages | dbt ships with a package manager, which allows analysts to use and publish both public and private repositories of dbt code which can then be referenced by others. Read more about [Package Management](/docs/build/packages). | +| Load seed files| Often in analytics, raw values need to be mapped to a more readable value (for example, converting a country-code to a country name) or enriched with static or infrequently changing data. These data sources, known as seed files, can be saved as a CSV file in your `project` and loaded into your data warehouse using the `seed` command. Read more about [Seeds](/docs/build/seeds).| +| Snapshot data | Often, records in a data source are mutable, in that they change over time. This can be difficult to handle in analytics if you want to reconstruct historic values. dbt provides a mechanism to snapshot raw data for a point in time, through use of [snapshots](/docs/build/snapshots).| + +### Related docs + +- [Getting started with dbt Cloud](/docs/get-started/getting-started/set-up-dbt-cloud) +- [Getting started with dbt Core](/docs/get-started/getting-started-dbt-core) +- [Best practice guides](/guides/best-practices) +- [What is a dbt Project?](/docs/build/projects) +- [dbt run](/docs/get-started/run-your-dbt-projects) diff --git a/website/docs/docs/running-a-dbt-project/profile.md b/website/docs/docs/running-a-dbt-project/profile.md deleted file mode 100644 index 66dc1fa3cca..00000000000 --- a/website/docs/docs/running-a-dbt-project/profile.md +++ /dev/null @@ -1,11 +0,0 @@ ---- -title: "Profile" -id: "profile" ---- - - -:::danger This page has been deprecated - -Check out [Connecting to your warehouse with the CLI](configure-your-profile) for the newer documentation. - -::: diff --git a/website/docs/docs/supported-data-platforms.md b/website/docs/docs/supported-data-platforms.md index 159dd13e319..5ee30fdd0b4 100644 --- a/website/docs/docs/supported-data-platforms.md +++ b/website/docs/docs/supported-data-platforms.md @@ -1,21 +1,21 @@ --- -title: "Supported Data Platforms" +title: "Supported data platforms" id: "supported-data-platforms" --- dbt connects to and runs SQL against your database, warehouse, lake or query engine. To keep things simple, we group all of these SQL-speaking things into one bucket called "data platforms". dbt can be extended to any data platform by means of a dedicated _adapter plugin_. These plugins are built as separate Python modules that dbt Core will discover them if they are installed on your system. All the adapters listed below are open source and free to use, just like dbt Core. -To learn more about adapters, check out [What Are Adapters](contributing/adapter-development/1-what-are-adapters). +To learn more about adapters, check out [What Are Adapters](/docs/contributing/adapter-development/1-what-are-adapters). ## Adapter Installation -With a few exceptions [^1], all adapters listed below can be installed from PyPI using `pip install `. The installation will include `dbt-core` and any other required dependencies, which may include both other dependencies and even other adapter plugins. Read more about [installing dbt](dbt-cli/install/overview). +With a few exceptions [^1], all adapters listed below can be installed from PyPI using `pip install `. The installation will include `dbt-core` and any other required dependencies, which may include both other dependencies and even other adapter plugins. Read more about [installing dbt](/docs/get-started/installation). ## Adapter Taxonomy ### Verified by dbt Labs -In order to provide a more consistent and reliable experience, dbt Labs now has a rigorous process by which we verify adapter plugins. The process covers aspects of development, documentation, user experience and maintenance. These adapters earn a "Verified" designation so that users can have a certain level of trust and expectation when they use them. To learn more see [Verifying a new adapter](docs/contributing/adapter-development/7-verifying-a-new-adapter) +In order to provide a more consistent and reliable experience, dbt Labs now has a rigorous process by which we verify adapter plugins. The process covers aspects of development, documentation, user experience and maintenance. These adapters earn a "Verified" designation so that users can have a certain level of trust and expectation when they use them. To learn more see [Verifying a new adapter](/docs/contributing/adapter-development/7-verifying-a-new-adapter) We also welcome and encourage adapter plugins from the dbt community (see the below [Contributing to a pre-existing adapter](#contributing-to-a-pre-existing-adapter)). Please note that these community maintainers are intrepid volunteers who owe you nothing, but give anyway -- so be kind and understanding, and help out where you can! diff --git a/website/docs/faqs/Core/install-pip-os-prereqs.md b/website/docs/faqs/Core/install-pip-os-prereqs.md index c0519a3e84a..8124eaaa215 100644 --- a/website/docs/faqs/Core/install-pip-os-prereqs.md +++ b/website/docs/faqs/Core/install-pip-os-prereqs.md @@ -6,7 +6,7 @@ id: install-pip-os-prereqs.md --- -Your operating system may require pre-installation setup before installing dbt Core with pip. After downloading and installing any dependencies specific to your development environment, you can proceed with the [pip installation of dbt Core](/docs/dbt-cli/install/pip). +Your operating system may require pre-installation setup before installing dbt Core with pip. After downloading and installing any dependencies specific to your development environment, you can proceed with the [pip installation of dbt Core](/docs/get-started/pip-install). ### CentOS diff --git a/website/docs/faqs/Environments/profile-name.md b/website/docs/faqs/Environments/profile-name.md index c8ed61dc087..9f9d8b0ae59 100644 --- a/website/docs/faqs/Environments/profile-name.md +++ b/website/docs/faqs/Environments/profile-name.md @@ -4,4 +4,4 @@ description: "Use company name for profile name" sidebar_label: 'Naming your profile' id: profile-name --- -We typically use a company name for a profile name, and then use targets to differentiate between `dev` and `prod`. Check out the docs on [managing environments](managing-environments) for more information. +We typically use a company name for a profile name, and then use targets to differentiate between `dev` and `prod`. Check out the docs on [managing environments](/docs/collaborate/environments) for more information. diff --git a/website/docs/faqs/Environments/target-names.md b/website/docs/faqs/Environments/target-names.md index f141a95fc1f..6d3cd78b8e0 100644 --- a/website/docs/faqs/Environments/target-names.md +++ b/website/docs/faqs/Environments/target-names.md @@ -5,4 +5,4 @@ sidebar_label: 'Naming your target' id: target-names --- -We typically use targets to differentiate between development and production runs of dbt, naming the targets `dev` and `prod` respectively. Check out the docs on [managing environments](managing-environments) for more information. +We typically use targets to differentiate between development and production runs of dbt, naming the targets `dev` and `prod` respectively. Check out the docs on [managing environments](/docs/collaborate/environments) for more information. diff --git a/website/docs/faqs/Models/create-dependencies.md b/website/docs/faqs/Models/create-dependencies.md index 6ca7d044fb6..4a84e3ab7d7 100644 --- a/website/docs/faqs/Models/create-dependencies.md +++ b/website/docs/faqs/Models/create-dependencies.md @@ -44,4 +44,4 @@ Found 2 models, 28 tests, 0 snapshots, 0 analyses, 130 macros, 0 operations, 0 s Done. PASS=2 WARN=0 ERROR=0 SKIP=0 TOTAL=2 ``` -To learn more about building a dbt project, we recommend you complete the [Getting Started guide](/guides/getting-started). +To learn more about building a dbt project, we recommend you complete the [Getting Started guide](/docs/get-started/getting-started/overview). diff --git a/website/docs/faqs/Models/specifying-column-types.md b/website/docs/faqs/Models/specifying-column-types.md index f7cf439bc4b..1adaf30fdce 100644 --- a/website/docs/faqs/Models/specifying-column-types.md +++ b/website/docs/faqs/Models/specifying-column-types.md @@ -38,6 +38,6 @@ So long as your model queries return the correct column type, the table you crea To define additional column options: -* Rather than enforcing uniqueness and not-null constraints on your column, use dbt's [testing](building-a-dbt-project/tests) functionality to check that your assertions about your model hold true. +* Rather than enforcing uniqueness and not-null constraints on your column, use dbt's [testing](/docs/build/tests) functionality to check that your assertions about your model hold true. * Rather than creating default values for a column, use SQL to express defaults (e.g. `coalesce(updated_at, current_timestamp()) as updated_at`) * In edge-cases where you _do_ need to alter a column (e.g. column-level encoding on Redshift), consider implementing this via a [post-hook](pre-hook-post-hook). diff --git a/website/docs/faqs/Models/unique-model-names.md b/website/docs/faqs/Models/unique-model-names.md index a0a450d04db..7aff90809a4 100644 --- a/website/docs/faqs/Models/unique-model-names.md +++ b/website/docs/faqs/Models/unique-model-names.md @@ -8,4 +8,4 @@ id: unique-model-names Yes! To build dependencies between models, you need to use the `ref` function. The `ref` function only takes one argument — the model name (i.e. the filename). As a result, these model names need to be unique, _even if they are in distinct folders_. -Often, this question comes up because users want to give two models the same name in their warehouse, splitting them across separate schemas (e.g. `stripe.users` and `app.users`). Checkout the docs on [custom aliases](using-custom-aliases) and [custom schemas](using-custom-schemas) to achieve this. +Often, this question comes up because users want to give two models the same name in their warehouse, splitting them across separate schemas (e.g. `stripe.users` and `app.users`). Checkout the docs on [custom aliases](using-custom-aliases) and [custom schemas](/docs/build/custom-schemas) to achieve this. diff --git a/website/docs/faqs/Project/example-projects.md b/website/docs/faqs/Project/example-projects.md index 219397462d5..d4bebc7206d 100644 --- a/website/docs/faqs/Project/example-projects.md +++ b/website/docs/faqs/Project/example-projects.md @@ -8,7 +8,7 @@ id: example-projects Yes! -* **Getting Started Tutorial:** You can build your own example dbt project in the [Getting Started Tutorial](/guides/getting-started) +* **Getting Started Tutorial:** You can build your own example dbt project in the [Getting Started guide](/docs/get-started/getting-started/overview) * **Jaffle Shop:** A demonstration project (closely related to the tutorial) for a fictional ecommerce store ([source code](https://github.com/dbt-labs/jaffle_shop)) * **MRR Playbook:** A demonstration project that models subscription revenue ([source code](https://github.com/dbt-labs/mrr-playbook), [docs](https://www.getdbt.com/mrr-playbook/#!/overview)) * **Attribution Playbook:** A demonstration project that models marketing attribution ([source code](https://github.com/dbt-labs/attribution-playbook), [docs](https://www.getdbt.com/attribution-playbook/#!/overview)) diff --git a/website/docs/faqs/Project/project-name.md b/website/docs/faqs/Project/project-name.md deleted file mode 100644 index ec4b393a50a..00000000000 --- a/website/docs/faqs/Project/project-name.md +++ /dev/null @@ -1,8 +0,0 @@ ---- -title: What should I name my dbt project? -description: "Using snake_case to name your dbt project" -sidebar_label: 'How to format your dbt project name' -id: project-name - ---- -The name of your company (in `snake_case`) often makes for a good [project name](reference/project-configs/name.md). diff --git a/website/docs/faqs/Project/which-schema.md b/website/docs/faqs/Project/which-schema.md index 56a2a87d844..f0634ac8c85 100644 --- a/website/docs/faqs/Project/which-schema.md +++ b/website/docs/faqs/Project/which-schema.md @@ -9,6 +9,6 @@ By default, dbt builds models in your target schema. To change your target schem * If you're developing in **dbt Cloud**, these are set for each user when you first use a development environment. * If you're developing with the **dbt CLI**, this is the `schema:` parameter in your `profiles.yml` file. -If you wish to split your models across multiple schemas, check out the docs on [using custom schemas](using-custom-schemas). +If you wish to split your models across multiple schemas, check out the docs on [using custom schemas](/docs/build/custom-schemas). Note: on BigQuery, `dataset` is used interchangeably with `schema`. diff --git a/website/docs/faqs/Snapshots/snapshot-target-schema.md b/website/docs/faqs/Snapshots/snapshot-target-schema.md index 02cd8f4d639..70c5b56f067 100644 --- a/website/docs/faqs/Snapshots/snapshot-target-schema.md +++ b/website/docs/faqs/Snapshots/snapshot-target-schema.md @@ -18,4 +18,4 @@ Instead, in the models that `ref` your snapshots, it makes more sense to `select For this reason, there is only _one_ `target_schema`, which is _not_ environment-aware by default. -However, this can create problems if you need to run a `snapshot` command when developing your models, or during a CI run. Fortunately, there's a few workarounds — check out [this Discourse article](https://discourse.getdbt.com/t/using-dynamic-schemas-for-snapshots/1070). +However, this can create problems if you need to run a `snapshot` command when developing your models, or during a CI run. Fortunately, there's a few workarounds — check out [this forum article](https://discourse.getdbt.com/t/using-dynamic-schemas-for-snapshots/1070). diff --git a/website/docs/faqs/Tests/available-tests.md b/website/docs/faqs/Tests/available-tests.md index 206bb60b5bf..ce3c3288491 100644 --- a/website/docs/faqs/Tests/available-tests.md +++ b/website/docs/faqs/Tests/available-tests.md @@ -12,6 +12,6 @@ Out of the box, dbt ships with the following tests: * `accepted_values` * `relationships` (i.e. referential integrity) -You can also write your own [custom schema tests](building-a-dbt-project/tests). +You can also write your own [custom schema tests](/docs/build/tests). Some additional custom schema tests have been open-sourced in the [dbt-utils package](https://github.com/dbt-labs/dbt-utils/tree/0.2.4/#schema-tests), check out the docs on [packages](package-management) to learn how to make these tests available in your project. diff --git a/website/docs/docs/contributing/adapter-development/1-what-are-adapters.md b/website/docs/guides/advanced/adapter-development/1-what-are-adapters.md similarity index 100% rename from website/docs/docs/contributing/adapter-development/1-what-are-adapters.md rename to website/docs/guides/advanced/adapter-development/1-what-are-adapters.md diff --git a/website/docs/docs/contributing/adapter-development/2-prerequisites-for-a-new-adapter.md b/website/docs/guides/advanced/adapter-development/2-prerequisites-for-a-new-adapter.md similarity index 100% rename from website/docs/docs/contributing/adapter-development/2-prerequisites-for-a-new-adapter.md rename to website/docs/guides/advanced/adapter-development/2-prerequisites-for-a-new-adapter.md diff --git a/website/docs/docs/contributing/adapter-development/3-building-a-new-adapter.md b/website/docs/guides/advanced/adapter-development/3-building-a-new-adapter.md similarity index 100% rename from website/docs/docs/contributing/adapter-development/3-building-a-new-adapter.md rename to website/docs/guides/advanced/adapter-development/3-building-a-new-adapter.md diff --git a/website/docs/docs/contributing/adapter-development/4-testing-a-new-adapter.md b/website/docs/guides/advanced/adapter-development/4-testing-a-new-adapter.md similarity index 100% rename from website/docs/docs/contributing/adapter-development/4-testing-a-new-adapter.md rename to website/docs/guides/advanced/adapter-development/4-testing-a-new-adapter.md diff --git a/website/docs/docs/contributing/adapter-development/5-documenting-a-new-adapter.md b/website/docs/guides/advanced/adapter-development/5-documenting-a-new-adapter.md similarity index 100% rename from website/docs/docs/contributing/adapter-development/5-documenting-a-new-adapter.md rename to website/docs/guides/advanced/adapter-development/5-documenting-a-new-adapter.md diff --git a/website/docs/docs/contributing/adapter-development/6-promoting-a-new-adapter.md b/website/docs/guides/advanced/adapter-development/6-promoting-a-new-adapter.md similarity index 100% rename from website/docs/docs/contributing/adapter-development/6-promoting-a-new-adapter.md rename to website/docs/guides/advanced/adapter-development/6-promoting-a-new-adapter.md diff --git a/website/docs/docs/contributing/adapter-development/7-verifying-a-new-adapter.md b/website/docs/guides/advanced/adapter-development/7-verifying-a-new-adapter.md similarity index 100% rename from website/docs/docs/contributing/adapter-development/7-verifying-a-new-adapter.md rename to website/docs/guides/advanced/adapter-development/7-verifying-a-new-adapter.md diff --git a/website/docs/guides/best-practices/how-we-structure/3-intermediate.md b/website/docs/guides/best-practices/how-we-structure/3-intermediate.md index 9fc71b326a4..84ee931d64b 100644 --- a/website/docs/guides/best-practices/how-we-structure/3-intermediate.md +++ b/website/docs/guides/best-practices/how-we-structure/3-intermediate.md @@ -71,7 +71,7 @@ select * from pivot_and_aggregate_payments_to_order_grain - ❌ **Exposed to end users.** Intermediate models should generally not be exposed in the main production schema. They are not intended for output to final targets like dashboards or applications, so it’s best to keep them separated from models that are so you can more easily control data governance and discoverability. - ✅ **Materialized ephemerally.** Considering the above, one popular option is to default to intermediate models being materialized [ephemerally](/docs/building-a-dbt-project/building-models/materializations/#ephemeral). This is generally the best place to start for simplicity. It will keep unnecessary models out of your warehouse with minimum configuration. Keep in mind though that the simplicity of ephemerals does translate a bit more difficulty in troubleshooting, as they’re interpolated into the models that `ref` them, rather than existing on their own in a way that you can view the output of. -- ✅ **Materialized as views in a custom schema with special permissions.** A more robust option is to materialize your intermediate models as views in a specific [custom schema](https://docs.getdbt.com/docs/building-a-dbt-project/building-models/using-custom-schemas), outside of your main production schema. This gives you added insight into development and easier troubleshooting as the number and complexity of your models grows, while remaining easy to implement and taking up negligible space. +- ✅ **Materialized as views in a custom schema with special permissions.