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feat: support pgvector extension #445

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merged 1 commit into from
Nov 8, 2023

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The pgvector plugin is a plugin for PostgreSQL that provides high-performance vector data types and related query capabilities. This plugin makes it more efficient and convenient to store and process vector data in PostgreSQL.

Here are some features and functionalities of the pgvector plugin:

  1. Vector data type: The pgvector plugin introduces a new data type called "vector" that can be used to store and manipulate

The pgvector plugin is a plugin for PostgreSQL that provides high-performance vector data types and related query capabilities. This plugin makes it more efficient and convenient to store and process vector data in PostgreSQL.

Here are some features and functionalities of the pgvector plugin:

  1. Vector data type: The pgvector plugin introduces a new data type called "vector" that can be used to store and manipulate high-dimensional vector data.

  2. Vector indexing: pgvector provides support for indexing and querying vector data, making it easier to perform similarity searches, clustering, and classification operations on vector data. The plugin supports GIN and GiST index types.

  3. Vector operations: pgvector provides a range of vector operation functions, allowing for addition, subtraction, dot product calculation, and length calculation between vectors.

  4. Similarity search: The pgvector plugin supports similarity searches based on vector similarity metrics. It enables similarity calculation and search using cosine similarity and other measurement methods.

  5. High performance: pgvector is optimized for vector data by utilizing SIMD instructions and efficient data structures, ensuring high-performance vector operations and queries.

  6. Extensibility: As an open-source project, the pgvector plugin offers flexible custom extension interfaces, allowing users to customize and extend its functionality based on their specific needs.

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CLAassistant commented Nov 7, 2023

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polardb-bot bot commented Nov 7, 2023

Hi @mrdrivingduck ~ Thanks for your contribution in this PR. ❤️

Please make sure that your PR conforms the standard, and has passed all the checks.

We will review your PR as soon as possible.

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polardb-bot bot commented Nov 7, 2023

Hey @mrdrivingduck :

Something wrong occuried during the checks of your commit 😟, please check the detail:

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@polardb-bot polardb-bot bot added the ci/failure CI status is failure label Nov 7, 2023
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polardb-bot bot commented Nov 8, 2023

Hey @mrdrivingduck :

Something wrong occuried during the checks of your commit 😟, please check the detail:

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@polardb-bot polardb-bot bot added ci/failure CI status is failure and removed ci/failure CI status is failure labels Nov 8, 2023
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Hey @mrdrivingduck :

Congratulations~ 🎉 Your commit has passed all the checks. Please wait for further manual review.

@polardb-bot polardb-bot bot added ci/success CI status is success and removed ci/failure CI status is failure labels Nov 8, 2023
The pgvector plugin is a plugin for PostgreSQL that provides
high-performance vector data types and related query capabilities.
This plugin makes it more efficient and convenient to store and
process vector data in PostgreSQL.

Here are some features and functionalities of the pgvector plugin:

1. Vector data type: The pgvector plugin introduces a new data
type called "vector" that can be used to store and manipulate

The pgvector plugin is a plugin for PostgreSQL that provides
high-performance vector data types and related query capabilities.
This plugin makes it more efficient and convenient to store and
process vector data in PostgreSQL.

Here are some features and functionalities of the pgvector plugin:

1. Vector data type: The pgvector plugin introduces a new data
type called "vector" that can be used to store and manipulate
high-dimensional vector data.

2. Vector indexing: pgvector provides support for indexing and
querying vector data, making it easier to perform similarity searches,
clustering, and classification operations on vector data. The plugin
supports GIN and GiST index types.

3. Vector operations: pgvector provides a range of vector operation
functions, allowing for addition, subtraction, dot product calculation,
and length calculation between vectors.

4. Similarity search: The pgvector plugin supports similarity searches
based on vector similarity metrics. It enables similarity calculation and
search using cosine similarity and other measurement methods.

5. High performance: pgvector is optimized for vector data by utilizing
SIMD instructions and efficient data structures, ensuring high-performance
vector operations and queries.

6. Extensibility: As an open-source project, the pgvector plugin offers flexible
custom extension interfaces, allowing users to customize and extend its
functionality based on their specific needs.
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polardb-bot bot commented Nov 8, 2023

Hey @mrdrivingduck :

Congratulations~ 🎉 Your commit has passed all the checks. Please wait for further manual review.

@polardb-bot polardb-bot bot added ci/success CI status is success and removed ci/success CI status is success labels Nov 8, 2023
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/rebase-and-merge

@polardb-bot polardb-bot bot merged commit 0695ead into ApsaraDB:POLARDB_11_DEV Nov 8, 2023
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polardb-bot bot commented Nov 8, 2023

@mrdrivingduck PR has been merged. 🍗

Thanks again for the contributors involved in this thread: ❤️

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3 participants