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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

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• Installation Guide
• Quick Start Guide for Users
• Quick Start Guide for Developers

General Information

Learn about MADlib.

• MADlib website 
• Quick start Jupyter notebooks for many MADlib algorithms

General Information

• MADlib website 
• Greenplum database YouTube channel with MADlib content YouTube channel including step-by-step guides for common algorithms
• Module and algorithm documentation
• FAQ

Developer Documentation

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• Source code repo
• Contribution Guidelines
• Documentation Guide (Doxygen)
• Ideas for contribution 
• Algorithm technical design document

Architecture

See how the pieces fit together. 

• Architecture
• Module Anatomy

Release Notes

See what has been released.

• Release notes
• Downloads

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. Eigen 3.2.2 is a C++ template library for linear algebra
4. PyYAML 3.10 is a YAML parser and emitter for Python
5. PyXB 1.2.4 is a Python library for XML Schema Bindings
6. Porter2 stemmer reduces workds to common roots for comparison and operating on.
7. UseLATEX.cmake contains CMAKE commands to use the LaTeX compiler

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

• MAD Skills : New Analysis Practices for Big Data (VLDB 2009)
• Hybrid In-Database Inference for Declarative Information Extraction (SIGMOD 2011)
• Towards a Unified Architecture for In-Database Analytics (SIGMOD 2012)
• The MADlib Analytics Library or MAD Skills, the SQL (VLDB 2012)

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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