** A more robust option is to materialize your intermediate models as views in a specific [custom schema](/docs/build/custom-schemas), outside of your main production schema. This gives you added insight into development and easier troubleshooting as the number and complexity of your models grows, while remaining easy to implement and taking up negligible space. :::tip Keep your warehouse tidy! There are three interfaces to the organizational knowledge graph we’re encoding into dbt: the DAG, the files and folder structure of our codebase, and the output into the warehouse. As such, it’s really important that we consider that output intentionally! Think of the schemas, tables, and views we’re creating in the warehouse as *part of the UX,* in addition to the dashboards, ML, apps, and other use cases you may be targeting for the data. Ensuring that our output is named and grouped well, and that models not intended for broad use are either not materialized or built into special areas with specific permissions is crucial to achieve this. diff --git a/website/docs/guides/best-practices/how-we-structure/4-marts.md b/website/docs/guides/best-practices/how-we-structure/4-marts.md index 201956ddbf7..3cf4bc78209 100644 --- a/website/docs/guides/best-practices/how-we-structure/4-marts.md +++ b/website/docs/guides/best-practices/how-we-structure/4-marts.md @@ -134,4 +134,4 @@ The most important aspect of marts is that they contain all of the useful data a - Reverse ETL - Reporting and dashboards - Data science and ML - - [Exposures](https://docs.getdbt.com/docs/building-a-dbt-project/exposures) (how we tie our dbt DAG into all of the above) + - [Exposures](https://docs.getdbt.com/docs/build/exposures) (how we tie our dbt DAG into all of the above) diff --git a/website/docs/guides/getting-started/getting-set-up.md b/website/docs/guides/getting-started/getting-set-up.md deleted file mode 100644 index 56bbcb13ff8..00000000000 --- a/website/docs/guides/getting-started/getting-set-up.md +++ /dev/null @@ -1,10 +0,0 @@ ---- -title: Getting set up in dbt Cloud -id: getting-set-up -description: "Set up a sample project to get you started using dbt Cloud." -sidebar_label: "Getting set up" ---- - -In this guide, you will learn how to set up dbt Cloud using a sample project and one of the most common data platforms. You can select from [BigQuery](/guides/getting-started/getting-set-up/setting-up-bigquery), [Databricks](/guides/getting-started/getting-set-up/setting-up-databricks), [Redshift](/guides/getting-started/getting-set-up/setting-up-redshift), or [Snowflake](/guides/getting-started/getting-set-up/setting-up-snowflake). If you're not sure, then try [BigQuery](/guides/getting-started/getting-set-up/setting-up-bigquery). - -If you'd rather edit and run files locally using the dbt command line interface (dbt CLI) to connect to dbt Core, then you can refer to [Getting started using dbt Core](/guides/getting-started/learning-more/getting-started-dbt-core). diff --git a/website/docs/guides/getting-started/getting-started.md b/website/docs/guides/getting-started/getting-started.md deleted file mode 100644 index 0cd06fe699e..00000000000 --- a/website/docs/guides/getting-started/getting-started.md +++ /dev/null @@ -1,29 +0,0 @@ ---- -title: Getting started with dbt Cloud -id: getting-started -description: "Create your first dbt project using a SQL query." ---- - -dbt centralizes your analytics code and enables software engineering-style guardrails for data teams. dbt enables you to collaborate on SQL, version it through Git, and test and document your queries before safely deploying them to production and monitoring them. - -dbt takes your analytics code and helps you modularize it before you compile and run against your database. This enables you and your team to collaborate on a single source of truth for metrics and insights. A single source of truth, combined with the ability to define tests for your data, reduces errors when your analytics code is updated due to changes in your business and alerts you when a job fails - -This guide will show you how to set up dbt Cloud and perform some key tasks. These tasks will illustrate how dbt establishes standard practices for your work. - -In this guide, you will: - -* Set up a warehouse with sample data -* Connect the warehouse to dbt Cloud -* Add a Git repository to dbt Cloud -* Execute a dbt transformation using `dbt run` -* Schedule a job or transformation - -If you want a more in-depth learning experience, we recommend taking the dbt Fundamentals on our [dbt Learn online courses site](https://courses.getdbt.com/). - -## Before you begin - -Before you begin, you will need: - -* Warehouse with sample data. If you don't have this, you can use the [Big Query project](guides/getting-started/getting-set-up/setting-up-bigquery), which leverages public data sets. -* Basic understanding of Git. -* Basic understanding of SQL. diff --git a/website/docs/guides/getting-started/learning-more.md b/website/docs/guides/getting-started/learning-more.md deleted file mode 100644 index 0ee54c5e8c7..00000000000 --- a/website/docs/guides/getting-started/learning-more.md +++ /dev/null @@ -1,14 +0,0 @@ ---- -title: "Learning more" -id: learning-more -description: "Learn more dbt skills and make more impact using dbt." -sidebar_label: "Learning more" ---- - -After building your first models, testing and documenting your project, and scheduling a job, you can explore different ways to enhance your dbt skills. - -To learn more: - -* Connect to dbt Core using the command line interface -* Refactor legacy SQL -* Learn how to use Jinja diff --git a/website/docs/guides/legacy/best-practices.md b/website/docs/guides/legacy/best-practices.md index 969886da238..f80cfda5a0d 100644 --- a/website/docs/guides/legacy/best-practices.md +++ b/website/docs/guides/legacy/best-practices.md @@ -16,7 +16,7 @@ We've codified our best practices in Git, in our [Git guide](https://github.com/ ::: ### Use separate development and production environments -dbt makes it easy to maintain separate production and development environments through the use of target within a profile. We recommend using a `dev` target when running dbt from your command line, and only running against a `prod` target when running from a production deployment. You can read more [about managing environments](managing-environments). +dbt makes it easy to maintain separate production and development environments through the use of target within a profile. We recommend using a `dev` target when running dbt from your command line, and only running against a `prod` target when running from a production deployment. You can read more [about managing environments](/docs/collaborate/environments). ### Use a style guide and for your project SQL styles, field naming conventions, and other rules for your dbt project should be codified, especially on projects where multiple dbt users are writing code. @@ -87,7 +87,8 @@ Our [style guide](https://github.com/dbt-labs/corp/blob/main/dbt_style_guide.md) ### Consider the information architecture of your data warehouse When a user connects to a via a SQL client, they often rely on the names of schemas, relations, and columns, to understand the data they are presented with. To improve the information architecture of a data warehouse, we: -* Use [custom schemas](using-custom-schemas) to separate relations into logical groupings, or hide intermediate models in a separate schema. Generally, these custom schemas align with the directories we use to group our models, and are configured from the `dbt_project.yml` file. + +* Use [custom schemas](/docs/build/custom-schemas) to separate relations into logical groupings, or hide intermediate models in a separate schema. Generally, these custom schemas align with the directories we use to group our models, and are configured from the `dbt_project.yml` file. * Use prefixes in names (for example, `stg_`, `fct_` and `dim_`) to indicate which relations should be queried by end users. ### Choose your materializations wisely diff --git a/website/docs/guides/legacy/building-packages.md b/website/docs/guides/legacy/building-packages.md index bf29a0b0479..32c09fabdbf 100644 --- a/website/docs/guides/legacy/building-packages.md +++ b/website/docs/guides/legacy/building-packages.md @@ -92,7 +92,7 @@ dbt makes it possible for users of your package to override your model - -Usually these are write-ups where there is no one perfect answer (unlike the “I’m stuck” questions on Stack Overflow), instead, you might need to dig into the “why” or discuss tradeoffs of your approach in these articles. - - -### dbt Blog -_[blog.getdbt.com](https://blog.getdbt.com/)_ - -Strategy oriented - -Bigger picture approaches, where the content is relevant to most data practitioners, not just for dbt users - -### Slack -_Sign up at [community.getdbt.com](https://community.getdbt.com/)_ - -Community oriented - -Create connections with other analytics engineers. Discuss ideas that require opinions, or push the boundaries of what has been done before. diff --git a/website/docs/guides/migration/versions/05-upgrading-to-v1.3.md b/website/docs/guides/migration/versions/05-upgrading-to-v1.3.md index 3ae8017d294..81ec124e3c4 100644 --- a/website/docs/guides/migration/versions/05-upgrading-to-v1.3.md +++ b/website/docs/guides/migration/versions/05-upgrading-to-v1.3.md @@ -4,14 +4,14 @@ title: "Upgrading to v1.3 (latest)" ### Resources - [Changelog](https://github.com/dbt-labs/dbt-core/blob/1.3.latest/CHANGELOG.md) -- [CLI Installation guide](/dbt-cli/install/overview) -- [Cloud upgrade guide](/docs/dbt-cloud/cloud-configuring-dbt-cloud/cloud-choosing-a-dbt-version) +- [CLI Installation guide](/docs/get-started/installation) +- [Cloud upgrade guide](/docs/dbt-versions/upgrade-core-in-cloud) ## Breaking changes There are no breaking changes for code in dbt projects and packages. We are committed to providing backward compatibility for all versions 1.x. If you encounter an error upon upgrading, please let us know by [opening an issue](https://github.com/dbt-labs/dbt-core/issues/new). -**Note:** If you have custom code accessing the `raw_sql` property of models (via the [`model`](dbt-jinja-functions/model) or [`graph`](https://docs.getdbt.com/reference/dbt-jinja-functions/graph) objects), it has been renamed to `raw_code`. This is a change to the manifest contract, described in more detail below. +**Note:** If you have custom code accessing the `raw_sql` property of models (with the [model](dbt-jinja-functions/model) or [graph](/reference/dbt-jinja-functions/graph) objects), it has been renamed to `raw_code`. This is a change to the manifest contract, described in more detail below. ### For users of dbt Metrics diff --git a/website/docs/guides/migration/versions/06-upgrading-to-v1.2.md b/website/docs/guides/migration/versions/06-upgrading-to-v1.2.md index e628ae4a64e..28cc3d11890 100644 --- a/website/docs/guides/migration/versions/06-upgrading-to-v1.2.md +++ b/website/docs/guides/migration/versions/06-upgrading-to-v1.2.md @@ -4,8 +4,8 @@ title: "Upgrading to v1.2" ### Resources - [Changelog](https://github.com/dbt-labs/dbt-core/blob/1.2.latest/CHANGELOG.md) -- [CLI Installation guide](/dbt-cli/install/overview) -- [Cloud upgrade guide](/docs/dbt-cloud/cloud-configuring-dbt-cloud/cloud-choosing-a-dbt-version) +- [CLI Installation guide](/docs/get-started/installation) +- [Cloud upgrade guide](/docs/dbt-versions/upgrade-core-in-cloud) ## Breaking changes diff --git a/website/docs/guides/migration/versions/07-upgrading-to-v1.1.md b/website/docs/guides/migration/versions/07-upgrading-to-v1.1.md index 4ed1844cfdb..84612006d43 100644 --- a/website/docs/guides/migration/versions/07-upgrading-to-v1.1.md +++ b/website/docs/guides/migration/versions/07-upgrading-to-v1.1.md @@ -4,8 +4,8 @@ title: "Upgrading to v1.1" ### Resources - [Changelog](https://github.com/dbt-labs/dbt-core/blob/1.1.latest/CHANGELOG.md) -- [CLI Installation guide](/dbt-cli/install/overview) -- [Cloud upgrade guide](/docs/dbt-cloud/cloud-configuring-dbt-cloud/cloud-choosing-a-dbt-version) +- [CLI Installation guide](/docs/get-started/installation) +- [Cloud upgrade guide](/docs/dbt-versions/upgrade-core-in-cloud) ## Breaking changes diff --git a/website/docs/guides/migration/versions/08-upgrading-to-v1.0.md b/website/docs/guides/migration/versions/08-upgrading-to-v1.0.md index c7d94354fa2..40391af1da5 100644 --- a/website/docs/guides/migration/versions/08-upgrading-to-v1.0.md +++ b/website/docs/guides/migration/versions/08-upgrading-to-v1.0.md @@ -5,8 +5,8 @@ title: "Upgrading to v1.0" - [Discourse](https://discourse.getdbt.com/t/3180) - [Changelog](https://github.com/dbt-labs/dbt-core/blob/1.0.latest/CHANGELOG.md) -- [CLI Installation guide](/dbt-cli/install/overview) -- [Cloud upgrade guide](/docs/dbt-cloud/cloud-configuring-dbt-cloud/cloud-choosing-a-dbt-version) +- [CLI Installation guide](/docs/get-started/installation) +- [Cloud upgrade guide](/docs/dbt-versions/upgrade-core-in-cloud) ## Breaking changes @@ -26,7 +26,7 @@ dbt Core major version 1.0 includes a number of breaking changes! Wherever possi ### Tests -The two **test types** are now "singular" and "generic" (instead of "data" and "schema", respectively). The `test_type:` selection method accepts `test_type:singular` and `test_type:generic`. (It will also accept `test_type:schema` and `test_type:data` for backwards compatibility.) **Not backwards compatible:** The `--data` and `--schema` flags to dbt test are no longer supported, and tests no longer have the tags `'data'` and `'schema'` automatically applied. Updated docs: [tests](building-a-dbt-project/tests), [test selection](test-selection-examples), [selection methods](node-selection/methods). +The two **test types** are now "singular" and "generic" (instead of "data" and "schema", respectively). The `test_type:` selection method accepts `test_type:singular` and `test_type:generic`. (It will also accept `test_type:schema` and `test_type:data` for backwards compatibility.) **Not backwards compatible:** The `--data` and `--schema` flags to dbt test are no longer supported, and tests no longer have the tags `'data'` and `'schema'` automatically applied. Updated docs: [tests](/docs/build/tests), [test selection](test-selection-examples), [selection methods](node-selection/methods). The `greedy` flag/property has been renamed to **`indirect_selection`**, which is now eager by default. **Note:** This reverts test selection to its pre-v0.20 behavior by default. `dbt test -s my_model` _will_ select multi-parent tests, such as `relationships`, that depend on unselected resources. To achieve the behavior change in v0.20 + v0.21, set `--indirect-selection=cautious` on the CLI or `indirect_selection: cautious` in yaml selectors. Updated docs: [test selection examples](test-selection-examples), [yaml selectors](yaml-selectors) diff --git a/website/docs/guides/migration/versions/10-upgrading-to-v0.20.md b/website/docs/guides/migration/versions/10-upgrading-to-v0.20.md index 6dcd5c0fa47..2fdf9c00256 100644 --- a/website/docs/guides/migration/versions/10-upgrading-to-v0.20.md +++ b/website/docs/guides/migration/versions/10-upgrading-to-v0.20.md @@ -23,7 +23,8 @@ dbt Core v0.20 has reached the end of critical support. No new patch versions wi ## New and changed documentation ### Tests -- [Building a dbt Project: tests](building-a-dbt-project/tests) + +- [Building a dbt Project: tests](/docs/build/tests) - [Test Configs](test-configs) - [Test properties](resource-properties/tests) - [Node Selection](node-selection/syntax) (with updated [test selection examples](test-selection-examples)) diff --git a/website/docs/guides/migration/versions/11-Older versions/upgrading-to-0-14-0.md b/website/docs/guides/migration/versions/11-Older versions/upgrading-to-0-14-0.md index 8a1a5faa458..c22bd1490bb 100644 --- a/website/docs/guides/migration/versions/11-Older versions/upgrading-to-0-14-0.md +++ b/website/docs/guides/migration/versions/11-Older versions/upgrading-to-0-14-0.md @@ -118,7 +118,7 @@ alter table archived.orders_archived rename "scd_id" to dbt_scd_id; ## Upgrading the generate_schema_name signature -In dbt v0.14.0, the `generate_schema_name` macro signature was changed to accept a second argument, `node`. For more information on the new `node` argument, consulting the documentation for [using custom schemas](using-custom-schemas). +In dbt v0.14.0, the `generate_schema_name` macro signature was changed to accept a second argument, `node`. For more information on the new `node` argument, consulting the documentation for [using custom schemas](/docs/build/custom-schemas). Existing one-argument implementations of `generate_schema_name` macros are still supported, but support for this form of the macro will be dropped in a future release. If you currently have a one-argument version of this macro, you will see a warning when you run your dbt project. diff --git a/website/docs/guides/migration/versions/11-Older versions/upgrading-to-0-16-0.md b/website/docs/guides/migration/versions/11-Older versions/upgrading-to-0-16-0.md index 9590eca0379..242de3d1b8d 100644 --- a/website/docs/guides/migration/versions/11-Older versions/upgrading-to-0-16-0.md +++ b/website/docs/guides/migration/versions/11-Older versions/upgrading-to-0-16-0.md @@ -28,7 +28,7 @@ information on the change. ### One-argument generate_schema_name deprecation Support for the one-argument variant of `generate_schema_name` macros (deprecated in a previous release) are no longer supported. If you are using the one-argument -variant of `generate_schema_name`, see [the docs on custom schemas](using-custom-schemas) +variant of `generate_schema_name`, see [the docs on custom schemas](/docs/build/custom-schemas) for an example of how to use the two-argument variant of `generate_schema_name`. ### BigQuery partition_by syntax diff --git a/website/docs/guides/orchestration/airflow-and-dbt-cloud/1-airflow-and-dbt-cloud.md b/website/docs/guides/orchestration/airflow-and-dbt-cloud/1-airflow-and-dbt-cloud.md index ee9650fae7d..86a5c669be6 100644 --- a/website/docs/guides/orchestration/airflow-and-dbt-cloud/1-airflow-and-dbt-cloud.md +++ b/website/docs/guides/orchestration/airflow-and-dbt-cloud/1-airflow-and-dbt-cloud.md @@ -48,7 +48,7 @@ While you’re learning the ropes, you’ll also gain a better understanding of ### Prerequisites -- [dbt Cloud Teams or Enterprise account](https://www.getdbt.com/pricing/) (with [admin access](https://docs.getdbt.com/docs/dbt-cloud/access-control/enterprise-permissions)) in order to create a service token. Permissions for service tokens can be found [here](https://docs.getdbt.com/docs/dbt-cloud/dbt-cloud-api/service-tokens#permissions-for-service-account-tokens). +- [dbt Cloud Teams or Enterprise account](https://www.getdbt.com/pricing/) (with [admin access](https://docs.getdbt.com/docs/collaborate/manage-access/enterprise-permissions)) in order to create a service token. Permissions for service tokens can be found [here](https://docs.getdbt.com/docs/dbt-cloud-apis/service-tokens#permissions-for-service-account-tokens). - A [free Docker account](https://hub.docker.com/signup) in order to sign in to Docker Desktop, which will be installed in the initial setup. - A local digital scratchpad for temporarily copy-pasting API keys and URLs diff --git a/website/docs/guides/orchestration/airflow-and-dbt-cloud/2-setting-up-airflow-and-dbt-cloud.md b/website/docs/guides/orchestration/airflow-and-dbt-cloud/2-setting-up-airflow-and-dbt-cloud.md index cb5895e80f4..165d7ea3610 100644 --- a/website/docs/guides/orchestration/airflow-and-dbt-cloud/2-setting-up-airflow-and-dbt-cloud.md +++ b/website/docs/guides/orchestration/airflow-and-dbt-cloud/2-setting-up-airflow-and-dbt-cloud.md @@ -46,9 +46,9 @@ cd airflow-dbt-cloud ```bash Airflow is starting up! This might take a few minutes… - + Project is running! All components are now available. - + Airflow Webserver: http://localhost:8080 Postgres Database: localhost:5432/postgres The default Airflow UI credentials are: admin:admin @@ -68,13 +68,13 @@ cd airflow-dbt-cloud ## 5. Create a dbt Cloud service token -Create a service token from within dbt Cloud using the instructions [found here](https://docs.getdbt.com/docs/dbt-cloud/dbt-cloud-api/service-tokens). Ensure that you save a copy of the token, as you won’t be able to access this later. In this example we use `Account Admin`, but you can also use `Job Admin` instead for token permissions. +Create a service token from within dbt Cloud using the instructions [found here](https://docs.getdbt.com/docs/dbt-cloud-apis/service-tokens). Ensure that you save a copy of the token, as you won’t be able to access this later. In this example we use `Account Admin`, but you can also use `Job Admin` instead for token permissions. ## 6. Create a dbt Cloud job -In your dbt Cloud account create a job, paying special attention to the information in the bullets below. Additional information for creating a dbt Cloud job can be found [here](https://docs.getdbt.com/docs/dbt-cloud/cloud-quickstart/#create-a-new-job). +In your dbt Cloud account create a job, paying special attention to the information in the bullets below. Additional information for creating a dbt Cloud job can be found [here](https://docs.getdbt.com/docs/get-started/getting-started/building-your-first-project/schedule-a-job). - Configure the job with the commands that you want to include when this job kicks off, as Airflow will be referring to the job’s configurations for this rather than being explicitly coded in the Airflow DAG. This job will run a set of commands rather than a single command. - Ensure that the schedule is turned **off** since we’ll be using Airflow to kick things off. diff --git a/website/docs/guides/orchestration/custom-cicd-pipelines/3-dbt-cloud-job-on-merge.md b/website/docs/guides/orchestration/custom-cicd-pipelines/3-dbt-cloud-job-on-merge.md index 3e3447ec403..042e6ea3d61 100644 --- a/website/docs/guides/orchestration/custom-cicd-pipelines/3-dbt-cloud-job-on-merge.md +++ b/website/docs/guides/orchestration/custom-cicd-pipelines/3-dbt-cloud-job-on-merge.md @@ -10,7 +10,7 @@ The setup below shows how to call the dbt Cloud API to run a job every time ther ### 1. Get your dbt Cloud API key -When running a CI/CD pipeline you’ll want to use a service token instead of any individual’s API key. There are [detailed docs](https://docs.getdbt.com/docs/dbt-cloud/dbt-cloud-api/service-tokens) available on this, but below is a quick rundown (this must be performed by an Account Admin): +When running a CI/CD pipeline you’ll want to use a service token instead of any individual’s API key. There are [detailed docs](https://docs.getdbt.com/docs/dbt-cloud-apis/service-tokens) available on this, but below is a quick rundown (this must be performed by an Account Admin): - Login to your dbt Cloud account - In the upper left, click the menu button, then *Account Settings* diff --git a/website/docs/reference/commands/test.md b/website/docs/reference/commands/test.md index f83b3f6dc30..27d6f62e260 100644 --- a/website/docs/reference/commands/test.md +++ b/website/docs/reference/commands/test.md @@ -27,4 +27,4 @@ dbt test --select one_specific_model,test_type:singular dbt test --select one_specific_model,test_type:generic ``` -For more information on writing tests, see the [Testing Documentation](building-a-dbt-project/tests). +For more information on writing tests, see the [Testing Documentation](/docs/build/tests). diff --git a/website/docs/reference/configs-and-properties.md b/website/docs/reference/configs-and-properties.md index eec119badb9..658319639ef 100644 --- a/website/docs/reference/configs-and-properties.md +++ b/website/docs/reference/configs-and-properties.md @@ -15,7 +15,7 @@ A rule of thumb: properties declare things _about_ your project resources; confi For example, you can use resource **properties** to: * Describe models, snapshots, seed files, and their columns -* Assert "truths" about a model, in the form of [tests](building-a-dbt-project/tests), e.g. "this `id` column is unique" +- Assert "truths" about a model, in the form of [tests](/docs/build/tests), e.g. "this `id` column is unique" * Define pointers to existing tables that contain raw data, in the form of [sources](using-sources), and assert the expected "freshness" of this raw data * Define official downstream uses of your data models, in the form of [exposures](exposures) diff --git a/website/docs/reference/dbt-jinja-functions/run_query.md b/website/docs/reference/dbt-jinja-functions/run_query.md index e23a836fe1f..ad2de09b080 100644 --- a/website/docs/reference/dbt-jinja-functions/run_query.md +++ b/website/docs/reference/dbt-jinja-functions/run_query.md @@ -13,7 +13,7 @@ Returns a [Table](https://agate.readthedocs.io/page/api/table.html) object with **Note:** The `run_query` macro will not begin a transaction automatically - if you wish to run your query inside of a transaction, please use `begin` and `commit ` statements as appropriate. :::info Using run_query for the first time? -Check out the section of the Getting Started guide on [using