595ebdb5e3
Bumps [pyyaml](https://github.com/yaml/pyyaml) from 3.12 to 5.1. - [Release notes](https://github.com/yaml/pyyaml/releases) - [Changelog](https://github.com/yaml/pyyaml/blob/master/CHANGES) - [Commits](https://github.com/yaml/pyyaml/compare/3.12...5.1) Signed-off-by: dependabot[bot] <support@github.com> Former-commit-id: 24d3855981565733ad377ba669262fe587444eb4 |
||
---|---|---|
.github/ISSUE_TEMPLATE | ||
ci | ||
core | ||
docker | ||
tests | ||
.clang-format | ||
.clang-tidy | ||
.clang-tidy-ignore | ||
.gitignore | ||
CHANGELOG.md | ||
CODE_OF_CONDUCT.md | ||
codecov.yaml | ||
CONTRIBUTING.md | ||
LICENSE | ||
NOTICE.md | ||
README.md |
Welcome to Milvus
Firstly, welcome, and thanks for your interest in Milvus! No matter who you are, what you do, we greatly appreciate your contribution to help us reinvent data science with Milvus. 🍻
What is Milvus
Milvus is an open source vector search engine which provides state-of-the-art similarity search and analysis for billion-scale feature vectors.
Milvus provides stable Python, Java and C++ APIs.
Keep up-to-date with newest releases and latest updates by reading Milvus release notes.
-
GPU-accelerated search engine
Milvus uses CPU/GPU heterogeneous computing architecture to process feature vectors, and are orders of magnitudes faster than traditional databases.
-
Various indexes
Milvus supports quantization indexing, tree-based indexing, and graph indexing algorithms.
-
Intelligent scheduling
Milvus optimizes the search computation and index building according to your data size and available resources.
-
Horizontal scalability
Milvus expands computation and storage by adding nodes during runtime, which allows you to scale the data size without redesigning the system.
Architecture
Get started
Hardware Requirements
Component | Recommended configuration |
---|---|
CPU | Intel CPU Haswell or higher |
GPU | NVIDIA Pascal series or higher |
Memory | 8 GB or more (depends on data size) |
Storage | SATA 3.0 SSD or higher |
Install using docker
Use Docker to install Milvus is a breeze. See the Milvus install guide for details.
Build from source
Software requirements
- Ubuntu 18.04 or higher
- CMake 3.14 or higher
- CUDA 10.0 or higher
- NVIDIA driver 418 or higher
Compilation
Step 1 Install dependencies
$ cd [Milvus sourcecode path]/core
./ubuntu_build_deps.sh
Step 2 Build
$ cd [Milvus sourcecode path]/core
$ ./build.sh -t Debug
or
$ ./build.sh -t Release
When the build is completed, all the stuff that you need in order to run Milvus will be installed under [Milvus root path]/core/milvus
.
Launch Milvus server
$ cd [Milvus root path]/core/milvus
Add lib/
directory to LD_LIBRARY_PATH
$ export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/path/to/milvus/lib
Then start Milvus server:
$ cd scripts
$ ./start_server.sh
To stop Milvus server, run:
$ ./stop_server.sh
To edit Milvus settings in conf/server_config.yaml
and conf/log_config.conf
, please read Milvus Configuration.
Try your first Milvus program
Run Python example code
Make sure Python 3.4 or higher is already installed and in use.
Install Milvus Python SDK.
# Install Milvus Python SDK
$ pip install pymilvus==0.2.0
Create a new file example.py
, and add Python example code to it.
Run the example code.
# Run Milvus Python example
$ python3 example.py
Run C++ example code
# Run Milvus C++ example
$ cd [Milvus root path]/core/milvus/bin
$ ./sdk_simple
Run Java example code
Make sure Java 8 or higher is already installed.
Refer to this link for the example code.
Contribution guidelines
Contributions are welcomed and greatly appreciated. If you want to contribute to Milvus, please read our contribution guidelines. 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 the Milvus community
To connect with other users and contributors, welcome to join our slack channel.
Milvus Roadmap
Please read our roadmap to learn about upcoming features.