You are viewing an old version of this page. View the current version.

Compare with Current View Page History

« Previous Version 8 Next »

        

 

MADlib® is an open-source library for scalable in-database analytics.

It provides data-parallel implementations of mathematical, statistical and machine learning methods for structured and unstructured data.

 

Quick Start Guides

Get going with a minimum of fuss.

 

 Developer Documentation

 

Contribute to the project.

 

 General Information

Learn about MADlib.

Architecture

See how the pieces fit together.

 

 

 Third Party Components

 

MADlib incorporates material from the following third-party components

 

  1. argparse 1.2.1 "provides an easy, declarative interface for creating command line tools"
  2. Boost 1.47.0 (or newer) "provides peer-reviewed portable C++ source libraries"
  3. doxypy 0.4.2 "is an input filter for Doxygen"
  4. Eigen 3.2.2 "is a C++ template library for linear algebra"
  5. PyYAML 3.10 "is a YAML parser and emitter for Python"
  6. PyXB 1.2.4 "is a Python library for XML Schema Bindings"

 

 Licensing

 

License information regarding MADlib and included third-party libraries can be found inside thelicense directory.

 

 Release Notes

 

Historical release notes for releases prior to move to ASF.

 

 Papers and Talks

 

 

 Related Software

 

  • PivotalR - PivotalR also lets the user run the functions of the open-source big-data machine learning package MADlib directly from R.
  • PyMADlib - PyMADlib is a python wrapper for MADlib, which brings you the power and flexibility of python with the number crunching power of MADlib.


  • No labels