THIS IS A TEST INSTANCE. ALL YOUR CHANGES WILL BE LOST!!!!
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.
General Information
Learn about MADlib.
Developer Documentation
Contribute to the project.
- Source code repo
- Contribution Guidelines
- Documentation Guide (Doxygen)
- Ideas for contribution
- Algorithm technical design document
Architecture
See how the pieces fit together.
Release Notes
See what has been released.
- Last release
- Historical release notes for releases prior to move to ASF.
Third Party Components
MADlib incorporates material from the following third-party components:
argparse 1.2.1"provides an easy, declarative interface for creating command line tools"Boost 1.47.0 (or newer)"provides peer-reviewed portable C++ source libraries"doxypy 0.4.2"is an input filter for Doxygen"Eigen 3.2.2"is a C++ template library for linear algebra"PyYAML 3.10"is a YAML parser and emitter for Python"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.
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.