Jinja](/guides/getting-started/learning-more/using-jinja#dynamically-retrieve-the-list-of-payment-methods) for an example of working with the results of the `run_query` macro! +Check out the section of the Getting Started guide on [using Jinja](/docs/get-started/learning-more/using-jinja#dynamically-retrieve-the-list-of-payment-methods) for an example of working with the results of the `run_query` macro! ::: **Example Usage:** diff --git a/website/docs/reference/dbt-jinja-functions/schemas.md b/website/docs/reference/dbt-jinja-functions/schemas.md index 35b45dfa818..4047d0ef856 100644 --- a/website/docs/reference/dbt-jinja-functions/schemas.md +++ b/website/docs/reference/dbt-jinja-functions/schemas.md @@ -5,7 +5,7 @@ id: "schemas" `schemas` is a variable available in an `on-run-end` hook, representing a list of schemas that dbt built objects in on this run. -If you do not use [custom schemas](using-custom-schemas), `schemas` will evaluate to your target schema, e.g. `['dbt_alice']`. If you use custom schemas, it will include these as well, e.g. `['dbt_alice', 'dbt_alice_marketing', 'dbt_alice_finance']`. +If you do not use [custom schemas](/docs/build/custom-schemas), `schemas` will evaluate to your target schema, e.g. `['dbt_alice']`. If you use custom schemas, it will include these as well, e.g. `['dbt_alice', 'dbt_alice_marketing', 'dbt_alice_finance']`. The `schemas` variable is useful for granting privileges to all schemas that dbt builds relations in, like so (note this is Redshift specific syntax): diff --git a/website/docs/reference/global-configs.md b/website/docs/reference/global-configs.md index eaf2ef1785d..4afc5cf09b1 100644 --- a/website/docs/reference/global-configs.md +++ b/website/docs/reference/global-configs.md @@ -186,7 +186,7 @@ config: ### Failing fast -Supply the `-x` or `--fail-fast` flag to `dbt run` to make dbt exit immediately if a single resource fails to build. If other models are in-progress when the first model fails, then dbt will terminate the connections for these still-running models. +Supply the `-x` or `--fail-fast` flag to `dbt run` to make dbt exit immediately if a single resource fails to build. If other models are in-progress when the first model fails, then dbt will terminate the connections for these still-running models. For example, you can select four models to run, but if a failure occurs in the first model, the failure will prevent other models from running: @@ -307,7 +307,7 @@ config: send_anonymous_usage_stats: False ``` -You can also use the DO_NOT_TRACK environmental variable to enable or disable sending anonymous data. For more information, see [Environmental variables](/dbt-cloud/using-dbt-cloud/cloud-environment-variables). +You can also use the DO_NOT_TRACK environmental variable to enable or disable sending anonymous data. For more information, see [Environmental variables](/docs/build/environment-variables). `DO_NOT_TRACK=1` is the same as `DBT_SEND_ANONYMOUS_USAGE_STATS=False` `DO_NOT_TRACK=0` is the same as `DBT_SEND_ANONYMOUS_USAGE_STATS=True` diff --git a/website/docs/reference/node-selection/methods.md b/website/docs/reference/node-selection/methods.md index 90ea7455466..d56a9e80165 100644 --- a/website/docs/reference/node-selection/methods.md +++ b/website/docs/reference/node-selection/methods.md @@ -196,7 +196,7 @@ The `test_type` method is used to select tests based on their type, `singular` o The `test_name` method is used to select tests based on the name of the generic test that defines it. For more information about how generic tests are defined, read about -[tests](building-a-dbt-project/tests). +[tests](/docs/build/tests). diff --git a/website/docs/reference/node-selection/syntax.md b/website/docs/reference/node-selection/syntax.md index b95dfdaacfa..5787ca3355b 100644 --- a/website/docs/reference/node-selection/syntax.md +++ b/website/docs/reference/node-selection/syntax.md @@ -114,3 +114,6 @@ dbt supports a shorthand language for defining subsets of nodes. This language u As your selection logic gets more complex, and becomes unwieldly to type out as command-line arguments, consider using a [yaml selector](yaml-selectors). You can use a predefined definition with the `--selector` flag. Note that when you're using `--selector`, most other flags (namely `--select` and `--exclude`) will be ignored. + + + diff --git a/website/docs/reference/project-configs/test-paths.md b/website/docs/reference/project-configs/test-paths.md index 4d99774b5ab..eec360663d9 100644 --- a/website/docs/reference/project-configs/test-paths.md +++ b/website/docs/reference/project-configs/test-paths.md @@ -18,7 +18,7 @@ test-paths: [directorypath] ## Definition -Optionally specify a custom list of directories where [data tests](docs/building-a-dbt-project/tests#data-tests) are located. +Optionally specify a custom list of directories where [data tests](/docs/build/tests) are located. ## Default Without specifying this config, dbt will search for tests in the `tests` directory, i.e. `test-paths: ["tests"]`. Specifically, it will look for `.sql` files containing: diff --git a/website/docs/reference/project-configs/version.md b/website/docs/reference/project-configs/version.md index 31d91ad9c82..346f1f85fef 100644 --- a/website/docs/reference/project-configs/version.md +++ b/website/docs/reference/project-configs/version.md @@ -7,7 +7,7 @@ dbt projects have two distinct types of the `version` tags. This field has a dif ## `dbt_project.yml` versions -The version tag in a `dbt_project` file represents the version of your dbt project. Although **this is a required parameter**, it is not currently meaningfully used by dbt. The version must be in a [semantic version](https://semver.org/) format, e.g. `1.0.0`. For more on Core versions, see "[About dbt Core versions](/docs/core-versions)." +The version tag in a `dbt_project` file represents the version of your dbt project. Although **this is a required parameter**, it is not currently meaningfully used by dbt. The version must be in a [semantic version](https://semver.org/) format, e.g. `1.0.0`. For more on Core versions, see [About dbt Core versions](/docs/dbt-versions/core). ```yml @@ -29,7 +29,5 @@ For more on property files, see their general [documentation](reference/configs- ```yml version: 2 # Only 2 is accepted by current and recent versions of dbt. ``` - - - + diff --git a/website/docs/reference/resource-configs/grants.md b/website/docs/reference/resource-configs/grants.md index 197bd76aad8..e38372ca38c 100644 --- a/website/docs/reference/resource-configs/grants.md +++ b/website/docs/reference/resource-configs/grants.md @@ -17,8 +17,8 @@ dbt encourages you to use grants as resource configs whenever possible in Core v * Apply grants on other database objects besides views and tables. * Take advantage of more-advanced permission capabilities offered by your data platform, for which dbt does not (yet!) offer out-of-the-box support using resource configuration. * Create more granular row- and column-level access, use masking policies, or apply future grants. - -For more information on hooks, see [Hooks & operations](/building-a-dbt-project/hooks-operations). + +For more information on hooks, see [Hooks & operations](/docs/build/hooks-operations). ## Definition @@ -26,7 +26,7 @@ You can use the `grants` field to set permissions or grants for a resource. When Like all configurations, `grants` will be included in dbt project metadata, including [the manifest artifact](dbt-artifacts/manifest-json). -### Common syntax +### Common syntax Grants have two key components: @@ -113,7 +113,7 @@ See [configs and properties](configs-and-properties) for details. ### Grant config inheritance -When you set `grants` for the same model in multiple places, such as in `dbt_project.yml` and in a more-specific `.sql` or `.yml` file, dbt's default behavior replaces the less-specific set of grantees with the more-specific set of grantees. This "merge and clobber" behavior updates each privilege when dbt parses your project. +When you set `grants` for the same model in multiple places, such as in `dbt_project.yml` and in a more-specific `.sql` or `.yml` file, dbt's default behavior replaces the less-specific set of grantees with the more-specific set of grantees. This "merge and clobber" behavior updates each privilege when dbt parses your project. For example: diff --git a/website/docs/reference/resource-configs/schema.md b/website/docs/reference/resource-configs/schema.md index ce055c9a038..3edb96f2ea6 100644 --- a/website/docs/reference/resource-configs/schema.md +++ b/website/docs/reference/resource-configs/schema.md @@ -9,7 +9,7 @@ This is a work in progress document. While this configuration applies to multipl ::: ## Definition -Optionally specify a custom schema for a [model](docs/building-a-dbt-project/building-models) or [seed](docs/building-a-dbt-project/seeds). (To specify a schema for a [snapshot](snapshots), use the [`target_schema` config](target_schema)). +Optionally specify a custom schema for a [model](/docs/build/sql-models) or [seed](/docs/build/seeds). (To specify a schema for a [snapshot](snapshots), use the [`target_schema` config](target_schema)). When dbt creates a relation (/) in a database, it creates it as: `{{ database }}.{{ schema }}.{{ identifier }}`, e.g. `analytics.finance.payments` @@ -17,7 +17,7 @@ The standard behavior of dbt is: * If a custom schema is _not_ specified, the schema of the relation is the target schema (`{{ target.schema }}`). * If a custom schema is specified, by default, the schema of the relation is `{{ target.schema }}_{{ schema }}`. -To learn more about changing the way that dbt generates a relation's `schema`, read [Using Custom Schemas](docs/building-a-dbt-project/building-models/using-custom-schemas) +To learn more about changing the way that dbt generates a relation's `schema`, read [Using Custom Schemas](/docs/build/custom-schemas) ## Usage diff --git a/website/docs/reference/resource-configs/target_schema.md b/website/docs/reference/resource-configs/target_schema.md index 3fbb1510d78..9d8eeb33b51 100644 --- a/website/docs/reference/resource-configs/target_schema.md +++ b/website/docs/reference/resource-configs/target_schema.md @@ -66,7 +66,7 @@ snapshots: ### Use the same schema-naming behavior as models -Leverage the [`generate_schema_name` macro](using-custom-schemas) to build snapshots in schemas that follow the same naming behavior as your models. +Leverage the [`generate_schema_name` macro](/docs/build/custom-schemas) to build snapshots in schemas that follow the same naming behavior as your models. Notes: * This macro is not available when configuring from the `dbt_project.yml` file, so must be configured in a snapshot config block. diff --git a/website/docs/reference/resource-properties/tests.md b/website/docs/reference/resource-properties/tests.md index a77e18c096c..87bf7bfd54c 100644 --- a/website/docs/reference/resource-properties/tests.md +++ b/website/docs/reference/resource-properties/tests.md @@ -148,11 +148,12 @@ This feature is not implemented for analyses. ## Related documentation -* [Testing guide](building-a-dbt-project/tests) + +* [Testing guide](/docs/build/tests) ## Description -The `tests` property defines assertions about a column, , or . The property contains a list of [generic tests](building-a-dbt-project/tests#generic-tests), referenced by name, which can include the four built-in generic tests available in dbt. For example, you can add tests that ensure a column contains no duplicates and zero null values. Any arguments or [configurations](test-configs) passed to those tests should be nested below the test name. +The `tests` property defines assertions about a column, , or . The property contains a list of [generic tests](/docs/build/tests#generic-tests), referenced by name, which can include the four built-in generic tests available in dbt. For example, you can add tests that ensure a column contains no duplicates and zero null values. Any arguments or [configurations](test-configs) passed to those tests should be nested below the test name. Once these tests are defined, you can validate their correctness by running `dbt test`. diff --git a/website/docs/reference/test-configs.md b/website/docs/reference/test-configs.md index 885718c2ebb..88255e62189 100644 --- a/website/docs/reference/test-configs.md +++ b/website/docs/reference/test-configs.md @@ -3,7 +3,8 @@ title: Test configurations --- ## Related documentation -* [Tests](building-a-dbt-project/tests) + +* [Tests](/docs/build/tests) diff --git a/website/docs/reference/warehouse-setups/snowflake-setup.md b/website/docs/reference/warehouse-setups/snowflake-setup.md index 6486f1e1752..a22f679e208 100644 --- a/website/docs/reference/warehouse-setups/snowflake-setup.md +++ b/website/docs/reference/warehouse-setups/snowflake-setup.md @@ -203,7 +203,7 @@ The "base" configs for Snowflake targets are shown below. Note that you should a | user | Yes | The user to log in as | | database | Yes | The database that dbt should create models in | | warehouse | Yes | The warehouse to use when building models | -| schema | Yes | The schema to build models into by default. Can be overridden with [custom schemas](using-custom-schemas) | +| schema | Yes | The schema to build models into by default. Can be overridden with [custom schemas](/docs/build/custom-schemas) | | role | No (but recommended) | The role to assume when running queries as the specified user. | | client_session_keep_alive | No | If `True`, the snowflake client will keep connections for longer than the default 4 hours. This is helpful when particularly long-running queries are executing (> 4 hours). Default: False (see [note below](#client_session_keep_alive)) | | threads | No | The number of concurrent models dbt should build. Set this to a higher number if using a bigger warehouse. Default=1 | diff --git a/website/docs/terms/cte.md b/website/docs/terms/cte.md index e6fe678fce7..2489b623b7d 100644 --- a/website/docs/terms/cte.md +++ b/website/docs/terms/cte.md @@ -66,7 +66,7 @@ When people talk about how CTEs can simplify your queries, they specifically mea #### Establish Structure -In leveraging CTEs, you can break complex code into smaller segments, ultimately helping provide structure to your code. At dbt Labs, we often like to use the [import, logical, and final structure](guides/getting-started/learning-more/refactoring-legacy-sql#implement-cte-groupings) for CTEs which creates a predictable and organized structure to your dbt models. +In leveraging CTEs, you can break complex code into smaller segments, ultimately helping provide structure to your code. At dbt Labs, we often like to use the [import, logical, and final structure](/docs/get-started/learning-more/refactoring-legacy-sql#implement-cte-groupings) for CTEs which creates a predictable and organized structure to your dbt models. #### Easily identify dependencies @@ -177,11 +177,11 @@ CTEs are likely to be supported across most, if not all, [modern data warehouses CTEs are essentially temporary views that can be used throughout a query. They are a great way to give your SQL more structure and readability, and offer simplified ways to debug your code. You can leverage appropriately-named CTEs to easily identify upstream dependencies and code functionality. CTEs also support recursiveness and reusability in the same query. Overall, CTEs can be an effective way to level-up your SQL to be more organized and understandable. -## Futher Reading +## Further Reading If you’re interested in reading more about CTE best practices, check out some of our favorite content around model refactoring and style: -- [Refactoring Legacy SQL to dbt](guides/getting-started/learning-more/refactoring-legacy-sql#implement-cte-groupings) +- [Refactoring Legacy SQL to dbt](/docs/get-started/learning-more/refactoring-legacy-sql#implement-cte-groupings) - [dbt Labs Style Guide](https://github.com/dbt-labs/corp/blob/main/dbt_style_guide.md#ctes) - [Modular Data Modeling Technique](https://www.getdbt.com/analytics-engineering/modular-data-modeling-technique/) diff --git a/website/docs/terms/dag.md b/website/docs/terms/dag.md index f70f2539f14..b3cd550e580 100644 --- a/website/docs/terms/dag.md +++ b/website/docs/terms/dag.md @@ -89,7 +89,7 @@ The DAG is also [available in the dbt Cloud IDE](https://www.getdbt.com/blog/on- :::tip Leverage exposures -One of the newer features of dbt is [exposures](https://docs.getdbt.com/docs/building-a-dbt-project/exposures), which allow you to define downstream use of your data models outside of your dbt project *within your dbt project*. What does this mean? This means you can add key dashboards, machine learning or data science pipelines, reverse ETL syncs, or other downstream use cases to your dbt project’s DAG. +One of the newer features of dbt is [exposures](https://docs.getdbt.com/docs/build/exposures), which allow you to define downstream use of your data models outside of your dbt project *within your dbt project*. What does this mean? This means you can add key dashboards, machine learning or data science pipelines, reverse ETL syncs, or other downstream use cases to your dbt project’s DAG. This level of interconnectivity and transparency can help boost data governance (who has access to and who [owns](https://docs.getdbt.com/reference/resource-configs/meta#designate-a-model-owner) this data) and transparency (what are the data sources and models affecting your key reports). @@ -108,4 +108,4 @@ Ready to restructure (or create your first) DAG? Check out some of the resources - [Data modeling techniques for more modularity](https://www.getdbt.com/analytics-engineering/modular-data-modeling-technique/) - [How we structure our dbt projects](https://docs.getdbt.com/guides/best-practices/how-we-structure/1-guide-overview) - [How to audit your DAG](https://www.youtube.com/watch?v=5W6VrnHVkCA) -- [Refactoring legacy SQL to dbt](https://docs.getdbt.com/guides/getting-started/learning-more/refactoring-legacy-sql) +- [Refactoring legacy SQL to dbt](/docs/get-started/learning-more/refactoring-legacy-sql) diff --git a/website/docs/terms/data-lineage.md b/website/docs/terms/data-lineage.md index 41b6b4426f4..a17dec4dca4 100644 --- a/website/docs/terms/data-lineage.md +++ b/website/docs/terms/data-lineage.md @@ -87,7 +87,7 @@ The biggest challenges around data lineage become more apparent as your data, sy ### **Scaling data pipelines** -As dbt projects scale with data and organization growth, the number of sources, models, macros, seeds, and [exposures](https://docs.getdbt.com/docs/building-a-dbt-project/exposures) invariably grow. And with an increasing number of nodes in your DAG, it can become harder to audit your DAG for WET code or inefficiencies. +As dbt projects scale with data and organization growth, the number of sources, models, macros, seeds, and [exposures](https://docs.getdbt.com/docs/build/exposures) invariably grow. And with an increasing number of nodes in your DAG, it can become harder to audit your DAG for WET code or inefficiencies. Working with dbt projects with thousands of models and nodes can feel overwhelming, but remember: your DAG and data lineage are meant to help you, not be your enemy. Tackle DAG audits in chunks, document all models, and [leverage strong structure conventions](https://docs.getdbt.com/guides/best-practices/how-we-structure/1-guide-overview). diff --git a/website/docs/terms/primary-key.md b/website/docs/terms/primary-key.md index de4c84a92cb..2baa2ee8171 100644 --- a/website/docs/terms/primary-key.md +++ b/website/docs/terms/primary-key.md @@ -108,7 +108,7 @@ In general for Redshift, it’s still good practice to define your primary keys ### Google BigQuery -BigQuery is pretty unique here in that it doesn’t support or enforce primary keys. If your team is on BigQuery, you’ll need to have some [pretty solid testing](https://docs.getdbt.com/docs/building-a-dbt-project/tests) in place to ensure your primary key fields are unique and non-null. +BigQuery is pretty unique here in that it doesn’t support or enforce primary keys. If your team is on BigQuery, you’ll need to have some [pretty solid testing](/docs/build/tests) in place to ensure your primary key fields are unique and non-null. ### Databricks @@ -141,7 +141,7 @@ If you don't have a field in your table that would act as a natural primary key, If your data warehouse doesn’t provide out-of-the box support and enforcement for primary keys, it’s important to clearly label and put your own constraints on primary key fields. This could look like: * **Creating a consistent naming convention for your primary keys**: You may see an `id` field or fields prefixed with `pk_` (ex. `pk_order_id`) to identify primary keys. You may also see the primary key be named as the obvious table grain (ex. In the jaffle shop’s `orders` table, the primary key is called `order_id`). -* **Adding automated [tests](https://docs.getdbt.com/docs/building-a-dbt-project/tests) to your data models**: Use a data tool, such as dbt, to create not null and unique tests for your primary key fields. +* **Adding automated [tests](/docs/build/tests) to your data models**: Use a data tool, such as dbt, to create not null and unique tests for your primary key fields. ## Testing primary keys diff --git a/website/docs/terms/surrogate-key.md b/website/docs/terms/surrogate-key.md index f1cdfa2fafe..718d3f53c92 100644 --- a/website/docs/terms/surrogate-key.md +++ b/website/docs/terms/surrogate-key.md @@ -177,7 +177,7 @@ After executing this, the table would now have the `unique_id` field now uniquel Amazing, you just made a surrogate key! You can just move on to the next data model, right? No!! It’s critically important to test your surrogate keys for uniqueness and non-null values to ensure that the correct fields were chosen to create the surrogate key. -In order to test for null and unique values you can utilize code-based tests like [dbt tests](https://docs.getdbt.com/docs/building-a-dbt-project/tests), that can check fields for nullness and uniqueness. You can additionally utilize simple SQL queries or unit tests to check if surrogate key count and non-nullness is correct. +In order to test for null and unique values you can utilize code-based tests like [dbt tests](/docs/build/tests), that can check fields for nullness and uniqueness. You can additionally utilize simple SQL queries or unit tests to check if surrogate key count and non-nullness is correct. ## A note on hashing algorithms diff --git a/website/docusaurus.config.js b/website/docusaurus.config.js index ebdea716aea..de0caff1f33 100644 --- a/website/docusaurus.config.js +++ b/website/docusaurus.config.js @@ -1,37 +1,36 @@ -const path = require('path'); -const math = require('remark-math'); -const katex = require('rehype-katex'); -const { versions, versionedPages } = require('./dbt-versions'); -require('dotenv').config() - +const path = require("path"); +const math = require("remark-math"); +const katex = require("rehype-katex"); +const { versions, versionedPages } = require("./dbt-versions"); +require("dotenv").config(); /* Debugging */ var SITE_URL; -if (!process.env.CONTEXT || process.env.CONTEXT == 'production') { - SITE_URL = 'https://docs.getdbt.com'; +if (!process.env.CONTEXT || process.env.CONTEXT == "production") { + SITE_URL = "https://docs.getdbt.com"; } else { SITE_URL = process.env.DEPLOY_URL; } var GIT_BRANCH; -if (!process.env.CONTEXT || process.env.CONTEXT == 'production') { - GIT_BRANCH = 'current'; +if (!process.env.CONTEXT || process.env.CONTEXT == "production") { + GIT_BRANCH = "current"; } else { GIT_BRANCH = process.env.HEAD; } let { ALGOLIA_APP_ID, ALGOLIA_API_KEY, ALGOLIA_INDEX_NAME } = process.env; -let metatags = [] +let metatags = []; // If Not Current Branch, do not index site -if (GIT_BRANCH !