milvus/cpp

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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 that supports similarity search of large-scale vectors. Built on optimized indexing algorithm, it is compatible with major AI/ML models.

Milvus was developed by ZILLIZ, a tech startup that intends to reinvent data science, with the purpose of providing enterprises with efficient and scalable similarity search and analysis of feature vectors and unstructured data.

Milvus provides stable Python, C++ and Java APIs.

Keep up-to-date with newest releases and latest updates by reading Milvus release notes.

• GPU-accelerated search engine

  Milvus is designed for the largest scale of vector index. CPU/GPU heterogeneous computing architecture allows you to process data at a speed 1000 times faster.

• Intelligent index

  With a “Decide Your Own Algorithm” approach, you can embed machine learning and advanced algorithms into Milvus without the headache of complex data engineering or migrating data between disparate systems. Milvus is built on optimized indexing algorithm based on quantization indexing, tree-based and graph indexing methods.

• Strong scalability

  The data is stored and computed on a distributed architecture. This lets you scale data sizes up and down without redesigning the system.

Architecture

Get started

Install and start Milvus server

Use Docker

Use Docker to install Milvus is a breeze. See the Milvus install guide for details.

Use source code

Compilation

Step 1 Install necessary tools

# Install tools
Centos7 : 
$ yum install gfortran qt4 flex bison 
$ yum install mysql-devel mysql
    
Ubuntu 16.04 or 18.04: 
$ sudo apt-get install gfortran qt4-qmake flex bison 
$ sudo apt-get install libmysqlclient-dev mysql-client

Verify the existence of libmysqlclient_r.so:

# Verify existence
$ locate libmysqlclient_r.so

If not, you need to create a symbolic link:

# Locate libmysqlclient.so
$ sudo updatedb
$ locate libmysqlclient.so 

# Create symbolic link
$ sudo ln -s /path/to/libmysqlclient.so /path/to/libmysqlclient_r.so

Step 2 Build

$ cd [Milvus sourcecode path]/cpp
$ ./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]/cpp/milvus.

If you encounter the following error message, protocol https not supported or disabled in libcurl

please reinstall CMake with curl:

1. Install curl development files:

   CentOS 7:   
   $ yum install curl-devel
   Ubuntu 16.04 or 18.04: 
   $ sudo apt-get install libcurl4-openssl-dev
   

2. Install CMake 3.14:

   $ ./bootstrap --system-curl 
   $ make 
   $ sudo make install
   

code format and linting

Install clang-format and clang-tidy

CentOS 7:   
$ yum install clang
Ubuntu 16.04: 
$ sudo apt-get install clang-tidy
$ sudo su
$ wget -O - https://apt.llvm.org/llvm-snapshot.gpg.key | sudo apt-key add -
$ apt-add-repository "deb http://apt.llvm.org/xenial/ llvm-toolchain-xenial-6.0 main"
$ apt-get update
$ apt-get install clang-format-6.0
Ubuntu 18.04: 
$ sudo apt-get install clang-tidy clang-format

$ rm cmake_build/CMakeCache.txt

Check code style

$ ./build.sh -l

To format the code

$ cd cmake_build
$ make clang-format

Run unit test

$ ./build.sh -u

Run code coverage

Install lcov

CentOS 7:   
$ yum install lcov
Ubuntu 16.04 or 18.04: 
$ sudo apt-get install lcov

$ ./build.sh -u -c

Launch Milvus server

$ cd [Milvus root path]/cpp/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]/cpp/milvus/bin
 $ ./sdk_simple

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](CODE OF CONDUCT.md) 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.

Resources

Milvus official website

Milvus docs

Milvus blog

Milvus CSDN

Milvus roadmap

License

Apache 2.0 license