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Running PR to keep track of custom changes to support YB #127
base: 2.5.2.Final
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Initial changes required for the Debezium Connector for Postgres to work with YugabyteDB source.
…st YugabyteDB (#105) This PR includes the changes required for the tests so that they can work against YugabyteDB. YugabyteDB issue: yugabyte/yugabyte-db#21394
Modified Dockerfile to package custom log4j.properties so that the log files can be rolled over when their size exceeds 100MB. Also changed the Kafka connect JDBC jar being used - this new jar has a custom change to log every sink record going to the target database.
Changes in this PR: 1. Modification of Dockerfile to include transformers for aiven at the time of docker image compilation a. Aiven source: https://github.com/Aiven-Open/transforms-for-apache-kafka-connect
…BC driver (#107) ## Problem The Debezium connector for Postgres uses a single host model where the JDBC driver connects to a PG instance and continues execution. However, when we move to YugabyteDB where we have a multi node deployment, the current model can fail in case the node it has connected to goes down. ## Solution To address that, we have made changes in this PR and replaced the Postgres JDBC driver with [YugabyteDB smart driver](https://github.com/yugabyte/pgjdbc) which allows us to specify multiple hosts in the JDBC url so that the connector does not fail or run into any fatal error while maintaining the High Availability aspect of YugabyteDB. Changes in this PR include: 1. Changing of version in `pom.xml` from `2.5.2.Final` to `2.5.2.ybpg.20241-SNAPSHOT` a. This is done to ensure that upon image compilation, the changed code from Debezium Code is picked up. 2. Replacing of all packages from `org.postgresql.*` to `com.yugabyte.*` to comply with the new JDBC driver. 3. Masking the validator method in debezium-core which disallowed characters like `: (colon)` in the configuration property `database.hostname`
**Summary** This PR is to support consistent snapshot in the case of an existing slot. In this case, the consistent_point hybrid time is determined from the pg_replication_slots view, specifically from the yb_restart_commit_ht column. There is an assumption here that this slot has not been used for streaming till this point. If this holds, then the history retention barrier will be in place as of the consistent snapshot time (consistent_point). The snapshot query will be run as of the consistent_point and subsequent streaming will start from the consistent_point of the slot. **Test Plan** Added new test mvn -Dtest=PostgresConnectorIT#initialSnapshotWithExistingSlot test
**Changes:** 1. Providing JMX Exporter jar to KAFKA_OPTS to be further provided to java options. 2. Modifying `metrics.yaml` to include correct regex to be scraped as per Postgres connector.
…peruser (#115) **Summary** This PR adds the support for a non superuser to be configured as the connector user (database.user). Such a user is required to have the privileges listed in https://debezium.io/documentation/reference/2.5/connectors/postgresql.html#postgresql-permissions Specifically, the changes in this revision relate to how the consistent_point is specified to the YugabyteDB server in order to execute a consistent snapshot. **Test Plan** Added new test mvn -Dtest=PostgresConnectorIT#nonSuperUserSnapshotAndStreaming test
…nectorTask (#114) This PR is to add a higher level retry whenever there's a where while starting a PostgresConnectorTask, the failures can include but not limited to the following: 1. Failure of creating JDBC connection 2. Failure to execute query 3. Tserver/master restart 4. Node restart 5. Connection failure
…streaming (#116) ## Problem PG connector does not wait for acknowledgement of snapshot completion offset before transitioning to streaming. This can lead to an issue if there is a connector restart in the streaming phase and it goes for a snapshot on restart. In streaming phase, as soon as the 1st GetChanges call is made on the server, the retention barriers are lifted and so the server can no longer serve the snapshot records on a restart. Therefore it is important that the connector waits for acknowledgement of snapshot completion offset before it actually transitions to streaming. ## Solution This PR introduces a waiting mechanism for acknowledgement of snapshot completion offset before transitioning to streaming. We have introduced a custom heartbeat implementation that will dispatch heartbeat when forced heartbeat method is called but we'll dispatch nothing when a normal heartbeat method is called. With this PR, connector will dispatch heartbeats while waiting for the snapshot completion offset i.e during the transition phase. For these heartbeat calls, there is no need to set the `heartbeat.interval.ms` since we are making forced heartbeat calls which do not rely on this config. Note, this heartbeat call is only required to support applications using debezium engine/embedded engine. It is not required when the connector is run with kakfa-connect. ### Test Plan Manually deployed connector in a docker container and tested two scenarios: 0 snapshot records & non-zero snapshot records. Unit tests corresponding to these scenarios will be added in a separate PR.