== 'current') { +if (GIT_BRANCH !== "current") { metatags.push({ - tagName: 'meta', + tagName: "meta", attributes: { - name: 'robots', - content: 'noindex' - } - }) + name: "robots", + content: "noindex", + }, + }); } console.log("DEBUG: CONTEXT =", process.env.CONTEXT); @@ -41,26 +40,25 @@ console.log("DEBUG: ALGOLIA_INDEX_NAME = ", ALGOLIA_INDEX_NAME); console.log("DEBUG: metatags = ", metatags); var siteSettings = { - baseUrl: '/', - favicon: '/img/favicon.ico', - tagline: 'End user documentation, guides and technical reference for dbt', - title: 'dbt Docs', + baseUrl: "/", + tagline: "End user documentation, guides and technical reference for dbt", + title: "dbt Developer Hub", url: SITE_URL, - onBrokenLinks: 'warn', + onBrokenLinks: "warn", trailingSlash: false, themeConfig: { - image: '/img/avatar.png', + image: "/img/avatar.png", colorMode: { - defaultMode: 'light', + defaultMode: "light", disableSwitch: false, respectPrefersColorScheme: true, }, // Adding non-empty strings for Algolia config // allows Docusaurus to run locally without .env file algolia: { - apiKey: ALGOLIA_API_KEY ? ALGOLIA_API_KEY : 'dbt', - indexName: ALGOLIA_INDEX_NAME ? ALGOLIA_INDEX_NAME : 'dbt', - appId: ALGOLIA_APP_ID ? ALGOLIA_APP_ID : 'dbt' + apiKey: ALGOLIA_API_KEY ? ALGOLIA_API_KEY : "dbt", + indexName: ALGOLIA_INDEX_NAME ? ALGOLIA_INDEX_NAME : "dbt", + appId: ALGOLIA_APP_ID ? ALGOLIA_APP_ID : "dbt", //debug: true, }, announcementBar: { @@ -69,13 +67,13 @@ var siteSettings = { "Register now for Coalesce 2022. The Analytics Engineering Conference!", backgroundColor: "#047377", textColor: "#fff", - isCloseable: true + isCloseable: true, }, announcementBarActive: true, announcementBarLink: "https://coalesce.getdbt.com/", prism: { theme: (() => { - var theme = require('prism-react-renderer/themes/nightOwl'); + var theme = require("prism-react-renderer/themes/nightOwl"); // Add additional rule to nightowl theme in order to change // the color of YAML keys (to be different than values). // There weren't many Prism themes that differentiated @@ -86,92 +84,82 @@ var siteSettings = { style: { // color chosen from the nightowl theme palette // https://github.com/FormidableLabs/prism-react-renderer/blob/master/src/themes/nightOwl.js#L83 - color: "rgb(255, 203, 139)" - } + color: "rgb(255, 203, 139)", + }, }); - return theme + return theme; })(), - additionalLanguages: ['bash'], + additionalLanguages: ["bash"], }, navbar: { hideOnScroll: true, logo: { - src: '/img/dbt-logo.svg', - srcDark: 'img/dbt-logo-light.svg', - alt: 'dbt Logo', + src: "/img/dbt-logo.svg", + srcDark: "img/dbt-logo-light.svg", + alt: "dbt Logo", }, items: [ { - to: '/docs/introduction', - label: 'Docs', - position: 'left', - activeBaseRegex: 'docs\/(?!(dbt-cloud))', - }, - { - to: '/reference/dbt_project.yml', - label: 'Reference', - position: 'left', - activeBasePath: 'reference' - }, - { - to: '/dbt-cli/cli-overview', - label: 'dbt CLI', - position: 'left', - activeBasePath: 'dbt-cli' + to: "/docs/introduction", + label: "Docs", + position: "left", + activeBaseRegex: "docs/(?!(dbt-cloud))", }, { - to: '/docs/dbt-cloud/cloud-overview', - label: 'dbt Cloud', - position: 'left', - activeBasePath: 'docs/dbt-cloud' + to: "/reference/dbt_project.yml", + label: "Reference", + position: "left", + activeBasePath: "reference", }, { - to: '/guides/getting-started', - label: 'Guides', - position: 'left', - activeBasePath: 'guides' - }, - { - to: '/blog/', - label: 'Developer Blog', - position: 'right', - activeBasePath: 'blog' - }, - { - label: 'Courses', - position: 'right', + label: "Learn", + position: "right", items: [ { - label: 'Online courses', + label: 'Courses', href: 'https://courses.getdbt.com', }, { - label: 'Live courses', - href: 'https://learn.getdbt.com/public', + label: 'Guides', + to: '/guides/best-practices', + }, + { + label: "Developer Blog", + to: "/blog", + }, + { + label: "Glossary", + to: "/glossary", } ], }, { - label: 'Community', - position: 'right', + label: "Community", + position: "right", items: [ { - label: 'Maintaining a Slack Channel', - to: '/community/maintaining-a-channel', + label: "Join the Community", + to: "/community/join", }, { - label: 'dbt Slack', - href: 'https://community.getdbt.com/', + label: "Become a contributor", + to: "/community/contribute", }, { - label: 'Blog', - href: 'https://blog.getdbt.com', + label: "Community Forum", + to: "/community/forum", }, { - label: 'GitHub', - href: 'https://github.com/dbt-labs/dbt-core', + label: "Events", + to: "/community/events", }, - ] + ], + }, + { + label: "Create a free account", + to: "https://www.getdbt.com/signup/", + position: "right", + className: "nav-create-account button button--primary", }, ], }, @@ -184,114 +172,113 @@ var siteSettings = { Privacy Policy Security Terms of Service - +
- +
- ` + `, }, ], - copyright: `Copyright © ${new Date().getFullYear()} dbt Labs™, Inc. All Rights Reserved.` + copyright: `Copyright © ${new Date().getFullYear()} dbt Labs™, Inc. All Rights Reserved.`, }, }, presets: [ [ - '@docusaurus/preset-classic', + "@docusaurus/preset-classic", { theme: { - customCss: require.resolve('./src/css/custom.css'), + customCss: require.resolve("./src/css/custom.css"), }, docs: { - path: 'docs', - routeBasePath: '/', - sidebarPath: require.resolve('./sidebars.js'), + path: "docs", + routeBasePath: "/", + sidebarPath: require.resolve("./sidebars.js"), remarkPlugins: [math], rehypePlugins: [katex], - editUrl: 'https://github.com/dbt-labs/docs.getdbt.com/edit/' + GIT_BRANCH + '/website/', + editUrl: + "https://github.com/dbt-labs/docs.getdbt.com/edit/" + + GIT_BRANCH + + "/website/", showLastUpdateTime: true, //showLastUpdateAuthor: false, sidebarCollapsible: true, }, blog: { - blogTitle: 'dbt Developer Blog', - blogDescription: 'Technical tutorials from the dbt Community.', + blogTitle: "dbt Developer Blog", + blogDescription: "Technical tutorials from the dbt Community.", postsPerPage: 20, - blogSidebarTitle: 'Recent posts', + blogSidebarTitle: "Recent posts", blogSidebarCount: 5, remarkPlugins: [math], rehypePlugins: [katex], }, - }, ], ], plugins: [ - [ - path.resolve('plugins/insertMetaTags'), - { metatags } - ], - path.resolve('plugins/svg'), - path.resolve('plugins/customWebpackConfig'), - [ - path.resolve('plugins/buildGlobalData'), - { versionedPages } - ], - path.resolve('plugins/buildAuthorPages') + [path.resolve("plugins/insertMetaTags"), { metatags }], + path.resolve("plugins/svg"), + path.resolve("plugins/customWebpackConfig"), + [path.resolve("plugins/buildGlobalData"), { versionedPages }], + path.resolve("plugins/buildAuthorPages"), ], scripts: [ { - src: 'https://code.jquery.com/jquery-3.4.1.min.js', - defer: true + src: "https://code.jquery.com/jquery-3.4.1.min.js", + defer: true, }, { - src: 'https://cdn.jsdelivr.net/npm/featherlight@1.7.14/release/featherlight.min.js', - defer: true + src: "https://cdn.jsdelivr.net/npm/featherlight@1.7.14/release/featherlight.min.js", + defer: true, }, - '/js/gtm.js', - 'https://kit.fontawesome.com/7110474d41.js' + "/js/gtm.js", + "/js/onetrust.js", + "https://kit.fontawesome.com/7110474d41.js", ], stylesheets: [ - '/css/fonts.css', - '/css/entypo.css', - '/css/search.css', - '/css/api.css', - 'https://fonts.googleapis.com/css2?family=Source+Sans+Pro:wght@400;500;600;700&display=swap', - 'https://fonts.googleapis.com/css2?family=Source+Code+Pro:wght@400;500;600;700&display=swap', + "/css/fonts.css", + "/css/entypo.css", + "/css/search.css", + "/css/api.css", + "https://fonts.googleapis.com/css2?family=Source+Sans+Pro:wght@400;500;600;700&display=swap", + "https://fonts.googleapis.com/css2?family=Source+Code+Pro:wght@400;500;600;700&display=swap", { - href: 'https://cdn.jsdelivr.net/npm/katex@0.13.24/dist/katex.min.css', - type: 'text/css', + href: "https://cdn.jsdelivr.net/npm/katex@0.13.24/dist/katex.min.css", + type: "text/css", integrity: - 'sha384-odtC+0UGzzFL/6PNoE8rX/SPcQDXBJ+uRepguP4QkPCm2LBxH3FA3y+fKSiJ+AmM', - crossorigin: 'anonymous', + "sha384-odtC+0UGzzFL/6PNoE8rX/SPcQDXBJ+uRepguP4QkPCm2LBxH3FA3y+fKSiJ+AmM", + crossorigin: "anonymous", }, + {rel: 'icon', href: 'img/favicon.png', type: 'image/png'}, + {rel: 'icon', href: 'img/favicon.svg', type: 'image/svg+xml'}, ], -} +}; // If versions json file found, add versions dropdown to nav if (versions) { siteSettings.themeConfig.navbar.items.push({ - label: 'Versions', - position: 'left', - className: 'nav-versioning', + label: "Versions", + position: "left", + className: "nav-versioning", items: [ ...versions.reduce((acc, version) => { if (version?.version) { acc.push({ label: `${version.version}`, - href: '#', - }) + href: "#", + }); } - return acc - }, []) - ] - }) + return acc; + }, []), + ], + }); } module.exports = siteSettings; diff --git a/website/functions/get-discourse-topics.js b/website/functions/get-discourse-topics.js index 2ddc8cce8bf..3c447604250 100644 --- a/website/functions/get-discourse-topics.js +++ b/website/functions/get-discourse-topics.js @@ -40,6 +40,10 @@ async function getDiscourseTopics({ body }) { topic.like_count = firstTopicPost.like_count } + if(firstTopicPost?.blurb) { + topic.blurb = firstTopicPost.blurb + } + // Push updated topic to array topicsArr.push(topic) diff --git a/website/package-lock.json b/website/package-lock.json index 810006d5ee0..3dfb32e9e61 100644 --- a/website/package-lock.json +++ b/website/package-lock.json @@ -1,1090 +1,1623 @@ { + "name": "website", "version": "0.0.0", - "lockfileVersion": 1, + "lockfileVersion": 2, "requires": true, - "dependencies": { - "@algolia/autocomplete-core": { + "packages": { + "": { + "version": "0.0.0", + "dependencies": { + "@docusaurus/core": "2.0.0-beta.17", + "@docusaurus/plugin-ideal-image": "2.0.0-beta.17", + "@docusaurus/preset-classic": "2.0.0-beta.17", + "@docusaurus/theme-search-algolia": "2.0.0-beta.17", + "@mdx-js/react": "^1.6.21", + "@svgr/webpack": "^6.0.0", + "axios": "^0.27.2", + "classnames": "^2.3.1", + "clsx": "^1.1.1", + "color": "^3.1.2", + "core-js": "^3.20.0", + "file-loader": "^6.2.0", + "fs": "0.0.2", + "gray-matter": "^4.0.3", + "hast-util-is-element": "^1.1.0", + "js-yaml": "^4.1.0", + "mobx": "^6.3.9", + "node-polyfill-webpack-plugin": "^1.1.4", + "prism-react-renderer": "^1.2.1", + "react": "^17.0.1", + "react-dom": "^17.0.1", + "react-is": "^18.1.0", + "react-tooltip": "^4.2.21", + "redoc": "^2.0.0-rc.57", + "rehype-katex": "^5.0.0", + "remark-math": "^3.0.1", + "slugify": "^1.6.1", + "styled-components": "5.3.3", + "swiper": "^8.4.3", + "url-loader": "^4.1.1" + }, + "devDependencies": { + "@swc/core": "^1.2.174", + "@swc/jest": "^0.2.20", + "@testing-library/jest-dom": "^5.16.2", + "@testing-library/react": "^12.1.3", + "@testing-library/user-event": "^13.5.0", + "css-loader": "^3.4.2", + "cypress": "^10.3.0", + "dotenv": "^10.0.0", + "jest": "^27.5.1", + "jest-cli": "^27.5.1", + "path-browserify": "^1.0.1", + "process": "^0.11.10", + "stream-http": "^3.2.0", + "style-loader": "^1.1.3", + "svg-inline-loader": "^0.8.2", + "tty-browserify": "0.0.1" + } + }, + "node_modules/@algolia/autocomplete-core": { "version": "1.5.2", "resolved": "https://registry.npmjs.org/@algolia/autocomplete-core/-/autocomplete-core-1.5.2.tgz", "integrity": "sha512-DY0bhyczFSS1b/CqJlTE/nQRtnTAHl6IemIkBy0nEWnhDzRDdtdx4p5Uuk3vwAFxwEEgi1WqKwgSSMx6DpNL4A==", - "requires": { + "dependencies": { "@algolia/autocomplete-shared": "1.5.2" } }, - "@algolia/autocomplete-preset-algolia": { + "node_modules/@algolia/autocomplete-preset-algolia": { "version": "1.5.2", "resolved": "https://registry.npmjs.org/@algolia/autocomplete-preset-algolia/-/autocomplete-preset-algolia-1.5.2.tgz", "integrity": "sha512-3MRYnYQFJyovANzSX2CToS6/5cfVjbLLqFsZTKcvF3abhQzxbqwwaMBlJtt620uBUOeMzhdfasKhCc40+RHiZw==", - "requires": { + "dependencies": { "@algolia/autocomplete-shared": "1.5.2" + }, + "peerDependencies": { + "@algolia/client-search": "^4.9.1", + "algoliasearch": "^4.9.1" } }, - 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"xdg-basedir": { "version": "4.0.0", diff --git a/website/package.json b/website/package.json index 76648878a12..9b9f5bfbb96 100644 --- a/website/package.json +++ b/website/package.json @@ -11,8 +11,8 @@ "@docusaurus/preset-classic": "2.0.0-beta.17", "@docusaurus/theme-search-algolia": "2.0.0-beta.17", "@mdx-js/react": "^1.6.21", - "axios": "^0.27.2", "@svgr/webpack": "^6.0.0", + "axios": "^0.27.2", "classnames": "^2.3.1", "clsx": "^1.1.1", "color": "^3.1.2", @@ -34,6 +34,7 @@ "remark-math": "^3.0.1", "slugify": "^1.6.1", "styled-components": "5.3.3", + "swiper": "^8.4.3", "url-loader": "^4.1.1" }, "devDependencies": { diff --git a/website/sidebars.js b/website/sidebars.js index 621e4ddd0d9..a2f17a50e38 100644 --- a/website/sidebars.js +++ b/website/sidebars.js @@ -1,288 +1,379 @@ const sidebarSettings = { docs: [ + "docs/introduction", + "docs/supported-data-platforms", { type: "category", - label: "Introduction", - items: ["docs/introduction", "docs/supported-data-platforms", "docs/core-versions"], + label: "Get started with dbt", + collapsed: true, + items: [ + "docs/get-started/getting-started/overview", + { + type: "category", + label: "Get started with dbt Cloud", + collapsed: true, + items: [ + "docs/get-started/getting-started/set-up-dbt-cloud", + { + type: "category", + label: "Getting set up", + items: [ + "docs/get-started/getting-started/getting-set-up/setting-up-bigquery", + "docs/get-started/getting-started/getting-set-up/setting-up-databricks", + "docs/get-started/getting-started/getting-set-up/setting-up-redshift", + "docs/get-started/getting-started/getting-set-up/setting-up-snowflake", + ], + }, + { + type: "category", + label: "Building your first project", + + items: [ + "docs/get-started/getting-started/building-your-first-project/build-your-first-models", + "docs/get-started/getting-started/building-your-first-project/test-and-document-your-project", + "docs/get-started/getting-started/building-your-first-project/schedule-a-job", + ], + }, + { + type: "category", + label: "Learning more", + items: [ + "docs/get-started/learning-more/using-jinja", + "docs/get-started/learning-more/refactoring-legacy-sql", + ], + }, + "docs/get-started/dbt-cloud-features", + "docs/get-started/connect-your-database", + "docs/get-started/develop-in-the-cloud", + "docs/get-started/dbt-cloud-tips", + ], + }, + { + type: "category", + label: "Get started with dbt Core", + collapsed: true, + items: [ + "docs/get-started/getting-started-dbt-core", + { + type: "category", + label: "Install dbt Core", + collapsed: true, + items: [ + "docs/get-started/installation", + "docs/get-started/homebrew-install", + "docs/get-started/pip-install", + "docs/get-started/docker-install", + "docs/get-started/source-install", + ], + }, + "docs/get-started/about-the-cli", + "docs/get-started/connection-profiles", + ], + }, + "docs/get-started/run-your-dbt-projects", + ], }, { type: "category", - label: "Building a dbt Project", + label: "Build dbt projects", collapsed: true, items: [ - "docs/building-a-dbt-project/projects", + "docs/build/projects", + { + type: "category", + label: "Build your DAG", + collapsed: true, + items: [ + "docs/build/sources", + { + type: "category", + label: "Models", + items: [ + "docs/build/models", + "docs/build/sql-models", + "docs/build/python-models", + ], + }, + "docs/build/seeds", + "docs/build/snapshots", + "docs/build/exposures", + "docs/build/metrics", + ], + }, + { + type: "category", + label: "Enhance your models", + collapsed: true, + items: [ + "docs/build/tests", + "docs/build/materializations", + "docs/build/incremental-models", + ], + }, { type: "category", - label: "Models", + label: "Enhance your code", + collapsed: true, items: [ - "docs/building-a-dbt-project/building-models", - "docs/building-a-dbt-project/building-models/materializations", - "docs/building-a-dbt-project/building-models/configuring-incremental-models", - "docs/building-a-dbt-project/building-models/using-custom-aliases", - "docs/building-a-dbt-project/building-models/using-custom-schemas", - "docs/building-a-dbt-project/building-models/using-custom-databases", - "docs/building-a-dbt-project/building-models/using-variables", - "docs/building-a-dbt-project/building-models/python-models", + "docs/build/jinja-macros", + "docs/build/project-variables", + "docs/build/environment-variables", + "docs/build/packages", + "docs/build/analyses", + ], + }, + { + type: "category", + label: "Organize your outputs", + collapsed: true, + items: [ + "docs/build/custom-schemas", + "docs/build/custom-databases", + "docs/build/custom-aliases", + "docs/build/custom-target-names", + ], + }, + { + type: "category", + label: "Advanced workflows", + collapsed: true, + items: [ + { + type: "category", + label: "dbt Cloud APIs", + items: [ + "docs/dbt-cloud-apis/overview", + { + type: "category", + label: "Authentication", + items: [ + "docs/dbt-cloud-apis/user-tokens", + "docs/dbt-cloud-apis/service-tokens", + ], + }, + "docs/dbt-cloud-apis/admin-cloud-api", + { + type: "category", + label: "Metadata API", + items: [ + "docs/dbt-cloud-apis/metadata-api", + "docs/dbt-cloud-apis/metadata-querying", + { + type: "category", + label: "Schema", + items: [ + "docs/dbt-cloud-apis/metadata-schema-model", + "docs/dbt-cloud-apis/metadata-schema-models", + "docs/dbt-cloud-apis/metadata-schema-modelByEnv", + "docs/dbt-cloud-apis/metadata-schema-metric", + "docs/dbt-cloud-apis/metadata-schema-metrics", + "docs/dbt-cloud-apis/metadata-schema-source", + "docs/dbt-cloud-apis/metadata-schema-sources", + "docs/dbt-cloud-apis/metadata-schema-seed", + "docs/dbt-cloud-apis/metadata-schema-seeds", + "docs/dbt-cloud-apis/metadata-schema-snapshots", + "docs/dbt-cloud-apis/metadata-schema-test", + "docs/dbt-cloud-apis/metadata-schema-tests", + "docs/dbt-cloud-apis/metadata-schema-exposure", + "docs/dbt-cloud-apis/metadata-schema-exposures", + ], + }, + ], + }, + ], + }, + "docs/build/hooks-operations", ], }, - "docs/building-a-dbt-project/managing-environments", - "docs/building-a-dbt-project/tests", - "docs/building-a-dbt-project/documentation", - "docs/building-a-dbt-project/using-sources", - "docs/building-a-dbt-project/seeds", - "docs/building-a-dbt-project/snapshots", - "docs/building-a-dbt-project/exposures", - "docs/building-a-dbt-project/jinja-macros", - "docs/building-a-dbt-project/hooks-operations", //"docs/building-a-dbt-project/dont-nest-your-curlies", //"docs/building-a-dbt-project/archival", - "docs/building-a-dbt-project/package-management", - "docs/building-a-dbt-project/analyses", - "docs/building-a-dbt-project/metrics", ], }, { type: "category", - label: "Running a dbt Project", + label: "Deploy dbt projects", collapsed: true, items: [ - "docs/running-a-dbt-project/using-the-dbt-ide", - "docs/running-a-dbt-project/using-the-cli", - "docs/running-a-dbt-project/running-dbt-in-production", + "docs/deploy/deployments", + "docs/deploy/regions", + { + type: "category", + label: "dbt Cloud deploy options", + items: [ + "docs/deploy/architecture", + "docs/deploy/single-tenant", + "docs/deploy/multi-tenant", + ], + }, + { + type: "category", + label: "dbt Cloud production jobs", + items: [ + "docs/deploy/job-triggers", + "docs/deploy/job-notifications", + "docs/deploy/source-freshness", + "docs/deploy/dashboard-status-tiles", + ], + }, + "docs/deploy/cloud-ci-job", ], }, { type: "category", - label: "Contributing", + label: "Collaborate", items: [ - "docs/contributing/oss-expectations", - "docs/contributing/contributor-license-agreements", - "docs/contributing/slack-rules-of-the-road", - "docs/contributing/long-lived-discussions-guidelines", + "docs/collaborate/environments", { type: "category", - label: "Adapter development", - link: { - type: 'generated-index', - title: 'Adapter Development', - description: 'Learn what an adapter is what what\'s required to make one. Also how to build, test, document, promote, and verify your new adapter. Visit the [#adapter-ecosystem](https://getdbt.slack.com/archives/C030A0UF5LM) Slack channel for additional help beyond this section.', + label: "Git version control", + items: [ + "docs/collaborate/git-version-control", + "docs/collaborate/git/version-control-basics", + "docs/collaborate/git/managed-repository", + "docs/collaborate/git/pr-template", + "docs/collaborate/git/resolve-merge-conflicts", + { + type: "category", + label: "Supported git providers", + items: [ + "docs/collaborate/git/connect-github", + "docs/collaborate/git/connect-gitlab", + { + type: "category", + label: "Azure DevOps", + items: [ + "docs/collaborate/git/connect-azure-devops", + "docs/collaborate/git/setup-azure", + "docs/collaborate/git/authenticate-azure", + ], + }, + "docs/collaborate/git/import-a-project-by-git-url", + ], + }, + ], + }, + { + type: "category", + label: "Document your dbt projects", + items: [ + "docs/collaborate/documentation", + "docs/collaborate/build-and-view-your-docs", + ], + }, - }, + { + type: "category", + label: "Manage access", items: [ - 'docs/contributing/adapter-development/1-what-are-adapters', - 'docs/contributing/adapter-development/2-prerequisites-for-a-new-adapter', - 'docs/contributing/adapter-development/3-building-a-new-adapter', - 'docs/contributing/adapter-development/4-testing-a-new-adapter', - 'docs/contributing/adapter-development/5-documenting-a-new-adapter', - 'docs/contributing/adapter-development/6-promoting-a-new-adapter', - 'docs/contributing/adapter-development/7-verifying-a-new-adapter' - ] - } + "docs/collaborate/manage-access/about-access", + "docs/collaborate/manage-access/seats-and-users", + { + type: "category", + label: "Permissions", + items: [ + "docs/collaborate/manage-access/self-service-permissions", + "docs/collaborate/manage-access/enterprise-permissions", + ], + }, + + { + type: "category", + label: "Single sign-on", + items: [ + "docs/collaborate/manage-access/sso-overview", + "docs/collaborate/manage-access/set-up-sso-saml-2.0", + "docs/collaborate/manage-access/set-up-sso-google-workspace", + "docs/collaborate/manage-access/set-up-sso-azure-active-directory", + ], + }, // SSO + { + type: "category", + label: "OAuth with data platforms", + items: [ + "docs/collaborate/manage-access/set-up-snowflake-oauth", + "docs/collaborate/manage-access/set-up-bigquery-oauth", + ], + }, // oauth + "docs/collaborate/manage-access/audit-log", + ], + }, // Manage access ], }, { type: "category", - label: "About", - items: ["docs/about/license", "docs/about/viewpoint"], + label: "Available dbt versions", + items: [ + "docs/dbt-versions/core", + "docs/dbt-versions/upgrade-core-in-cloud", + "docs/dbt-versions/product-lifecycles", + { + type: "category", + label: "dbt Cloud Release Notes", + items: [ + "docs/dbt-versions/dbt-cloud-release-notes", + { + type: "autogenerated", + dirName: "docs/dbt-versions/release-notes", + }, + ], + }, + ], }, + "docs/dbt-support", { type: "category", label: "Frequently asked questions", link: { - type: 'generated-index', title: 'Frequently asked questions', - description: 'Our Frequently Asked Questions (FAQs) section is a space where you can find an answer to some questions we get asked a lot (but that we’re happy to answer!). If you have a question or are still stuck on something, just reach out to us by emailing support@getdbt.com or clicking on the chat widget, and we’ll do our best to help out.', slug: '/docs/faqs', + type: "generated-index", + title: "Frequently asked questions", + description: + "Our Frequently Asked Questions (FAQs) section is a space where you can find an answer to some questions we get asked a lot (but that we’re happy to answer!). If you have a question or are still stuck on something, just reach out to us by emailing support@getdbt.com or clicking on the chat widget, and we’ll do our best to help out.", + slug: "/docs/faqs", }, items: [ { - type: 'autogenerated', - dirName: 'faqs' + type: "autogenerated", + dirName: "faqs", }, ], }, ], - "dbt CLI": [ - "dbt-cli/cli-overview", - { - type: "category", - label: "Installing dbt from the command line", - items: [ - "dbt-cli/install/overview", - "dbt-cli/install/homebrew", - "dbt-cli/install/pip", - "dbt-cli/install/docker", - "dbt-cli/install/from-source", - ], - }, - "dbt-cli/configure-your-profile", - ], "dbt Cloud": [ { type: "category", label: "Overview", - link: { type: 'doc', id: 'docs/dbt-cloud/cloud-overview' }, - items: [ - 'docs/dbt-cloud/cloud-quickstart', - ], + link: { type: "doc", id: "docs/dbt-cloud/cloud-overview" }, + items: [], }, { type: "category", label: "dbt Cloud IDE", items: [ - "docs/dbt-cloud/cloud-ide/the-dbt-ide", - "docs/dbt-cloud/cloud-ide/handling-merge-conflicts", "docs/dbt-cloud/cloud-ide/viewing-docs-in-the-ide", - "docs/dbt-cloud/cloud-ide/the-ide-git-button", - "docs/dbt-cloud/cloud-ide/ide-beta", ], }, { type: "category", label: "Configuring dbt Cloud", items: [ - "docs/dbt-cloud/cloud-configuring-dbt-cloud/connecting-your-database", - "docs/dbt-cloud/cloud-configuring-dbt-cloud/cloud-using-a-managed-repository", - "docs/dbt-cloud/cloud-configuring-dbt-cloud/cloud-configuring-repositories", - "docs/dbt-cloud/cloud-configuring-dbt-cloud/cloud-installing-the-github-application", - "docs/dbt-cloud/cloud-configuring-dbt-cloud/connecting-gitlab", - { - type: "category", - label: "Connecting Azure DevOps", - link: { type: 'doc', id: 'docs/dbt-cloud/cloud-configuring-dbt-cloud/connecting-azure-devops' }, - items: [ - 'docs/dbt-cloud/cloud-configuring-dbt-cloud/setup-azure', - 'docs/dbt-cloud/cloud-configuring-dbt-cloud/authenticate-azure', - ], - }, - "docs/dbt-cloud/cloud-configuring-dbt-cloud/cloud-import-a-project-by-git-url", "docs/dbt-cloud/cloud-configuring-dbt-cloud/cloud-choosing-a-dbt-version", - "docs/dbt-cloud/cloud-configuring-dbt-cloud/cloud-upgrading-dbt-versions", ], }, { type: "category", label: "Using dbt Cloud", link: { - type: 'generated-index', - title: 'Using dbt Cloud', - description: 'Learn how you can use dbt Cloud.', - slug: '/docs/dbt-cloud', + type: "generated-index", + title: "Using dbt Cloud", + description: "Learn how you can use dbt Cloud.", + slug: "/docs/dbt-cloud", }, items: [ - "docs/dbt-cloud/using-dbt-cloud/cloud-enabling-continuous-integration", - "docs/dbt-cloud/using-dbt-cloud/cloud-generating-documentation", - "docs/dbt-cloud/using-dbt-cloud/cloud-snapshotting-source-freshness", "docs/dbt-cloud/using-dbt-cloud/artifacts", - "docs/dbt-cloud/using-dbt-cloud/cloud-using-a-custom-cron-schedule", - "docs/dbt-cloud/using-dbt-cloud/cloud-setting-a-custom-target-name", - "docs/dbt-cloud/using-dbt-cloud/cloud-environment-variables", - "docs/dbt-cloud/using-dbt-cloud/cloud-notifications", - "docs/dbt-cloud/using-dbt-cloud/cloud-dashboard-status-tiles", "docs/dbt-cloud/using-dbt-cloud/cloud-model-timing-tab", "docs/dbt-cloud/using-dbt-cloud/cloud-metrics-layer", ], }, - { - type: "category", - label: "Access Control", - items: [ - "docs/dbt-cloud/access-control/access-control-overview", - "docs/dbt-cloud/access-control/cloud-seats-and-users", - "docs/dbt-cloud/access-control/self-service-permissions", - "docs/dbt-cloud/access-control/enterprise-permissions", - ], - }, - { - type: "category", - label: "dbt Cloud Enterprise", - items: [ - "docs/dbt-cloud/dbt-cloud-enterprise", - { - type: "category", - label: "Single Sign On", - items: [ - "docs/dbt-cloud/dbt-cloud-enterprise/sso-overview", - "docs/dbt-cloud/dbt-cloud-enterprise/setting-up-sso-with-saml-2.0", - "docs/dbt-cloud/dbt-cloud-enterprise/setting-up-sso-with-google-gsuite", - "docs/dbt-cloud/dbt-cloud-enterprise/setting-up-enterprise-sso-with-azure-active-directory", - ], - }, - { - type: "category", - label: "Database Auth", - items: [ - "docs/dbt-cloud/dbt-cloud-enterprise/setting-up-enterprise-snowflake-oauth", - "docs/dbt-cloud/cloud-configuring-dbt-cloud/cloud-setting-up-bigquery-oauth", - ], - }, - "docs/dbt-cloud/dbt-cloud-enterprise/audit-log", - ], - }, - { - type: "category", - label: "dbt Cloud Deployments", - items: [ - "docs/dbt-cloud/deployments/deployment-overview", - "docs/dbt-cloud/deployments/multi-tenant-deployment", - "docs/dbt-cloud/deployments/single-tenant-deployment", - "docs/dbt-cloud/deployments/deployment-architecture", - ], - }, - { - type: "category", - label: "dbt Cloud APIs", - items: [ - "docs/dbt-cloud/dbt-cloud-api/cloud-apis", - { - type: "category", - label: "Authentication", - items: [ - "docs/dbt-cloud/dbt-cloud-api/user-tokens", - "docs/dbt-cloud/dbt-cloud-api/service-tokens", - ], - }, - "docs/dbt-cloud/dbt-cloud-api/admin-cloud-api", - { - type: "category", - label: "Metadata API", - items: [ - "docs/dbt-cloud/dbt-cloud-api/metadata/metadata-overview", - "docs/dbt-cloud/dbt-cloud-api/metadata/metadata-querying", - { - type: "category", - label: "Schema", - items: [ - "docs/dbt-cloud/dbt-cloud-api/metadata/schema/metadata-schema-model", - "docs/dbt-cloud/dbt-cloud-api/metadata/schema/metadata-schema-models", - "docs/dbt-cloud/dbt-cloud-api/metadata/schema/metadata-schema-modelByEnv", - "docs/dbt-cloud/dbt-cloud-api/metadata/schema/metadata-schema-metric", - "docs/dbt-cloud/dbt-cloud-api/metadata/schema/metadata-schema-metrics", - "docs/dbt-cloud/dbt-cloud-api/metadata/schema/metadata-schema-source", - "docs/dbt-cloud/dbt-cloud-api/metadata/schema/metadata-schema-sources", - "docs/dbt-cloud/dbt-cloud-api/metadata/schema/metadata-schema-seed", - "docs/dbt-cloud/dbt-cloud-api/metadata/schema/metadata-schema-seeds", - "docs/dbt-cloud/dbt-cloud-api/metadata/schema/metadata-schema-snapshots", - "docs/dbt-cloud/dbt-cloud-api/metadata/schema/metadata-schema-test", - "docs/dbt-cloud/dbt-cloud-api/metadata/schema/metadata-schema-tests", - "docs/dbt-cloud/dbt-cloud-api/metadata/schema/metadata-schema-exposure", - "docs/dbt-cloud/dbt-cloud-api/metadata/schema/metadata-schema-exposures", - ], - }, - ], - }, - ], - }, - "docs/dbt-cloud/cloud-dbt-cloud-support", - { - type: "category", - label: "dbt Cloud Release Notes", - link: { type: 'doc', id: 'docs/dbt-cloud/release-notes' }, - items: [ - { - type: "autogenerated", - dirName: "docs/dbt-cloud/release-notes", - }, - ], - }, ], reference: [ { @@ -435,23 +526,19 @@ const sidebarSettings = { { type: "category", label: "For analyses", - items: [ - "reference/analysis-properties", - ], + items: ["reference/analysis-properties"], }, { type: "category", label: "For exposures", - items: [ - "reference/exposure-properties", - ], + items: ["reference/exposure-properties"], }, { type: "category", label: "For macros", items: [ "reference/macro-properties", - "reference/resource-properties/argument-type" + "reference/resource-properties/argument-type", ], }, ], @@ -514,10 +601,11 @@ const sidebarSettings = { type: "category", label: "dbt Jinja functions", link: { - type: 'generated-index', - title: 'dbt Jinja functions', - description: 'In addition to the standard Jinja library, we\'ve added additional functions and variables to the Jinja context that are useful when working with a dbt project.', - slug: '/reference/dbt-jinja-functions', + type: "generated-index", + title: "dbt Jinja functions", + description: + "In addition to the standard Jinja library, we've added additional functions and variables to the Jinja context that are useful when working with a dbt project.", + slug: "/reference/dbt-jinja-functions", }, items: [ { @@ -585,71 +673,34 @@ const sidebarSettings = { { type: "category", label: "Database Permissions", - items: [ - "reference/snowflake-permissions", - ], + items: ["reference/snowflake-permissions"], }, ], guides: [ - { - type: "category", - label: "Getting Started with dbt Cloud", - link: { type: 'doc', id: 'guides/getting-started/getting-started' }, - items: [ - { - type: "category", - label: "Getting set up", - link: { type: 'doc', id: 'guides/getting-started/getting-set-up' }, - items: [ - "guides/getting-started/getting-set-up/setting-up-bigquery", - "guides/getting-started/getting-set-up/setting-up-databricks", - "guides/getting-started/getting-set-up/setting-up-redshift", - "guides/getting-started/getting-set-up/setting-up-snowflake", - ], - }, - { - type: "category", - label: "Building your first project", - link: { type: 'doc', id: 'guides/getting-started/building-your-first-project' }, - - items: [ - "guides/getting-started/building-your-first-project/build-your-first-models", - "guides/getting-started/building-your-first-project/test-and-document-your-project", - "guides/getting-started/building-your-first-project/schedule-a-job", - ], - }, - { - type: "category", - label: "Learning more", - link: { type: 'doc', id: 'guides/getting-started/learning-more' }, - items: [ - "guides/getting-started/learning-more/getting-started-dbt-core", - "guides/getting-started/learning-more/using-jinja", - "guides/getting-started/learning-more/refactoring-legacy-sql", - ], - } - ] - }, { type: "category", label: "Best practices", link: { - type: 'generated-index', - title: 'Best practice guides', - description: 'Learn how dbt Labs approaches building projects through our current viewpoints on structure, style, and setup.', - slug: '/guides/best-practices', + type: "generated-index", + title: "Best practice guides", + description: + "Learn how dbt Labs approaches building projects through our current viewpoints on structure, style, and setup.", + slug: "/guides/best-practices", }, items: [ { type: "category", label: "How we structure our dbt projects", - link: { type: 'doc', id: 'guides/best-practices/how-we-structure/1-guide-overview' }, + link: { + type: "doc", + id: "guides/best-practices/how-we-structure/1-guide-overview", + }, items: [ "guides/best-practices/how-we-structure/2-staging", "guides/best-practices/how-we-structure/3-intermediate", "guides/best-practices/how-we-structure/4-marts", "guides/best-practices/how-we-structure/5-the-rest-of-the-project", - ] + ], }, ], }, @@ -657,16 +708,20 @@ const sidebarSettings = { type: "category", label: "Orchestration", link: { - type: 'generated-index', - title: 'Orchestration guides', - description: 'Learn how to orchestrate your data transformations in dbt, using dbt Cloud, a variety of popular tools, or both working together.', - slug: '/guides/orchestration', + type: "generated-index", + title: "Orchestration guides", + description: + "Learn how to orchestrate your data transformations in dbt, using dbt Cloud, a variety of popular tools, or both working together.", + slug: "/guides/orchestration", }, items: [ { type: "category", label: "Airflow and dbt Cloud", - link: { type: 'doc', id: 'guides/orchestration/airflow-and-dbt-cloud/1-airflow-and-dbt-cloud' }, + link: { + type: "doc", + id: "guides/orchestration/airflow-and-dbt-cloud/1-airflow-and-dbt-cloud", + }, items: [ "guides/orchestration/airflow-and-dbt-cloud/2-setting-up-airflow-and-dbt-cloud", "guides/orchestration/airflow-and-dbt-cloud/3-running-airflow-and-dbt-cloud", @@ -676,14 +731,17 @@ const sidebarSettings = { { type: "category", label: "Customizing CI/CD", - link: { type: 'doc', id: 'guides/orchestration/custom-cicd-pipelines/1-cicd-background' }, + link: { + type: "doc", + id: "guides/orchestration/custom-cicd-pipelines/1-cicd-background", + }, items: [ "guides/orchestration/custom-cicd-pipelines/2-lint-on-push", "guides/orchestration/custom-cicd-pipelines/3-dbt-cloud-job-on-merge", "guides/orchestration/custom-cicd-pipelines/4-something-to-consider", ], }, - ] + ], }, { type: "category", @@ -693,10 +751,11 @@ const sidebarSettings = { type: "category", label: "Versions", link: { - type: 'generated-index', - title: 'Version migration guides', - description: 'Learn how to upgrade to the latest version of dbt Core.', - slug: '/guides/migration/versions', + type: "generated-index", + title: "Version migration guides", + description: + "Learn how to upgrade to the latest version of dbt Core.", + slug: "/guides/migration/versions", }, items: [ { @@ -709,30 +768,50 @@ const sidebarSettings = { type: "category", label: "Tools", link: { - type: 'generated-index', - title: 'Tool migration guides', - description: 'Learn how to migrate to dbt from other tools and platforms.', - slug: '/guides/migration/tools', + type: "generated-index", + title: "Tool migration guides", + description: + "Learn how to migrate to dbt from other tools and platforms.", + slug: "/guides/migration/tools", }, items: [ { type: "category", label: "Migrating from stored procedures", link: { - type: 'doc', - id: 'guides/migration/tools/migrating-from-stored-procedures/1-migrating-from-stored-procedures', + type: "doc", + id: "guides/migration/tools/migrating-from-stored-procedures/1-migrating-from-stored-procedures", }, items: [ - 'guides/migration/tools/migrating-from-stored-procedures/2-inserts', - 'guides/migration/tools/migrating-from-stored-procedures/3-updates', - 'guides/migration/tools/migrating-from-stored-procedures/4-deletes', - 'guides/migration/tools/migrating-from-stored-procedures/5-merges', - 'guides/migration/tools/migrating-from-stored-procedures/6-migrating-from-stored-procedures-conclusion', - ] - } - ] - }, - ] + "guides/migration/tools/migrating-from-stored-procedures/2-inserts", + "guides/migration/tools/migrating-from-stored-procedures/3-updates", + "guides/migration/tools/migrating-from-stored-procedures/4-deletes", + "guides/migration/tools/migrating-from-stored-procedures/5-merges", + "guides/migration/tools/migrating-from-stored-procedures/6-migrating-from-stored-procedures-conclusion", + ], + }, + ], + }, + { + type: "category", + label: "Advanced", + items: [ + { + type: "category", + label: "Adapter development", + items: [ + "guides/advanced/adapter-development/1-what-are-adapters", + "guides/advanced/adapter-development/2-prerequisites-for-a-new-adapter", + "guides/advanced/adapter-development/3-building-a-new-adapter", + "guides/advanced/adapter-development/4-testing-a-new-adapter", + "guides/advanced/adapter-development/5-documenting-a-new-adapter", + "guides/advanced/adapter-development/6-promoting-a-new-adapter", + "guides/advanced/adapter-development/7-verifying-a-new-adapter", + ], + }, + ], + }, + ], }, { type: "category", @@ -740,7 +819,6 @@ const sidebarSettings = { items: [ "guides/legacy/debugging-errors", "guides/legacy/debugging-schema-names", - "guides/legacy/navigating-the-docs", "guides/legacy/getting-help", "guides/legacy/best-practices", "guides/legacy/writing-custom-generic-tests", @@ -748,28 +826,80 @@ const sidebarSettings = { "guides/legacy/creating-new-materializations", "guides/legacy/understanding-state", "guides/legacy/videos", - ] + ], + }, + ], + community: [ + { + type: "doc", + id: "community/join", + }, + { + type: "category", + label: "Contributing", + link: { + type: "doc", + id: "community/contribute", + }, + items: [ + { + type: "doc", + label: "Become a contributor", + id: "community/contribute", + }, + "community/contributing/contributing-writing", + "community/contributing/contributing-coding", + "community/contributing/contributing-online-community", + "community/contributing/contributing-realtime-events", + ], + }, + { + type: "link", + label: "Community Forum", + href: "/community/forum", + }, + { + type: "link", + label: "Events", + href: "/community/events", + }, + { + type: "category", + label: "Additional resources", + items: [ + "community/resources/viewpoint", + "community/resources/code-of-conduct", + "community/resources/slack-rules-of-the-road", + "community/resources/maintaining-a-channel", + "community/resources/vendor-guidelines", + "community/resources/forum-guidelines", + "community/resources/organizing-inclusive-events", + "community/resources/oss-expectations", + "community/resources/oss-projects", + "community/resources/contributor-license-agreements", + "community/resources/speaking-at-a-meetup", + ], }, ], - "Glossary": [ + Glossary: [ { type: "category", label: "Analytics Engineering Glossary", link: { - type: 'generated-index', - title: 'Analytics Engineering Glossary', - description: 'The Analytics Engineering Glossary is a living collection of terms & concepts commonly used in the data industry. You can use and contribute to this resource to educate yourself, your team, and your stakeholders.', - slug: '/glossary', + type: "generated-index", + title: "Analytics Engineering Glossary", + description: + "The Analytics Engineering Glossary is a living collection of terms & concepts commonly used in the data industry. You can use and contribute to this resource to educate yourself, your team, and your stakeholders.", + slug: "/glossary", }, items: [ { - type: 'autogenerated', - dirName: 'terms' + type: "autogenerated", + dirName: "terms", }, ], }, ], }; - -module.exports = sidebarSettings +module.exports = sidebarSettings; diff --git a/website/snippets/discourse-help-feed-header.md b/website/snippets/discourse-help-feed-header.md new file mode 100644 index 00000000000..ef50864e7f1 --- /dev/null +++ b/website/snippets/discourse-help-feed-header.md @@ -0,0 +1 @@ +### Questions from the Community \ No newline at end of file diff --git a/website/snippets/tutorial-add-tests-to-models.md b/website/snippets/tutorial-add-tests-to-models.md index 9989cbe2ecc..937a444a1f0 100644 --- a/website/snippets/tutorial-add-tests-to-models.md +++ b/website/snippets/tutorial-add-tests-to-models.md @@ -1,4 +1,4 @@ -Adding [tests](/docs/building-a-dbt-project/tests) to a project helps validate that your models are working correctly. +Adding [tests](/docs/build/tests) to a project helps validate that your models are working correctly. To add tests to your project: @@ -56,7 +56,6 @@ When you run `dbt test`, dbt iterates through your YAML files, and constructs a - diff --git a/website/snippets/what-is-dbt-intro.md b/website/snippets/what-is-dbt-intro.md new file mode 100644 index 00000000000..6826dafb852 --- /dev/null +++ b/website/snippets/what-is-dbt-intro.md @@ -0,0 +1 @@ +dbt is a transformation workflow that helps you get more work done while producing higher quality results. You can use dbt to modularize and centralize your analytics code, while also providing your data team with guardrails typically found in software engineering workflows. Collaborate on data models, version them, and test and document your queries before safely deploying them to production, with monitoring and visibility. diff --git a/website/src/components/blogPostCard/index.js b/website/src/components/blogPostCard/index.js new file mode 100644 index 00000000000..0600d45add1 --- /dev/null +++ b/website/src/components/blogPostCard/index.js @@ -0,0 +1,27 @@ +import React from 'react'; +import styles from './styles.module.css'; +import useBaseUrl from '@docusaurus/useBaseUrl'; +import Link from '@docusaurus/Link'; + + +function BlogPostCard({ postMetaData }) { + const { title, date, readingTime, description, link, image } = postMetaData + return ( +
+
+ {image &&
} +
+

