From d270f23e51d8f19034e6f1c1591e06712b1a7d23 Mon Sep 17 00:00:00 2001 From: Jinjing Zhou <VoVAllen@users.noreply.github.com> Date: Mon, 3 Jun 2024 22:15:10 -0700 Subject: [PATCH] Update readme (#7) Signed-off-by: Jinjing Zhou <VoVAllen@users.noreply.github.com> --- LICENSE | 201 ++++++++++++++++++++++++++++++++++++++++++++++++++++++ README.md | 75 +++++++++++++------- 2 files changed, 251 insertions(+), 25 deletions(-) create mode 100644 LICENSE diff --git a/LICENSE b/LICENSE new file mode 100644 index 0000000..d4911bd --- /dev/null +++ b/LICENSE @@ -0,0 +1,201 @@ + Apache License + Version 2.0, January 2004 + http://www.apache.org/licenses/ + + TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + + 1. 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We also recommend that a + file or class name and description of purpose be included on the + same "printed page" as the copyright notice for easier + identification within third-party archives. + + Copyright [2024] TensorChord + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. \ No newline at end of file diff --git a/README.md b/README.md index 30f560e..b7a4021 100644 --- a/README.md +++ b/README.md @@ -1,40 +1,37 @@ -# pg_bestmatch +# pg_bestmatch.rs -This PostgreSQL extension provides functionalities for BM25 text queries, allowing efficient full-text search by converting text into sparse vectors. This enables integration with vector search extensions such as `pgvecto.rs` or `pgvector`. +This PostgreSQL extension provides functionalities for BM25 text queries, generateing BM25 statistic sparse vectors for text. BM25 outperforms dense vector-based retrieval methods in many [RAG benchmark tasks](https://hazyresearch.stanford.edu/blog/2024-05-20-m2-bert-retrieval). -## Installation +User can use vector search extensions such as `pgvecto.rs` or `pgvector` for efficient searches in postgres. -```sql -CREATE EXTENSION pg_bestmatch; -SET search_path TO public, bm_catalog; -``` +> [!IMPORTANT] +> Based on our initial tests, HNSW indexing does not support the sparse vectors generated by BM25 very well. The high sparsity prevents effective navigation within the graph. -## Build from source -Before building, you should have `PostgreSQL`, `Rust` and `Cargo` installed on your system. - -1. Install `cargo-pgrx`. - -```sh -cargo install cargo-pgrx --version v0.12.0-alpha.1 -``` +* [Installation](#installation) +* [How does it work?](#how-does-it-work) +* [Usage](#usage) +* [Build from source](#build-from-source) +* [Comparison with pg_search](#comparison-with-pg_search) +* [Reference](#Reference) -2. Initialize `cargo-pgrx`. +## Installation -```sh -cargo pgrx init --pg16=$(which pg_config) # assuming that you have PostgreSQL 16 installed +```sql +CREATE EXTENSION pg_bestmatch; +SET search_path TO public, bm_catalog; ``` -3. Build. - -```sh -cargo pgrx install --release # if you want to install it on your machine -cargo pgrx package # if you want to package `pg_bestmatch` -``` +## How does it work? +- Create an BM25 statistics based on your document set by `bm25_create(table_name, column_name, statistic_name);`. It will create a materilized view to record the stats. +- Generate document sparse vector by `bm25_document_to_svector(statistic_name, passage)` +- For query, generate query sparse vector `bm25_query_to_svector(statistic_name, query)` +- Calculate the score by dot product between the query sparse vector and the document sparse vector +- Currently we use huggingface tokenizer with `bert-base-uncased` vocabulary set to tokenize words. Might support more configuration on tokenizer in the future. ## Usage -Here is an example workflow demonstrating the usage of this extension with the example of [Stanford LoCo benchmark](https://hazyresearch.stanford.edu/blog/2024-01-11-m2-bert-retrieval). +Here is an example workflow demonstrating the usage of this extension with the example of [Stanford LoCo benchmark](https://hazyresearch.stanford.edu/blog/2024-05-20-m2-bert-retrieval). 0. Load the dataset. Here is a script for you if you want to experience `pg_bestmatch` with the dataset. @@ -123,6 +120,34 @@ SELECT sum((array[answer_pids] = array(SELECT pid FROM documents WHERE queries.d This workflow showcases how to leverage BM25 text queries and vector search in PostgreSQL using this extension. The Top 1 recall of BM25 on this dataset is `0.77`. If you reproduce the result, your operations are correct. + +## Build from source + +Before building, you should have `PostgreSQL`, `Rust` and `Cargo` installed on your system. + +1. Install `cargo-pgrx`. + +```sh +cargo install cargo-pgrx --version v0.12.0-alpha.1 +``` + +2. Initialize `cargo-pgrx`. + +```sh +cargo pgrx init --pg16=$(which pg_config) # assuming that you have PostgreSQL 16 installed +``` + +3. Build. + +```sh +cargo pgrx install --release # if you want to install it on your machine +cargo pgrx package # if you want to package `pg_bestmatch` +``` + +## Comparison with pg_search +- `pg_bestmatch.rs` only provides methods for generating sparse vectors and does not support index-based search (which can be achieved by pgvecto.rs or pgvector). +- `pg_search` performs BM25 retrieval via the external `tantivy` engine, which may have limitations when combined with transactions, filters, or JOIN operations. Since `pg_bestmatch.rs` is entirely native to Postgres, it offers full compatibility with these operations inside postgres. + ## Reference - `tokenize`