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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

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Developer Documentation

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Architecture

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Release Notes

Historical release notes for releases prior to move to ASF. 

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

Papers

Related Software

  • PivotalR - lets the user run the functions of the open-source big-data machine learning package MADlib directly from R.

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


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