{title}

+ {readingTime && {date} · {readingTime} minute read} +

+ {description} +

+ Read more +
+
+
+ ); +} + +export default BlogPostCard; + diff --git a/website/src/components/blogPostCard/styles.module.css b/website/src/components/blogPostCard/styles.module.css new file mode 100644 index 00000000000..0374b5f1618 --- /dev/null +++ b/website/src/components/blogPostCard/styles.module.css @@ -0,0 +1,58 @@ +:root { + --border-radius: 10px; +} + +.card { + border: 1px solid #EFF2F3; + border-radius: var(--border-radius); + box-shadow: 0px 11px 24px rgba(138, 138, 138, .1); + padding: 2.5rem 2.5rem 1.5rem 2.5rem; +} + +/* if blog post has thumbnail image */ + +.imageCard { + border: 1px solid #EFF2F3; + border-radius: var(--border-radius); + box-shadow: 0px 11px 24px rgba(138, 138, 138, .1); + padding: 0; +} + +.contentContainer { + padding: 2.5rem 2.5rem 1.5rem 2.5rem; +} + +.imageContainer { + width: 100%; + border-radius: var(--border-radius) var(--border-radius) 0px 0px; + min-height: 200px; +} + +.cardWrapper, .cardWrapper article { + height: 100%; +} + +.cardWrapper a { + color: inherit; +} +.cardWrapper a:hover { + text-decoration: none; +} + +[data-theme='dark'] a.ctaLink { + color: #fff; + text-decoration: underline; +} + +a.ctaLink { + color: #009999; + font-weight: 600; +} +a.ctaLink:after { + content: ' →'; +} + +.icon { + margin-bottom: 0.5rem; + max-width: 50px; +} diff --git a/website/src/components/callout/index.js b/website/src/components/callout/index.js new file mode 100644 index 00000000000..60546525225 --- /dev/null +++ b/website/src/components/callout/index.js @@ -0,0 +1,29 @@ +import React from 'react'; +import styles from './styles.module.css'; +import useBaseUrl from '@docusaurus/useBaseUrl'; +import Link from '@docusaurus/Link'; +import { useColorMode } from '@docusaurus/theme-common'; + + +function Callout({ heading, subheading, cta, link }) { + const { isDarkTheme } = useColorMode(); + return ( +
+
+
+
+

{heading}

+

{subheading}

+ + {cta} + +
+
+
+
+ ); +} + +export default Callout; + diff --git a/website/src/components/callout/styles.module.css b/website/src/components/callout/styles.module.css new file mode 100644 index 00000000000..45a0f9d903d --- /dev/null +++ b/website/src/components/callout/styles.module.css @@ -0,0 +1,39 @@ +.Callout { + background: #262A38; + padding-top:3rem; + padding-bottom:3rem; + text-align: center; + padding-top:6rem; + padding-bottom: 6rem; + margin-top:6rem; +} + +[data-theme='light'] .Callout, [data-theme='dark'] .button { + color: #fff; +} + +.button { + background-color: #047377; + border-color: #047377; + border-radius: var(--ifm-button-border-radius); + border-style: solid; + border-width: var(--ifm-button-border-width); + color: var(--ifm-button-color); + cursor: pointer; + display: inline-block; + font-size: calc(0.875rem * var(--ifm-button-size-multiplier)); + font-weight: var(--ifm-button-font-weight); + line-height: 1.5; + padding: 0.8rem 1.5rem; + text-align: center; + user-select: none; + vertical-align: middle; + white-space: nowrap; + transition-property: color, background, border-color; + transition-duration: var(--ifm-button-transition-duration); + transition-timing-function: var(--ifm-transition-timing-default); +} + +.button:hover { + color: #ffffff; +} diff --git a/website/src/components/card/index.js b/website/src/components/card/index.js new file mode 100644 index 00000000000..ad0cfa91177 --- /dev/null +++ b/website/src/components/card/index.js @@ -0,0 +1,39 @@ +import React from 'react'; +import styles from './styles.module.css'; +import useBaseUrl from '@docusaurus/useBaseUrl'; +import Link from '@docusaurus/Link'; +import { useColorMode } from '@docusaurus/theme-common'; + + +function Card({ title, body, link, icon }) { + const { isDarkTheme } = useColorMode(); + return ( +
+ {link ? +
+ {icon && } +

{title}

+

+ {body} +

+
+ :
+ {icon && } +

{title}

+

+ {body} +

+
} +
+ ); +} + +export default Card; + diff --git a/website/src/components/card/styles.module.css b/website/src/components/card/styles.module.css new file mode 100644 index 00000000000..d61148079f6 --- /dev/null +++ b/website/src/components/card/styles.module.css @@ -0,0 +1,26 @@ +:root { + --border-radius: 10px; +} + +.card { + border: 1px solid #EFF2F3; + border-radius: var(--border-radius); + box-shadow: 0px 11px 24px rgba(138, 138, 138, .1); + padding: 2.5rem 2.5rem 1.5rem 2.5rem; +} + +.cardWrapper, .cardWrapper article { + height: 100%; +} + +.cardWrapper a { + color: inherit; +} +.cardWrapper a:hover { + text-decoration: none; +} + +.icon { + margin-bottom: 0.5rem; + max-width: 50px; +} diff --git a/website/src/components/collapsible/index.js b/website/src/components/collapsible/index.js index f3a7126ec04..e039433c542 100644 --- a/website/src/components/collapsible/index.js +++ b/website/src/components/collapsible/index.js @@ -2,7 +2,7 @@ import React, {useState} from 'react'; import styles from './styles.module.css'; -function Collapsible({children, header, expand}) { +function Collapsible({children, header, description, expand}) { const [expanded, setExpanded] = useState(expand); const toggleExpanded = function() { @@ -12,10 +12,10 @@ function Collapsible({children, header, expand}) { return ( <>

- { expanded ? '➖' : '➕' } {header} + { expanded ? ' -' : ' +' }

- { expanded ? children : Click to expand } + { expanded ? children : { description ? description : "Click to expand" } } ); } diff --git a/website/src/components/discourse/index.js b/website/src/components/discourse/index.js index ade96f5fd99..8a6b121ee3b 100644 --- a/website/src/components/discourse/index.js +++ b/website/src/components/discourse/index.js @@ -112,9 +112,9 @@ export const DiscourseFeed = ({ className={feedStyles.loadingIcon} data-testid="feed-loader" /> - ) : isError || !topics?.length > 0 ? ( -

Unable to load forum topics at this time.

- ) : ( + ) : isError || !topics?.length > 0 ? ( +

No recent forum posts for this topic. Ask a question!

+ ) : (
    {topics.map(topic => (
  • @@ -134,6 +134,14 @@ export const DiscourseFeed = ({ )} + {(topic?.blurb) && ( + <> + {' '} +
    + {topic.blurb} +
    + + )}
    • ))}
@@ -155,7 +163,7 @@ export const DiscourseHelpFeed = ({ show_cta = true, link_text = 'Ask the Community', link_href = `https://discourse.getdbt.com/new-topic${category ? `?category=${category}` : ''}${tags ? (!category ? `?tags=${tags}` : `&tags=${tags}`) : ''}`, - after, + after = '2000-01-01', before, inString, min_posts, @@ -164,13 +172,14 @@ export const DiscourseHelpFeed = ({ max_views, term, title, - topic_count = 5, + topic_count = 3, styles = {} }) => { return +
+
+
+
+

