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MADlib graduated to an Apache Top Level Project on 7/19/17.  Read the press release. 

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

It provides data-parallel implementations of mathematical, statistical,

graph and machine learning methods for structured and unstructured data.

 

Quick Start Guides

Get going with a minimum of fuss.

 

General Information

Developer Documentation

 

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 General Information

Learn about MADlib.

Architecture

See how the pieces fit together.

 

Architecture

 

 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

 

Release Notes

Licensing

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

 

 Release Notes

 

Historical release notes for releases prior to move to ASF.

 

 Papers and Talks

 ASF licensing guidance for MADlib pertaining to its pre-Apache history as an open source project with BSD licensing is described here.

Papers

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Related Software

 

  • PivotalR

     

    -

    PivotalR also

    lets the user run the functions of the open-source big-data machine learning

    package 

    package MADlib

     directly

    directly from R.

  • PyMADlib  - PyMADlib is a python nascent Python wrapper for MADlib, which brings you the power and flexibility of python with the number crunching power of of MADlib.


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