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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]/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
.
If you encounter the following error message,
protocol https not supported or disabled in libcurl
please reinstall CMake with curl:
-
Install curl development files:
CentOS 7: $ yum install curl-devel Ubuntu 16.04 or 18.04: $ sudo apt-get install libcurl4-openssl-dev
-
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
Run mysql docker
docker pull mysql:latest
docker run -p 3306:3306 -e MYSQL_ROOT_PASSWORD=123456 -d mysql:latest
Run code coverage
$ ./coverage.sh -u root -p 123456 -t 127.0.0.1
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
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.