{heading}

+

{subheading}

+
+
+
+ + ); +} + +export default Hero; + diff --git a/website/src/components/hero/styles.module.css b/website/src/components/hero/styles.module.css new file mode 100644 index 00000000000..efacee33f6e --- /dev/null +++ b/website/src/components/hero/styles.module.css @@ -0,0 +1,51 @@ +.Hero { + background: #262A38; + padding-top:3rem; + padding-bottom:3rem; + text-align: center; + display: flex; + justify-content: center; + align-items: center; + /* position: relative; */ + min-height: 375px; + margin-bottom: 0; +} + +[data-theme='light'] .Hero { + color: #fff; +} + +@media (min-width: 996px) { + .Hero { + margin-bottom: 6rem; + } +} + +.showGraphic { + display: none; +} + +@media (min-width: 996px) { + .showGraphic{ + position: absolute; + left: -50px; + top:150px; + content:''; + display: block; + width: 25vw; + max-width: 315px; + height: 428px; + background-size: contain; + background-image: url('/img/hero-graphic-2x.png'); + background-repeat: no-repeat; + } +} + +.w60 { + width: 100%; +} +@media (min-width: 996px) { + .w60 { + width: 60%; + } +} diff --git a/website/src/components/postCarousel/index.js b/website/src/components/postCarousel/index.js new file mode 100644 index 00000000000..0b93c2d29e5 --- /dev/null +++ b/website/src/components/postCarousel/index.js @@ -0,0 +1,37 @@ +import React from 'react'; +import BlogPostCard from '@site/src/components/blogPostCard'; +import { Swiper, SwiperSlide } from 'swiper/react'; +import { Navigation } from 'swiper'; +import 'swiper/css'; +import 'swiper/css/navigation'; + + +function PostCarousel({ blogPostData }) { + return ( +
+ + + {blogPostData.map((item) => )} + + +
+ ); +} + +export default PostCarousel; + diff --git a/website/src/css/custom.css b/website/src/css/custom.css index a5dfab7f543..ac1ee6a48c1 100644 --- a/website/src/css/custom.css +++ b/website/src/css/custom.css @@ -30,13 +30,13 @@ --ifm-menu-color-active: #009999; --ifm-pagination-nav-color-hover: #047377; --ifm-tabs-color-active: #047377; - --ifm-menu-color-background-active: #EFFBFA; + --ifm-menu-color-background-active: #effbfa; --ifm-font-family-monospace: "Source Code Pro", SFMono-Regular, Menlo, Monaco, Consolas, "Liberation Mono", "Courier New", monospace; --ifm-font-family-base: "Source Sans Pro", sans-serif; --ifm-heading-font-family: "Source Sans Pro", sans-serif; - --ifm-code-padding-vertical: .2rem; - --ifm-code-padding-horizontal: .4rem; + --ifm-code-padding-vertical: 0.2rem; + --ifm-code-padding-horizontal: 0.4rem; --ifm-code-background: var(--ifm-color-emphasis-200); --ifm-navbar-item-padding-horizontal: 1rem; --ifm-alert-color: var(--ifm-font-color-base-inverse); @@ -51,15 +51,15 @@ --color-off-white: #eff2f3; --color-white: white; --color-nav-text: #bfc0c0; - --color-nav-sub-level-text: #545A66; - --color-footer-accent: #979EAB; + --color-nav-sub-level-text: #545a66; + --color-footer-accent: #979eab; --docsearch-text-color: #262a38; - --pagination-icon-next: '\2192'; - --pagination-icon-prev: '\2190'; + --pagination-icon-next: "\2192"; + --pagination-icon-prev: "\2190"; --filter-brightness-low: 1.1; --filter-brightness-high: 1.5; - --light-dark-toggle: 'data:image/svg+xml;base64,PHN2ZyB3aWR0aD0iMTYiIGhlaWdodD0iMTYiIGZpbGw9Im5vbmUiIHhtbG5zPSJodHRwOi8vd3d3LnczLm9yZy8yMDAwL3N2ZyI+PHBhdGggZD0iTTQuMzA4IDMuMzg1YzAtMS4xNzguMTczLTIuMzcuNjE1LTMuMzg1QzEuOTgzIDEuMjggMCA0LjI4MiAwIDcuNjkyQTguMzA4IDguMzA4IDAgMCAwIDguMzA4IDE2YzMuNDEgMCA2LjQxMi0xLjk4MyA3LjY5Mi00LjkyMy0xLjAxNS40NDItMi4yMDcuNjE1LTMuMzg1LjYxNWE4LjMwOCA4LjMwOCAwIDAgMS04LjMwNy04LjMwN1oiIGZpbGw9IiM5MkEwQjMiLz48L3N2Zz4='; + --light-dark-toggle: "data:image/svg+xml;base64,PHN2ZyB3aWR0aD0iMTYiIGhlaWdodD0iMTYiIGZpbGw9Im5vbmUiIHhtbG5zPSJodHRwOi8vd3d3LnczLm9yZy8yMDAwL3N2ZyI+PHBhdGggZD0iTTQuMzA4IDMuMzg1YzAtMS4xNzguMTczLTIuMzcuNjE1LTMuMzg1QzEuOTgzIDEuMjggMCA0LjI4MiAwIDcuNjkyQTguMzA4IDguMzA4IDAgMCAwIDguMzA4IDE2YzMuNDEgMCA2LjQxMi0xLjk4MyA3LjY5Mi00LjkyMy0xLjAxNS40NDItMi4yMDcuNjE1LTMuMzg1LjYxNWE4LjMwOCA4LjMwOCAwIDAgMS04LjMwNy04LjMwN1oiIGZpbGw9IiM5MkEwQjMiLz48L3N2Zz4="; /* search overrides */ --docsearch-searchbox-background: var(--color-white) !important; @@ -68,19 +68,20 @@ --docsearch-modal-background: var(--color-white) !important; --docsearch-modal-shadow: none; - --docsearch-muted-color-for-keys: #EFF2F3; + --docsearch-muted-color-for-keys: #eff2f3; --docsearch-highlight-color: var(--docsearch-muted-color) !important; - --docsearch-muted-color: #545A66; - --docsearch-container-background: rgba(255,255,255, 1) !important; + --docsearch-muted-color: #545a66; + --docsearch-container-background: rgba(255, 255, 255, 1) !important; --docsearch-key-gradient: transparent !important; - --docsearch-key-shadow: inset 0 0 0 0 #cdcde6,inset 0 0 0 0 #fff,0 0 0 0 rgba(30,35,90,0.0) !important; - --docsearch-key-shadow: none !important; + --docsearch-key-shadow: inset 0 0 0 0 #cdcde6, inset 0 0 0 0 #fff, + 0 0 0 0 rgba(30, 35, 90, 0) !important; + --docsearch-key-shadow: none !important; } /* dark theme styles!!! */ -html[data-theme='dark'] { +html[data-theme="dark"] { --ifm-navbar-background-color: var(--color-primary-blue); --ifm-menu-color-background-active: var(--color-primary-blue); --ifm-menu-color: var(--color-white); @@ -88,7 +89,7 @@ html[data-theme='dark'] { /* search button darkmode */ --docsearch-muted-color: var(--color-off-white); --docsearch-muted-color-for-keys: var(--docsearch-muted-color); - --docsearch-searchbox-background: var(--color-primary-blue) !important; + --docsearch-searchbox-background: var(--color-primary-blue) !important; /* search popup */ --docsearch-modal-background: var(--color-primary-blue) !important; @@ -103,21 +104,21 @@ html[data-theme='dark'] { } /* For /dbt-cloud/api REDOC Page */ -html[data-theme='dark'] .api-content h2, -html[data-theme='dark'] .api-content h3, -html[data-theme='dark'] .api-content h4, -html[data-theme='dark'] .api-content h5, -html[data-theme='dark'] .api-content h5 span, -html[data-theme='dark'] .api-content h1 { +html[data-theme="dark"] .api-content h2, +html[data-theme="dark"] .api-content h3, +html[data-theme="dark"] .api-content h4, +html[data-theme="dark"] .api-content h5, +html[data-theme="dark"] .api-content h5 span, +html[data-theme="dark"] .api-content h1 { color: white; } -html[data-theme='dark'] .api-content button, -html[data-theme='dark'] .api-content a { +html[data-theme="dark"] .api-content button, +html[data-theme="dark"] .api-content a { filter: brightness(1.25); } -html[data-theme='dark'] .api-content a:hover { +html[data-theme="dark"] .api-content a:hover { filter: brightness(1.25); } @@ -139,48 +140,48 @@ html[data-theme='dark'] .api-content a:hover { margin-top: 1em; } -html[data-theme='dark'] .api-content { - color: white; +html[data-theme="dark"] .api-content { + color: white; } -html[data-theme='dark'] .api-content table td > span, -html[data-theme='dark'] .api-content table td p { +html[data-theme="dark"] .api-content table td > span, +html[data-theme="dark"] .api-content table td p { color: var(--color-orange); } -html[data-theme='dark'] table td { +html[data-theme="dark"] table td { filter: brightness(1.25); color: white; } -html[data-theme='dark'] .api-content table td span { +html[data-theme="dark"] .api-content table td span { color: white; } -html[data-theme='dark'] .hComDo div { +html[data-theme="dark"] .hComDo div { background: transparent; } -html[data-theme='dark'] .api-content table td p { +html[data-theme="dark"] .api-content table td p { color: brown; } -html[data-theme='dark'] .redoc-wrap .menu-content * :not(.operation-type), -html[data-theme='dark'] .redoc-wrap .menu-content, -html[data-theme='dark'] .redoc-wrap .menu-content .search-input { +html[data-theme="dark"] .redoc-wrap .menu-content * :not(.operation-type), +html[data-theme="dark"] .redoc-wrap .menu-content, +html[data-theme="dark"] .redoc-wrap .menu-content .search-input { color: white !important; background-color: transparent !important; } -html[data-theme='dark'] .redoc-wrap svg { +html[data-theme="dark"] .redoc-wrap svg { filter: brightness(4.5); } -html[data-theme='dark'] .redoc-markdown pre { +html[data-theme="dark"] .redoc-markdown pre { filter: brightness(1.5); } -html[data-theme='dark'] input.sc-avest { +html[data-theme="dark"] input.sc-avest { filter: brightness(2.5); } @@ -194,7 +195,7 @@ html[data-theme='dark'] input.sc-avest { background: var(--color-off-white); } -html[data-theme='dark'] .container.home { +html[data-theme="dark"] .container.home { background: var(--ifm-background-color) !important; } @@ -219,7 +220,7 @@ code { color: var(--ifm-color-emphasis-900); } -html[data-theme='dark'] a code { +html[data-theme="dark"] a code { color: var(--color-white); } @@ -267,8 +268,8 @@ a.code-link:hover { } /* navbar */ -[data-theme='dark'] nav.navbar, -[data-theme='dark'] div.navbar-sidebar__brand { +[data-theme="dark"] nav.navbar, +[data-theme="dark"] div.navbar-sidebar__brand { background-color: var(--ifm-navbar-background-color); } @@ -284,7 +285,7 @@ a.code-link:hover { .navbar__link { font-size: 1rem; - margin: var(--ifm-navbar-item-padding-vertical) var(--ifm-navbar-item-padding-horizontal) 0; + margin: 0 var(--ifm-navbar-item-padding-horizontal) 0; padding: 0; border-bottom: 1px solid transparent; } @@ -306,6 +307,57 @@ a.code-link:hover { justify-content: center; } +.navbar-sidebar .menu__link.nav-create-account { + color: var(--color-white); + border: none; +} + +.navbar-sidebar .menu__link.nav-create-account:hover { + color: var(--color-white); + background: var(--color-light-teal); +} + +.navbar__items .navbar__link.nav-create-account { + color: var(--color-white); + height: 30px; + align-self: auto; + padding: 0 12px; + margin-top: 0; + margin-left: 0; + border: none; + order: 3; +} + +.navbar__items .navbar__link.nav-create-account:hover { + background: var(--color-light-teal); +} + +/* Reorder search and darkmode toggle */ +.navbar__items.navbar__items--right div[class^="searchBox"] { + order: 2; +} + +.navbar__items.navbar__items--right div[class^="toggle"] { + order: 4; +} + +/* moon/sun icons for dark/light mode */ +html[data-theme="light"] svg[class^="lightToggleIcon_"] { + display: none; +} + +html[data-theme="light"] svg[class^="darkToggleIcon_"] { + display: block; +} + +html[data-theme="dark"] svg[class^="lightToggleIcon_"] { + display: block; +} + +html[data-theme="dark"] svg[class^="darkToggleIcon_"] { + display: none; +} + /* Search Button Styles */ .search { width: 100%; @@ -313,12 +365,12 @@ a.code-link:hover { font-size: 20px; border: 0px; outline-width: 0px; - transition: all .3s ease; + transition: all 0.3s ease; } /* search popup */ .DocSearch-Container { - background-color: rgba(0,0,0,.85) !important; + background-color: rgba(0, 0, 0, 0.85) !important; } .DocSearch-Form { @@ -332,7 +384,7 @@ a.code-link:hover { } .navbar-sidebar__close { - margin-right: .75em; + margin-right: 0.75em; } /* navbar buttons */ @@ -347,7 +399,7 @@ a.navbar__item.navbar__link.btn { a.navbar__item.navbar__link.btn:hover { filter: brightness(var(--filter-brightness-high)); - transition: all .3s ease; + transition: all 0.3s ease; } /* sidebar menu */ @@ -380,6 +432,7 @@ a.navbar__item.navbar__link.btn:hover { background: transparent; } + /* level2 */ li.theme-doc-sidebar-item-category.theme-doc-sidebar-item-category-level-2 .menu__list-item-collapsible { font-weight: 600; @@ -393,6 +446,12 @@ li.theme-doc-sidebar-item-category.theme-doc-sidebar-item-category-level-2 .menu } .menu__list .menu__list .menu__link { + padding-top: 0.5rem; + padding-bottom: 0.5rem; +} + +.menu__list-item-collapsible a { + padding-left: 0; padding-top: .75rem; padding-bottom: .75rem; } @@ -412,11 +471,14 @@ i.theme-doc-sidebar-item-category.theme-doc-sidebar-item-category-level-2.menu__ } /* color for subtext only */ -.theme-doc-sidebar-item-link :not(.menu__list-item-collapsible .menu__link:first-of-type) { +.theme-doc-sidebar-item-link + :not(.menu__list-item-collapsible .menu__link:first-of-type) { color: var(--color-nav-sub-level-text); } -[data-theme='dark'] .theme-doc-sidebar-item-link :not(.menu__list-item-collapsible .menu__link:first-of-type) { +[data-theme="dark"] + .theme-doc-sidebar-item-link + :not(.menu__list-item-collapsible .menu__link:first-of-type) { color: var(--color-white); } @@ -438,7 +500,7 @@ i.theme-doc-sidebar-item-category.theme-doc-sidebar-item-category-level-2.menu__ background-color: transparent; } -.menu__list-item--collapsed .menu__link--sublist::after, +.menu__list-item--collapsed .menu__link--sublist::after, .menu__list-item--collapsed .menu__caret::before { transform: rotateZ(90deg); } @@ -452,7 +514,10 @@ i.theme-doc-sidebar-item-category.theme-doc-sidebar-item-category-level-2.menu__ background-repeat: no-repeat; height: 9px; min-width: 6px; - width: calc( var(--ifm-breadcrumb-separator-size) * var(--ifm-breadcrumb-size-multiplier) * var(--ifm-breadcrumb-separator-size-multiplier) ); + width: calc( + var(--ifm-breadcrumb-separator-size) * var(--ifm-breadcrumb-size-multiplier) * + var(--ifm-breadcrumb-separator-size-multiplier) + ); } /* Table of Contents */ @@ -620,11 +685,6 @@ div .toggle_src-components-faqs-styles-module { background-size: 1.25rem 1.25rem; } -.home .row .col--4 { - margin-bottom: 20px; - min-height: 251px; -} - /* card styles */ .card.large { position: relative; @@ -684,7 +744,7 @@ div .toggle_src-components-faqs-styles-module { } .card.large .button:hover { - background: #fff; + background: var(--color-white); border-color: var(--color-white); color: var(--color-green-blue); } @@ -736,15 +796,15 @@ div .toggle_src-components-faqs-styles-module { } .pagination-nav__item--next .pagination-nav__label::after { - content: var(--pagination-icon-next); + content: var(--pagination-icon-next); font-weight: var(--ifm-font-weight-narrow); - margin-left: .5em; + margin-left: 0.5em; } .pagination-nav__item:first-child .pagination-nav__label::before { - content: var(--pagination-icon-prev) ; + content: var(--pagination-icon-prev); font-weight: var(--ifm-font-weight-narrow); - margin-right: .5em; + margin-right: 0.5em; } .pagination-nav__sublabel { @@ -771,8 +831,12 @@ td, font-size: 1.125rem !important; } .markdown h1:first-child { - font-size: clamp(var(--ifm-h1-font-size) * .9375, 1vw, var(--ifm-h1-font-size)); - margin-top: .5rem; + font-size: clamp( + var(--ifm-h1-font-size) * 0.9375, + 1vw, + var(--ifm-h1-font-size) + ); + margin-top: 0.5rem; } .link_src-components-faqs-styles-module { font-size: 1.125rem; @@ -781,15 +845,20 @@ td, /* Docs */ .docImage_src-components-lightbox-, .docImage_src-components-lightbox-styles-module, -.docImage_2V3X, .docImage_917O { +.docImage_2V3X, +.docImage_917O { max-width: 100%; } -.generatedIndexPage_node_modules-\@docusaurus-theme-classic-lib-next-theme-DocCategoryGeneratedIndexPage-styles-module .cardContainer_node_modules-\@docusaurus-theme-classic-lib-next-theme-DocCard-styles-module, .generatedIndexPage_aEAk .card { +.generatedIndexPage_node_modules-\@docusaurus-theme-classic-lib-next-theme-DocCategoryGeneratedIndexPage-styles-module + .cardContainer_node_modules-\@docusaurus-theme-classic-lib-next-theme-DocCard-styles-module, +.generatedIndexPage_aEAk .card { color: var(--color-white); background: var(--ifm-footer-background-color); } -.generatedIndexPage_node_modules-\@docusaurus-theme-classic-lib-next-theme-DocCategoryGeneratedIndexPage-styles-module .cardContainer_node_modules-\@docusaurus-theme-classic-lib-next-theme-DocCard-styles-module:hover, .generatedIndexPage_aEAk .card:hover { +.generatedIndexPage_node_modules-\@docusaurus-theme-classic-lib-next-theme-DocCategoryGeneratedIndexPage-styles-module + .cardContainer_node_modules-\@docusaurus-theme-classic-lib-next-theme-DocCard-styles-module:hover, +.generatedIndexPage_aEAk .card:hover { color: var(--color-white); background: var(--color-primary-blue); } @@ -799,11 +868,11 @@ td, display: block; margin-bottom: 0; background: var(--color-off-white); - padding: .5rem 0; + padding: 0.5rem 0; } -html[data-theme='dark'] .blog-breadcrumbs { - background-color: rgba(20,20,10,0.75); +html[data-theme="dark"] .blog-breadcrumbs { + background-color: rgba(20, 20, 10, 0.75); } .blog-breadcrumbs a { @@ -817,15 +886,15 @@ html[data-theme='dark'] .blog-breadcrumbs { } /* darkmode breadcrumbs */ -html[data-theme='dark'] .blog-breadcrumbs a[href="#"] { +html[data-theme="dark"] .blog-breadcrumbs a[href="#"] { filter: brightness(var(--filter-brightness-low)); } -html[data-theme='dark'] .blog-breadcrumbs a:not(:last-of-type):after { +html[data-theme="dark"] .blog-breadcrumbs a:not(:last-of-type):after { color: var(--ifm-link-color); } -html[data-theme='dark'] .breadcrumbs__item--active .breadcrumbs__link { +html[data-theme="dark"] .breadcrumbs__item--active .breadcrumbs__link { filter: brightness(var(--filter-brightness-high)); } @@ -838,7 +907,7 @@ html[data-theme='dark'] .breadcrumbs__item--active .breadcrumbs__link { bottom: 0; margin: auto 0; width: auto; - font-size: .9rem; + font-size: 0.9rem; pointer-events: none; } @@ -864,13 +933,13 @@ html[data-theme='dark'] .breadcrumbs__item--active .breadcrumbs__link { /* footer styles */ .footer { font-weight: var(--ifm-font-weight-narrow); - font-size: .875rem; + font-size: 0.875rem; padding-top: var(--ifm-footer-padding-vertical); padding-bottom: var(--ifm-footer-padding-vertical); } .footer button { - font-size: .875rem !important; + font-size: 0.875rem !important; } .footer a { @@ -911,31 +980,31 @@ html[data-theme='dark'] .breadcrumbs__item--active .breadcrumbs__link { .footer .fa-brands { color: var(--color-footer-accent); font-size: 1.6rem; - transition: all .3s ease-in-out; + transition: all 0.3s ease-in-out; } .footer .fa-brands:hover { -filter: opacity(.75); + filter: opacity(0.75); } /* copyright */ .footer__bottom { text-align: left; color: var(--color-footer-accent); - font-size: .875rem; + font-size: 0.875rem; } .footer__copyright { - margin-top: .5em; + margin-top: 0.5em; } @media (min-width: 997px) and (max-width: 1045px) { .navbar__link.nav-versioning { - transition: all .3s ease-in-out; + transition: all 0.3s ease-in-out; } } -@media (min-width: 997px) and (max-width: 1729px) { +@media (min-width: 997px) and (max-width: 2560px) { .container > .row .col { padding-left: 2.5rem; } @@ -964,9 +1033,10 @@ filter: opacity(.75); } @media (max-width: 996px) { - .navbar-sidebar__brand .navbarSidebarToggle_node_modules-\@docusaurus-theme-classic-lib-next-theme-Navbar-styles-module { + .navbar-sidebar__brand + .navbarSidebarToggle_node_modules-\@docusaurus-theme-classic-lib-next-theme-Navbar-styles-module { margin-right: 0; - margin-left: .25em; + margin-left: 0.25em; } .navbar-sidebar__brand > div:first-of-type { @@ -988,18 +1058,14 @@ filter: opacity(.75); height: auto; text-align: center; } - - .container.container--fluid.home .row { - margin: calc(2vh) auto !important; - } } -@media screen and (max-width: 1199px) { +@media screen and (max-width: 1199px) { button.DocSearch-Button { background: var(--ifm-color-gray-100); } - [data-theme='dark'] button.DocSearch-Button { + [data-theme="dark"] button.DocSearch-Button { background-color: #ffffff20; } @@ -1015,57 +1081,64 @@ filter: opacity(.75); } @media screen and (min-width: 1200px) { - /* search bar styles */ - button.DocSearch-Button { - border: 1px solid #95a0b1; - border-radius: 5px; - height: 35px; - } - - button.DocSearch-Button:active, - button.DocSearch-Button:focus, - button.DocSearch-Button:hover { - color: var(--docsearch-muted-color); - background: white; - box-shadow: var(--docsearch-searchbox-shadow); - border: 1px solid var(--ifm-link-color); - } - - button .DocSearch-Button-Placeholder { - font-size: .875rem; - font-weight: 600; - padding: 0 12px 0 8px; - } - - /* magnifying glass icon */ - button.DocSearch-Button .DocSearch-Search-Icon { - color: var(--docsearch-muted-color); - stroke-width: 2px; - width: 1em; - height: 1em; - } - - /* keys wrapper */ - button .DocSearch-Button-Keys { - border: 1px solid var(--docsearch-muted-color-for-keys); - border-radius: 5px; - padding: 0.24em 0.5em; - gap: 0.1em; - } - - /* single key */ - button .DocSearch-Button-Key { - font-size: 1.25rem; - margin-right: 0; - padding: 4px 4px 2px; - } + /* search bar styles */ + button.DocSearch-Button { + border: 1px solid #95a0b1; + border-radius: 5px; + height: 30px; + } + + button.DocSearch-Button:active, + button.DocSearch-Button:focus, + button.DocSearch-Button:hover { + color: var(--docsearch-muted-color); + background: white; + box-shadow: var(--docsearch-searchbox-shadow); + border: 1px solid var(--ifm-link-color); + } + + button .DocSearch-Button-Placeholder { + font-size: 0.875rem; + font-weight: 600; + padding: 0 12px 0 8px; + } + + /* magnifying glass icon */ + button.DocSearch-Button .DocSearch-Search-Icon { + color: var(--docsearch-muted-color); + stroke-width: 2px; + width: 1em; + height: 1em; + } + + /* keys wrapper */ + button .DocSearch-Button-Keys { + border: 1px solid var(--docsearch-muted-color-for-keys); + border-radius: 5px; + padding: 0.24em 0.5em; + gap: 0.1em; + } + + /* single key */ + button .DocSearch-Button-Key { + font-size: 1.25rem; + margin-right: 0; + padding: 4px 4px 2px; + } + + /* Add dark background on hover for searchbox */ + [data-theme="dark"] button.DocSearch-Button:active, + [data-theme="dark"] button.DocSearch-Button:focus, + [data-theme="dark"] button.DocSearch-Button:hover { + background: #ffffff10; + } } @media (min-width: 1440px) { .container--fluid { max-width: inherit; } - + html.docs-version-current .navbar__brand { background-color: var(--ifm-background-color); border-right: 1px solid var(--ifm-toc-border-color); @@ -1074,7 +1147,6 @@ filter: opacity(.75); button.DocSearch-Button { min-width: 175px; } - } @media (min-width: 997px) { @@ -1084,18 +1156,21 @@ filter: opacity(.75); max-height: var(--ifm-navbar-height); width: 300px; min-width: 5.5em; -} + } html.docs-version-current .navbar { width: 100%; - margin-left: 0; + margin-left: 0; } .navbar { - padding: 0 var(--ifm-navbar-padding-horizontal) 0 0; + padding: 0 var(--ifm-navbar-padding-horizontal) 0 0; } - html.docs-version-current aside html.docs-version-current .sidebar_node_modules-\@docusaurus-theme-classic-lib-next-theme-DocSidebar-styles-module { + html.docs-version-current + aside + html.docs-version-current + .sidebar_node_modules-\@docusaurus-theme-classic-lib-next-theme-DocSidebar-styles-module { position: relative; } @@ -1106,19 +1181,16 @@ filter: opacity(.75); .navbar__item { padding: var(--ifm-navbar-item-padding-vertical) 0; -} + } .navbar__item.navbar__link { display: flex; align-self: stretch; } - .navbar__items.navbar__items--right > div:nth-of-type(3) { - order: 1; - } - .navbar__items--right > :last-child { - padding: var(--ifm-navbar-item-padding-vertical) 1em var(--ifm-navbar-item-padding-vertical) .5em; + padding: var(--ifm-navbar-item-padding-vertical) 1em + var(--ifm-navbar-item-padding-vertical) 0.5em; } .blog-main-row > main { @@ -1128,23 +1200,23 @@ filter: opacity(.75); } .table-of-contents::before { - content: 'CONTENTS'; + content: "CONTENTS"; margin-left: 0.5rem; color: var(--color-nav-sub-level-text); - font-size: .875rem; + font-size: 0.875rem; font-weight: var(--ifm-font-weight-semibold); } - [data-theme='dark'] .table-of-contents::before { + [data-theme="dark"] .table-of-contents::before { color: var(--color-white); } - html[data-theme='dark'] .menu-content { + html[data-theme="dark"] .menu-content { border-right: 1px solid #dadde1; } .docSidebarContainer_src-theme-DocPage-styles-module { - margin-top: calc(-.8 * var(--ifm-navbar-height)) !important; + margin-top: calc(-0.8 * var(--ifm-navbar-height)) !important; } } @@ -1157,7 +1229,8 @@ filter: opacity(.75); margin-bottom: 3rem; } -.blog-post-page .docItemCol_node_modules-\@docusaurus-theme-classic-lib-next-theme-DocItem-styles-module { +.blog-post-page + .docItemCol_node_modules-\@docusaurus-theme-classic-lib-next-theme-DocItem-styles-module { max-width: 70% !important; } @@ -1172,7 +1245,8 @@ filter: opacity(.75); .blog-main-row .blog-right-sidebar { max-width: initial !important; } - .blog-post-page .docItemCol_node_modules-\@docusaurus-theme-classic-lib-next-theme-DocItem-styles-module { + .blog-post-page + .docItemCol_node_modules-\@docusaurus-theme-classic-lib-next-theme-DocItem-styles-module { max-width: 100% !important; } } @@ -1251,7 +1325,8 @@ filter: opacity(.75); text-align: left; } @media (max-width: 699px) { - .card.large.blog-hero-card:before, .card.large.blog-hero-card:after { + .card.large.blog-hero-card:before, + .card.large.blog-hero-card:after { display: none; } .blog-hero-card { @@ -1271,7 +1346,8 @@ filter: opacity(.75); .author-header { align-items: center; } -.author-header-left, .author-header-right { +.author-header-left, +.author-header-right { padding: 20px; } .author-header img { @@ -1350,15 +1426,15 @@ filter: opacity(.75); /*position: sticky;*/ text-align: center; background: var(--color-off-white); - position:relative; - bottom:0; + position: relative; + bottom: 0; max-width: 400px; } .docs-cta h4 { margin-bottom: 10px; } .docs-cta p { - font-size: .9rem; + font-size: 0.9rem; line-height: 21px; } .docs-cta .docs-cta-btn { @@ -1377,7 +1453,7 @@ filter: opacity(.75); @media (max-width: 996px) { .docs-cta { - display:none; + display: none; } } @@ -1392,13 +1468,17 @@ filter: opacity(.75); .mobile-toc-section { display: block; } - .mobile-toc-section .tableOfContents_node_modules-\@docusaurus-theme-classic-lib-next-theme-TOC-styles-module { + .mobile-toc-section + .tableOfContents_node_modules-\@docusaurus-theme-classic-lib-next-theme-TOC-styles-module { display: none; } - .mobile-toc-section .tableOfContents_node_modules-\@docusaurus-theme-classic-lib-next-theme-TOC-styles-module.tocActive { + .mobile-toc-section + .tableOfContents_node_modules-\@docusaurus-theme-classic-lib-next-theme-TOC-styles-module.tocActive { display: block; } - .mobile-toc-section .tableOfContents_node_modules-\@docusaurus-theme-classic-lib-next-theme-TOC-styles-module .table-of-contents__left-border { + .mobile-toc-section + .tableOfContents_node_modules-\@docusaurus-theme-classic-lib-next-theme-TOC-styles-module + .table-of-contents__left-border { border-left: none; } #mobile-toc-dropdown button.tocActive:after { @@ -1418,7 +1498,7 @@ filter: opacity(.75); width: 100%; } #mobile-toc-dropdown > button::after { - content: ''; + content: ""; background: var(--ifm-menu-link-sublist-icon) 50% 50% / 2rem 2rem no-repeat; filter: var(--ifm-menu-link-sublist-icon-filter); height: 1.25rem; @@ -1442,7 +1522,7 @@ filter: opacity(.75); } /* OneTrust Cookies Settings Btn in Footer */ -footer #ot-sdk-btn.ot-sdk-show-settings, +footer #ot-sdk-btn, footer #ot-sdk-btn.optanon-show-settings { background: none; border: none; @@ -1456,8 +1536,8 @@ footer #ot-sdk-btn.optanon-show-settings { font-weight: 400; cursor: pointer; } -footer #ot-sdk-btn.ot-sdk-show-settings:hover, -footer #ot-sdk-btn.optanon-show-settings:hover{ +footer #ot-sdk-btn:hover, +footer #ot-sdk-btn.optanon-show-settings:hover { background: none; border: none; color: var(--ifm-footer-color); @@ -1465,6 +1545,162 @@ footer #ot-sdk-btn.optanon-show-settings:hover{ } /* Discourse Forum & Events Page */ -.events-page section, section.discourse-forum-page { +.events-page section, +section.discourse-forum-page { padding: 4rem 0; } + +/* New Homepage Styles */ + +.home section { + margin: 6.25rem auto 6.25rem; + max-width: var(--ifm-container-width-xl); + padding: 0 var(--ifm-spacing-horizontal); +} + +.home section.from-the-blog { + margin-bottom: 0; +} +.home section.from-the-community { + margin-top: 0; + +} + +.home .resource-section h2 { + margin: 0; +} + +@media (max-width: 995px) { + .home .resource-section h2 { + text-align: center; + margin: 2rem inherit; + } +} + +section > h2:not(.resource-section) { + margin-bottom: 25px; +} + +.home .resource-section { + display: grid; + grid-template-columns: 1fr; + grid-gap: 16px; + grid-template-areas: + "featH2" + "featResource" + "popH2" + "popResources"; +} + +@media (min-width: 996px) { + .home .resource-section { + display: grid; + grid-template-columns: 2fr 1fr; + row-gap: 25px; + column-gap: calc(var(--ifm-spacing-horizontal) * 4); + grid-template-areas: + "popH2 featH2" + "popResources featResource"; + } +} + +.home .popular-header { + grid-area: popH2; + margin-top: 2.5rem; +} + +@media (min-width: 996px) { + .home .popular-header { + margin-top: 0; + } +} + +.home .popular-resources { + grid-area: popResources; +} + +.home .popular-resources .grid { + display: grid; + grid-template-columns: 1fr; + grid-gap: var(--ifm-spacing-horizontal); +} + +@media (min-width: 996px) { + .home .popular-resources .grid { + grid-template-columns: 1fr 1fr; + grid-template-rows: 1fr 1fr; + grid-gap: calc(var(--ifm-spacing-horizontal) * 2); + } +} + +.home .featured-header { + grid-area: featH2; +} + +.home .featured-resource { + grid-area: featResource; + height: 100%; +} + +.home .swiper .swiper-slide { + height: unset; +} + +.home .swiper.swiper-initialized { + padding-right: 3rem; + padding-left: 3rem; + padding-top: 0rem; + padding-bottom: 6.25rem; + margin-bottom: 0; +} + +.home .swiper .swiper-button-next, .home .swiper .swiper-button-prev { + color: #047377; + font-weight: 800; + position: absolute; + top: 40%; +} + +[data-theme='dark'] .home .swiper-button-next, [data-theme='dark'] .home .swiper-button-prev { + color: #fff; + font-weight: 800; +} + +/* Community Home styles */ +.community-home section { + margin: calc(5vh) auto calc(2vh); + max-width: var(--ifm-container-width-xl); + padding: 0 var(--ifm-spacing-horizontal); +} + + +/* utilities */ +.grid--3-col { + display: grid; + grid-template-columns: repeat(1, 1fr); + grid-gap: var(--ifm-spacing-horizontal) +} + +@media(min-width: 996px) { + .grid--3-col { + grid-template-columns: repeat(3, 1fr); + grid-gap: calc(var(--ifm-spacing-horizontal) * 2); + } +} + +.grid--2-col { + display: grid; + grid-template-columns: repeat(1, 1fr); + grid-gap: var(--ifm-spacing-horizontal) +} + +@media(min-width: 996px) { + .grid--2-col { + grid-template-columns: repeat(2, 1fr); + grid-gap: calc(var(--ifm-spacing-horizontal) * 2); + } +} + +.justify-content-center { + justify-content: center !important; +} diff --git a/website/src/pages/events.js b/website/src/pages/community/events.js similarity index 100% rename from website/src/pages/events.js rename to website/src/pages/community/events.js diff --git a/website/src/pages/community/forum.js b/website/src/pages/community/forum.js new file mode 100644 index 00000000000..346d96e9adf --- /dev/null +++ b/website/src/pages/community/forum.js @@ -0,0 +1,26 @@ +import React from 'react'; +import Layout from '@theme/Layout'; +import Head from '@docusaurus/Head'; +import { DiscourseFeed } from '@site/src/components/discourse'; + +function Events() { + return ( + + + dbt Community Forum + + +
+
+