#119) **Summary** This PR adds support for the INITIAL_ONLY snapshot mode for Yugabyte. In the case of Yugabyte also, the snapshot is consumed by executing a snapshot query (SELECT statement) . To ensure that the streaming phase continues exactly from where the snapshot left, this snapshot query is executed as of a specific database state. In YB, this database state is represented by a value of HybridTime. Changes due to transactions with commit_time strictly greater than this snapshot HybridTime will be consumed during the streaming phase. This value for HybridTime is the value of the "yb_restart_commit_ht" column of the pg_replication_slots view of the associated slot. Thus, in the case of Yugabyte, even for the INITIAL_ONLY snapshot mode, a slot needs to be created if one does not exist. With this approach, a connector can be deployed in INITIAL_ONLY mode to consume the initial snapshot. This can be followed by the deployment of another connector in NEVER mode. This connector will continue the streaming from exactly where the snapshot left. **Test Plan** 1. Added new test -` mvn -Dtest=PostgresConnectorIT#snapshotInitialOnlyFollowedByNever test ` 2. Enabled existing test - `mvn -Dtest=PostgresConnectorIT#shouldNotProduceEventsWithInitialOnlySnapshot test` 3. Enabled existing test - `mvn -Dtest=PostgresConnectorIT#shouldPerformSnapshotOnceForInitialOnlySnapshotMode test `
… image (#118) This PR adds the dependencies for the `AvroConverter` to function in the Kafka Connect environment. The dependencies will only be added at the time of building the docker image.
This PR adds a log which will be print the IP of the node every time a connection is created.
Retry in case of failures while task is restarting. Right now any kind of failure will lead to task throwing RetriableException exception causing Task restart.
…te source (#120) **Summary** This PR enables 30/33 tests in IncrementalSnapshotIT for Yugabyte source The tests that are excluded are 1. updates 2. updatesLargeChunk 3. updatesWithRestart **Test Plan** `mvn -Dtest=IncrementalSnapshotIT test`
This PR comments out the part in the init_database i.e. the startup script during tests where some extensions are being installed - it is taking more than 2 minutes at this stage and since we do not need it in the tests we use, it can be skipped.
Throw retry for all exceptions. In future, we will need to throw runtime exception for wrong configurations.
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…r image (#129) This PR only changes the link in the `Dockerfile` to fetch the latest custom sink connector jar from GitHub. According to PR yugabyte/kafka-connect-jdbc#3, changes include the following: 1. Addition of 3 new configuration properties * `log.table.balance`: i. Default is `false` but when set to `true`, the sink connector will execute a query to get the table balance from the target table. ii. Note that this is only applicable for consistency related tests where the given query is applicable - it will fail if set in any other tests. * `expected.total.balance` i. Default is `1000000` (1M) which can be changed to whatever value we are expecting the total balance to be in the target table. * `tables.for.balance` i. This takes a comma separated string value for all the table names from which the sink connector is supposed to extract balances from. ii. This property will only be valid when `log.table.balance` is specified as `true` iii. There is no default for this property so if `log.table.balance` is set to `true` and `tables.for.balance` is not specified then we will throw a `RuntimeException` 2. Log additions to aid debugging.
