yukun 3e1b2ab4a0
Filtering by numeric scalar fields prototype (#1919)
* Add hybrid request handler

Signed-off-by: fishpenguin <kun.yu@zilliz.com>

* Add C++ sdk for createcollection and insertentities

Signed-off-by: fishpenguin <kun.yu@zilliz.com>

* Add RequestHandler

Signed-off-by: fishpenguin <kun.yu@zilliz.com>

* Add test case for hybrid insert

Signed-off-by: fishpenguin <kun.yu@zilliz.com>

* Fix sqlite bug for createcollection

Signed-off-by: fishpenguin <kun.yu@zilliz.com>

* Add HybridQuery Handler DBImpl and ExecBinaryQuery

Signed-off-by: fishpenguin <kun.yu@zilliz.com>

* Add HybridSearch sdk

Signed-off-by: fishpenguin <kun.yu@zilliz.com>

* Add HybridSearch test case

Signed-off-by: fishpenguin <kun.yu@zilliz.com>

* Fix HybridSearch bug

Signed-off-by: fishpenguin <kun.yu@zilliz.com>

* Fix HybridSearch crash bug

Signed-off-by: fishpenguin <kun.yu@zilliz.com>

* Change void* to vector<uint8_t> in Attr codec

Signed-off-by: fishpenguin <kun.yu@zilliz.com>

* Add context and new search task

Signed-off-by: fishpenguin <kun.yu@zilliz.com>

* Add merge for Hybrid

Signed-off-by: fishpenguin <kun.yu@zilliz.com>

* Add AST validation

Signed-off-by: fishpenguin <kun.yu@zilliz.com>

* Add unittest for hybrid

Signed-off-by: fishpenguin <kun.yu@zilliz.com>

* Fix hybrid search nq bug

Signed-off-by: fishpenguin <kun.yu@zilliz.com>

* Fix bugs after merge master

Signed-off-by: fishpenguin <kun.yu@zilliz.com>

* Fix clang format

Signed-off-by: fishpenguin <kun.yu@zilliz.com>

* Fix unittest bugs

Signed-off-by: fishpenguin <kun.yu@zilliz.com>

* Fix Codacy

Signed-off-by: fishpenguin <kun.yu@zilliz.com>

* Fix compact unittest bug

Signed-off-by: fishpenguin <kun.yu@zilliz.com>

* Remove grpc request in hybridsearchcontext

Signed-off-by: fishpenguin <kun.yu@zilliz.com>

* Fix some codacy quality issue

Signed-off-by: fishpenguin <kun.yu@zilliz.com>

* Fix HYBRID_DB_TEST bug

Signed-off-by: fishpenguin <kun.yu@zilliz.com>

* Annotate new search task

Signed-off-by: fishpenguin <kun.yu@zilliz.com>

* Add Hybrid RPC handler unittest

Signed-off-by: fishpenguin <kun.yu@zilliz.com>

* Fix logs

Signed-off-by: fishpenguin <kun.yu@zilliz.com>

* Add HybridSearch unittest

Signed-off-by: fishpenguin <kun.yu@zilliz.com>
2020-04-16 14:54:12 +08:00
2020-04-15 21:32:20 +08:00
2019-09-28 12:36:14 +08:00
2019-09-28 15:00:26 +08:00
2019-12-16 14:07:20 +08:00
2020-03-03 00:25:22 +08:00
2020-04-01 18:51:26 +08:00
2020-03-03 00:25:22 +08:00
2020-03-02 22:55:18 +08:00
2019-09-16 14:43:44 +08:00
2020-03-27 09:52:31 +08:00
2020-02-24 05:48:43 +08:00
2020-04-03 11:15:43 +08:00
2020-04-03 11:15:43 +08:00
2020-03-03 00:25:22 +08:00
2020-03-03 00:25:22 +08:00
2020-03-03 00:25:22 +08:00

Milvuslogo

Slack GitHub Docker pulls

Build Status CII Best Practices codecov codebeat badge CodeFactor Grade Codacy Badge

English | 中文版

What is Milvus

As an open source vector similarity search engine, Milvus is easy-to-use, highly reliable, scalable, robust, and blazing fast. Adopted by over 100 organizations and institutions worldwide, Milvus empowers applications in a variety of fields, including image processing, computer vision, natural language processing, voice recognition, recommender systems, drug discovery, etc.

Milvus has the following architecture:

arch

For more detailed introduction of Milvus and its architecture, see Milvus overview. Keep up-to-date with newest releases and latest updates by reading Milvus release notes.

Milvus is an LF AI Foundation incubation project. Learn more at lfai.foundation.

Get started

Install Milvus

See the Milvus install guide to install Milvus using Docker. To install Milvus from source code, see build from source.

Try example programs

Try an example program with Milvus using Python, Java, Go, or C++ example code.

Supported clients

Application scenarios

You can use Milvus to build intelligent systems in a variety of AI application scenarios. Refer to Milvus Scenarios for live demos. You can also refer to Milvus Bootcamp for detailed solutions and application scenarios.

Benchmark

See our test reports for more information about performance benchmarking of different indexes in Milvus.

Roadmap

To learn what's coming up soon in Milvus, read our Roadmap.

It is a Work in Progress, and is subject to reasonable adjustments when necessary. And we greatly welcome any comments/requirements/suggestions regarding Milvus roadmap.👏

Contribution guidelines

Contributions are welcomed and greatly appreciated. Please read our contribution guidelines for detailed contribution workflow. This project adheres to the code of conduct of Milvus. By participating, you are expected to uphold this code.

We use GitHub issues to track issues and bugs. For general questions and public discussions, please join our community.

Join our community

❤️To connect with other users and contributors, welcome to join our Slack channel.

See our community repository to learn about our governance and access more community resources.

Resources

License

Apache License 2.0

Description
Milvus 是一款全球领先的开源向量数据库,赋能 AI 应用和向量相似度搜索,加速非结构化数据检索。
Readme Apache-2.0 216 MiB
Languages
Go 59%
C++ 19.7%
Python 19.5%
Shell 0.7%
Groovy 0.4%
Other 0.5%