dbt Community Forum

+

The dbt Community Forum is the preferred platform for support questions as well as a space for long-lived discussions about dbt, analytics engineering, and the analytics profession. It's a place for us to build up a long-lasting knowledge base around the common challenges, opportunities, and patterns we work with every day.

+ + + +
+
+ + ); +} + +export default Events; diff --git a/website/src/pages/forum.js b/website/src/pages/forum.js deleted file mode 100644 index a90e2cc875c..00000000000 --- a/website/src/pages/forum.js +++ /dev/null @@ -1,25 +0,0 @@ -import React from 'react'; -import Layout from '@theme/Layout'; -import Head from '@docusaurus/Head'; -import { DiscourseFeed } from '@site/src/components/discourse'; - -function Events() { - return ( - - - dbt Discourse - - -
-
-

dbt Discourse

- - - -
-
- - ); -} - -export default Events; diff --git a/website/src/pages/index.js b/website/src/pages/index.js index df3446b9971..5c9de9e85b2 100644 --- a/website/src/pages/index.js +++ b/website/src/pages/index.js @@ -1,11 +1,14 @@ import React from 'react'; -import Link from '@docusaurus/Link'; -import useDocusaurusContext from '@docusaurus/useDocusaurusContext'; -import useBaseUrl from '@docusaurus/useBaseUrl'; import Layout from '@theme/Layout'; -import classnames from 'classnames'; import Head from '@docusaurus/Head'; +import Card from '@site/src/components/card'; +import BlogPostCard from '@site/src/components/blogPostCard'; +import Hero from '@site/src/components/hero'; +import PostCarousel from '@site/src/components/postCarousel'; +import allBlogData from './../../.docusaurus/docusaurus-plugin-content-blog/default/blog-archive-80c.json' + + const bannerAnimation = require('@site/static/img/banner-white.svg'); @@ -14,269 +17,144 @@ function getBanner() { }; function Home() { - const context = useDocusaurusContext(); + + const recentBlogData = allBlogData.blogPosts.slice(0, 6).reduce((accumulator, currentValue) => { + let postMetaData = { + title: currentValue.metadata.title, + date: currentValue.metadata.formattedDate, + readingTime: Math.round(currentValue.metadata.readingTime), + description: currentValue.metadata.description, + link: currentValue.metadata.permalink, + } + accumulator.push(postMetaData) + return accumulator + }, []) + const featuredResource = { + title: "How we structure our dbt projects", + description: "Our hands-on learnings for how to structure your dbt project for success and gain insights into the principles of analytics engineering.", + link: "/guides/best-practices/how-we-structure/1-guide-overview", + image: "/img/structure-dbt-projects.png" + } return ( <> - -
-
-
-

Get started

-

If you’re new to dbt™, start here. These resources will get you off to a strong start:

-
-
-
-
-
-
-

What is dbt?

-
-
-

- Some of the very first questions a new user has are covered in this introduction. -

-
-
- - Learn More - -
-
-
-
-
-
-

Getting started guide

-
-
-

- Read this guide to learn how to build, test, and deploy a new dbt project. -

-
-
- - Learn More - -
-
-
-
-
-
-

dbt Learn

-
-
-

- Learn dbt on your own time with our on demand course or sign up for an upcoming, live public course. -

-
-
- - Learn Now - +
+ +
+

Popular resources

+
+
+
+ +
+
+ +
+
+ +
+
+
-
-
-
-
-
-

Build your project

-

If you’re getting comfortable with dbt, bookmark these resources! They’ll help you level up quickly.

-
-
-
-
-
-
-

Docs

-
-
-

- The core concepts of dbt, from models, to sources, to tests. -

-
-
- - Read Up - -
-
+

Featured resource

+
+
-
-
-
-

Reference

-
-
-

- The technical reference for dbt configurations. You’ll need to know the basics of dbt before using this section. -

-
-
- - Browse Reference - -
-
-
-
-
-
-

FAQs

-
-
-

- Commonly asked questions about dbt. -

-
-
- - Get Answers - -
+ + +
+

The latest from the Developer Blog

+ +
+ +
+

From the dbt Community

+
+
+
-
-
-
-
-

If you’re a dbt Cloud™ user, these resources may also be helpful:

-
-
-
-
-
-
-

dbt Cloud guides

-
-
-

- Guides to help you set up your dbt project in dbt Cloud -

-
-
- - Cloud Overview - -
+
+
-
-
-
-
-

dbt Cloud API

-
-
-

- Technical reference docs for using the dbt Cloud APIs. -

-
-
- - API docs - -
+
+
-
-
-
-
-
-

Learn from the community

-

Every data team uses dbt to solve different analytics engineering problems. It can be useful to learn how other teams are using dbt with the following resources:

-
-
-
-
-
-
-

Discourse

-
-
-

- Common use cases and helpful articles from the community have been published here -

-
-
- - Get Advice - -
+ + +
+

Use dbt like a pro

+
+
+
-
-
-
-
-

Slack

-
-
-

- Where the dbt community hangs out, discusses issues, and troubleshoots problems together -

-
-
- - Join us on Slack - -
+
+
-
-
-
-
-

Example projects

-
-
-

- A list of some dbt projects in the wild -

-
-
- - View Projects - -
+
+
-
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-
-
-
-

Having trouble?

-

If you're having trouble, check out our guide on Getting Help for information on getting support and asking questions in the community.

-
-
+
+
+
diff --git a/website/src/theme/MDXComponents/index.js b/website/src/theme/MDXComponents/index.js index 2fe4c79a228..c9514a320b3 100644 --- a/website/src/theme/MDXComponents/index.js +++ b/website/src/theme/MDXComponents/index.js @@ -4,12 +4,12 @@ * This source code is licensed under the MIT license found in the * LICENSE file in the root directory of this source tree. */ -import React, { isValidElement } from 'react'; -import Head from '@docusaurus/Head'; -import CodeBlock from '@theme/CodeBlock'; -import Heading from '@theme/Heading'; -import Details from '@theme/Details'; -import './styles.css'; // MDX elements are wrapped through the MDX pragma. In some cases (notably usage +import React, { isValidElement } from "react"; +import Head from "@docusaurus/Head"; +import CodeBlock from "@theme/CodeBlock"; +import Heading from "@theme/Heading"; +import Details from "@theme/Details"; +import "./styles.css"; // MDX elements are wrapped through the MDX pragma. In some cases (notably usage // with Head/Helmet) we need to unwrap those elements. /* @@ -35,6 +35,11 @@ import Var from '@site/src/components/variable'; import Term from '@site/src/components/term'; import EventsFeed from '@site/src/components/events'; import { DiscourseFeed, DiscourseHelpFeed } from '@site/src/components/discourse'; +import Hero from '@site/src/components/hero' +import Card from '@site/src/components/card' +import Callout from '@site/src/components/callout' +import BlogPostCard from '@site/src/components/blogPostCard'; +import PostCarousel from '@site/src/components/postCarousel'; function unwrapMDXElement(element) { if (element?.props?.mdxType && element?.props?.originalType) { @@ -48,27 +53,27 @@ function unwrapMDXElement(element) { const MDXComponents = { head: (props) => { const unwrappedChildren = React.Children.map(props.children, (child) => - unwrapMDXElement(child), + unwrapMDXElement(child) ); return {unwrappedChildren}; }, code: (props) => { const inlineElements = [ - 'a', - 'b', - 'big', - 'i', - 'span', - 'em', - 'strong', - 'sup', - 'sub', - 'small', + "a", + "b", + "big", + "i", + "span", + "em", + "strong", + "sup", + "sub", + "small", ]; const shouldBeInline = React.Children.toArray(props.children).every( (el) => - (typeof el === 'string' && !el.includes('\n')) || - (React.isValidElement(el) && inlineElements.includes(el.props.mdxType)), + (typeof el === "string" && !el.includes("\n")) || + (React.isValidElement(el) && inlineElements.includes(el.props.mdxType)) ); return shouldBeInline ? : ; }, @@ -76,7 +81,7 @@ const MDXComponents = { pre: (props) => ( @@ -85,7 +90,7 @@ const MDXComponents = { const items = React.Children.toArray(props.children); // Split summary item from the rest to pass it as a separate prop to the // Details theme component - const summary = items.find((item) => item?.props?.mdxType === 'summary'); + const summary = items.find((item) => item?.props?.mdxType === "summary"); const children = <>{items.filter((item) => item !== summary)}; return (
@@ -100,15 +105,20 @@ const MDXComponents = { h5: (props) => , h6: (props) => , + BlogPostCard: BlogPostCard, + Callout: Callout, + Card: Card, Changelog: Changelog, CloudCore: CloudCore, Collapsible: Collapsible, FAQ: FAQ, FAQList: FAQList, File: File, + Hero: Hero, Lightbox: Lightbox, Link: Link, LoomVideo: LoomVideo, + PostCarousel: PostCarousel, Tabs: Tabs, TabItem: TabItem, Snippet: Snippet, @@ -121,5 +131,6 @@ const MDXComponents = { EventsFeed: EventsFeed, DiscourseFeed: DiscourseFeed, DiscourseHelpFeed: DiscourseHelpFeed, + Card: Card, }; export default MDXComponents; diff --git a/website/static/img/docs/dbt-cloud/cloud-ide/create-new.png b/website/static/img/docs/dbt-cloud/cloud-ide/create-new.png new file mode 100644 index 00000000000..f40a554f341 Binary files /dev/null and b/website/static/img/docs/dbt-cloud/cloud-ide/create-new.png differ diff --git a/website/static/img/docs/dbt-cloud/cloud-ide/credentials.png b/website/static/img/docs/dbt-cloud/cloud-ide/credentials.png new file mode 100644 index 00000000000..7afb78409e1 Binary files /dev/null and b/website/static/img/docs/dbt-cloud/cloud-ide/credentials.png differ diff --git a/website/static/img/docs/dbt-cloud/cloud-ide/new-environment.png b/website/static/img/docs/dbt-cloud/cloud-ide/new-environment.png new file mode 100644 index 00000000000..6998cc3ce9c Binary files /dev/null and b/website/static/img/docs/dbt-cloud/cloud-ide/new-environment.png differ diff --git a/website/static/img/favicon.ico b/website/static/img/favicon.ico deleted file mode 100644 index ac704a27297..00000000000 Binary files a/website/static/img/favicon.ico and /dev/null differ diff --git a/website/static/img/favicon.png b/website/static/img/favicon.png new file mode 100644 index 00000000000..50b097a0468 Binary files /dev/null and b/website/static/img/favicon.png differ diff --git a/website/static/img/favicon.svg b/website/static/img/favicon.svg new file mode 100644 index 00000000000..a0577b18630 --- /dev/null +++ b/website/static/img/favicon.svg @@ -0,0 +1,12 @@ + + + + + \ No newline at end of file diff --git a/website/static/img/hero-graphic-2x.png b/website/static/img/hero-graphic-2x.png new file mode 100644 index 00000000000..8501a22e2c6 Binary files /dev/null and b/website/static/img/hero-graphic-2x.png differ diff --git a/website/static/img/hero-graphic.png b/website/static/img/hero-graphic.png new file mode 100644 index 00000000000..9c6a6d81485 Binary files /dev/null and b/website/static/img/hero-graphic.png differ diff --git a/website/static/img/icons/book.svg b/website/static/img/icons/book.svg new file mode 100644 index 00000000000..ff1faa686b5 --- /dev/null +++ b/website/static/img/icons/book.svg @@ -0,0 +1,3 @@ + + + diff --git a/website/static/img/icons/calendar.svg b/website/static/img/icons/calendar.svg new file mode 100644 index 00000000000..de2a9b11880 --- /dev/null +++ b/website/static/img/icons/calendar.svg @@ -0,0 +1,3 @@ + + + diff --git a/website/static/img/icons/computer.svg b/website/static/img/icons/computer.svg new file mode 100644 index 00000000000..c9a61e442bf --- /dev/null +++ b/website/static/img/icons/computer.svg @@ -0,0 +1,3 @@ + + + diff --git a/website/static/img/icons/discussions.svg b/website/static/img/icons/discussions.svg new file mode 100644 index 00000000000..e29a8dd8930 --- /dev/null +++ b/website/static/img/icons/discussions.svg @@ -0,0 +1,3 @@ + + + diff --git a/website/static/img/icons/docs.svg b/website/static/img/icons/docs.svg new file mode 100644 index 00000000000..bb788a1b4d8 --- /dev/null +++ b/website/static/img/icons/docs.svg @@ -0,0 +1,3 @@ + + + diff --git a/website/static/img/icons/folder.svg b/website/static/img/icons/folder.svg new file mode 100644 index 00000000000..e65bf093c95 --- /dev/null +++ b/website/static/img/icons/folder.svg @@ -0,0 +1,3 @@ + + + diff --git a/website/static/img/icons/guides.svg b/website/static/img/icons/guides.svg new file mode 100644 index 00000000000..c67e31a2018 --- /dev/null +++ b/website/static/img/icons/guides.svg @@ -0,0 +1,3 @@ + + + diff --git a/website/static/img/icons/packages.svg b/website/static/img/icons/packages.svg new file mode 100644 index 00000000000..cd2623a05b3 --- /dev/null +++ b/website/static/img/icons/packages.svg @@ -0,0 +1,3 @@ + + + diff --git a/website/static/img/icons/pencil-paper.svg b/website/static/img/icons/pencil-paper.svg new file mode 100644 index 00000000000..b614cd9f186 --- /dev/null +++ b/website/static/img/icons/pencil-paper.svg @@ -0,0 +1,3 @@ + + + diff --git a/website/static/img/icons/question-mark.svg b/website/static/img/icons/question-mark.svg new file mode 100644 index 00000000000..1de805a8e8f --- /dev/null +++ b/website/static/img/icons/question-mark.svg @@ -0,0 +1,3 @@ + + + diff --git a/website/static/img/icons/rocket.svg b/website/static/img/icons/rocket.svg new file mode 100644 index 00000000000..c524ebead6a --- /dev/null +++ b/website/static/img/icons/rocket.svg @@ 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