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…is set (#131) ## Problem PG connector filters out record based on its starting point (WAL position), which in turn depends on the offset received from Kafka. So, in case, the starting point corresponds to a record in the middle of a transaction, PG connector will filter out the records of that transaction with LSN < starting point. This creates a problem in the downstream pipeline expects consistency of data. Filtering of records leads to PG connector shipping transaction with missing records. When such a transaction is applied on the sink, consistency breaks. ## Solution When 'provide.transaction.metadata' connector configuration is set, PG connector ships transaction boundary records BEGIN/COMMIT. Based on these boundary records, sink connector writes data maintaining consistency. Therefore, when this connector config is set, we will disable filtering records based on WAL Resume position. ## Testing Manually testing - Ran the connector with this fix in our QA runs where the issue was first discovered. All 10 runs triggered passed. Unit testing - Cannot reproduce the above mentioned scenario in a unit test.
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…rds with CHANGE (#106)
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This PR adds a configuration to let the user disable consistent snapshot i.e. `yb.consistent.snapshot` to the connector which is enabled by default. Setting consistent snapshot means setting/establishing the boundary between snapshot records (records that existed at the time of stream creation) and streaming records. If `yb.consistent.snapshot` is disabled i.e. set to `false`: - We will not be setting a boundary for snapshot - If the connector restarts after taking a snapshot but before acknowledging the streaming LSN, the snapshot will be taken again. This can result in some records being received both during the snapshot phase and the streaming phase.
## Problem The Postgres JDVC driver jar being used currently has a `CRITICAL` vulnerability `CVE-2024-1597` as identified by `trivy` in the version `42.6.0`. ## Solution For the fix, this PR upgrades the jar to a driver version `42.6.1` which does not have the vulnerability.
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This PR adds a GitHub action to the repository which can be run manually to publish a Docker image to Quay and create a GitHub release draft with a fat jar.
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This PR fixes the path for the connector jar file to pick up the correct artefact to be packaged in the Docker image.
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## Problem Suppose we have a column with a non-basic value like `timestamp` - the code for converting the values here is following: ```java if (connectorConfig.plugin().isYBOutput()) { if (value != null && !UnchangedToastedReplicationMessageColumn.isUnchangedToastedValue(value)) { value = converter.convert(((Object[]) value)[0]); Struct cell = new Struct(fields[i].schema()); cell.put("value", value); cell.put("set", true); result.put(fields[i], cell); } else { result.put(fields[i], null); } } else { result.put(fields[i], value); } ``` The `else` block above has a missing line which should utilise a converter for the value. ## Solution This PR modifies the `PostgresSchema#getTableSchemaBuilder` method to return the default `TableSchemaBuilder` when the plugin is NOT `yboutput`. Additionally, this PR fixes the `else` block in `PGTableSchemaBuilder` with the required conversion and adds tests verifying the same for `pgoutput` by adding the following logic: ```java ... else { value = converter.convert(value); result.put(fields[i], value); } ... ```
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This PR adds the logic to throw an exception if a connector is deployed with `decimal.handling.mode=PRECISE`.
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This PR adds a test which works with both `pgoutput` and `yboutput` and tests that if we update the column of any type, we should get the relevant change event.
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This PR introduces the following change: * Version of the pom in the jar file will now be the same as the one being specified in the input form
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This PR changes the following: 1. Adds a plugin to the pom.xml file to package the connector according to Confluent specifications 2. Adds a GitHub pipeline to automate the above packaging process
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## Problem For very large tables, the default `SELECT *` query can take a really long time to complete leading to longer time for snapshots. ## Solution This PR aims to implement snapshotting the table in parallel using an inbuilt method `yb_hash_code` to only run the query for a given hash range. The following 2 configuration properties are introduced with this PR: 1. A new `snapshot.mode` called `parallel` - this will behave exactly like `initial_only` but we will have the ability to launch multiple tasks. 2. `primary.key.hash.columns` - this config takes in a comma separated values of the primary key hash component of the table. > **Note:** When `snapshot.mode` is set to `parallel`, we will not support providing regex in the property `table.include.list` and the user will need to specify the full name of the table in the property. Additionally, we will only allow one table in the `table.include.list` if `snapshot.mode` is `parallel`.
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…on (#163) ## Problem With the introduction of the parallel snapshot model, we can have multiple tasks when the snapshot mode is set to `parallel`. This introduces a problem at the underlying layer when the connector stores the sourceInfo for its partitions i.e. `PostgresPartition` objects in Kafka. The `PostgresPartition` is identified by a map which has a structure `{"server", topicPrefix}` - currently this is the same for all the `PostgresPartition` objects which are created by the tasks when `snapshot.mode` is `parallel` and hence they all end up referring to the same source partition in the Kafka topic. Subsequently, what happens is that (assume that we have 2 tasks i.e. 0 and 1): 1. One task (task_0) completes the snapshot while the other is yet to start. a. After completion, `task_0` updates the `sourceInfo` saying that its snapshot is completed. 2. When task_1 starts up, it reads the same `sourceInfo` object and concludes that the snapshot is completed so it skips its snapshot. The above situation will cause a data loss since task_1 will never actually take a snapshot. ## Solution This PR implements a short term solution where we simply add the task ID to the partition so that each `PostgresPartition` can identity a sourcePartition uniquely, the identifying map will now become `{"server", topicPrefix_taskId}`. **Note:** This solution is a quick fix for the problem given that the number of tasks in the connector remain the same. This partially fixes yugabyte/yugabyte-db#24555
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…query (#164) This PR makes the changes to set the transaction isolation level to `SERIALIZABLE, READ ONLY, DEFERRABLE` before executing the snapshot read query.
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## Problem With the current retry model, it was being noticed that the connector ended up retrying infinitely whenever an exception was thrown. This could lead to false positives that the connector is still running while the retries will keep failing. ## Solution This PR addresses the issue by adding a check to the task layer so now if the retry count reaches the maximum value, the connector will exit and the task will reach in a failed state - this will help the end user know the status of the task and act accordingly. This PR also redefines the following properties and changes their default values: 1. `errors.max.retries` - new default value is 60 2. `retriable.restart.connector.wait.ms` - new default value is 30000 (30s) With the above change, the complete retry duration with the above default configuration will now be 30 minutes. This effectively means that if the connector/s task fails after exhausting all the retries then it will go into a `FAILED` state. For example, if the connector is needed to retry for a total of 30 minutes then we can handle it in 2 ways: 1. **By fixing the number of retries:** Let's say we want the number of retries to be fixed to 15 so we can now configure our retry delay accordingly i.e. `30 / 15 = 2 minutes = 120 s = 120000 ms`, so the configuration will now add: ```json "retriable.restart.connector.wait.ms":"120000", "errors.max.retries":"15" ``` 4. **By fixing the retry delay:** If we want to have a retry delay of a minute then we will configure the number of retries accordingly i.e. `30 / 1 = 30 retries`, so the configuration will now be: ```json "retriable.restart.connector.wait.ms":"60000", "errors.max.retries":"30" ```
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This PR adds a bug fix which was causing one less number of retries, for example, if `errors.max.retries` was set to 5, the connector was only retrying for 4 times. Additionally, this PR adds a test to verify the logic.
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…d structure (#168) This PR adds a transformer `PGCompatible` with full path `io.debezium.connector.postgresql.transforms.yugabytedb`, this will be helpful in converting the structure of the emitted events to match the one emitted by standard Debezium connectors. **Example:** Consider the following schema for a table `test`: `(id INT PRIMARY KEY, name TEXT, age INT)` - If a record is inserted having values `(1, 'John Doe', 25)` then after using the above transformer, the `payload` of the record would look like: ```json "payload": { "id": 1, "name": "John Doe", "age": 25 } ``` - If the same record is now updated and age is changed to 30 i.e. `UPDATE test SET age = 30 WHERE id = 1;` then the `payload` would look like: ```json "payload": { "id": 1, "name": null, "age": 30 } ``` > **NOTE:** The above example assumes that the replica identity of the table is `CHANGE` and that is how the assumption was made that the `UPDATE` event will not contain the value for the fields which were not updated. For more information on replica identity, see [YugabyteDB docs](https://docs.yugabyte.com/preview/explore/change-data-capture/using-logical-replication/key-concepts/#replica-identity).
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