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README.md

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Build Status

SAMOA: Scalable Advanced
Massive Online Analysis.

This repository is discontinued. The development of SAMOA has moved over to the Apache Software Foundation. Please subscribe to the dev mailing list to participate in the development, and use Jira to report bugs and propose new features. The new repository is mirrored on GitHub.

SAMOA is a platform for mining on big data streams. It is a distributed streaming machine learning (ML) framework that contains a programing abstraction for distributed streaming ML algorithms.

SAMOA enables development of new ML algorithms without dealing with the complexity of underlying streaming processing engines (SPE, such as Apache Storm and Apache S4). SAMOA also provides extensibility in integrating new SPEs into the framework. These features allow SAMOA users to develop distributed streaming ML algorithms once and to execute the algorithms in multiple SPEs, i.e., code the algorithms once and execute them in multiple SPEs.

Build

###Storm mode

Simply clone the repository and install SAMOA.

git clone git@github.com:yahoo/samoa.git
cd samoa
mvn -Pstorm package

The deployable jar for SAMOA will be in target/SAMOA-Storm-0.0.1-SNAPSHOT.jar.

###S4 mode

If you want to compile SAMOA for S4, you will need to install the S4 dependencies manually as explained in Executing SAMOA with Apache S4.

Once the dependencies if needed are installed, you can simply clone the repository and install SAMOA.

git clone git@github.com:yahoo/samoa.git
cd samoa
mvn -Ps4 package

###Local mode

If you want to test SAMOA in a local environment, simply clone the repository and install SAMOA.

git clone git@github.com:yahoo/samoa.git
cd samoa
mvn package

The deployable jar for SAMOA will be in target/SAMOA-Local-0.0.1-SNAPSHOT.jar.

Slides

SAMOA Slides

G. De Francisci Morales SAMOA: A Platform for Mining Big Data Streams Keynote Talk at RAMSS ’13: 2nd International Workshop on Real-Time Analysis and Mining of Social Streams WWW, Rio De Janeiro, 2013.

License

The use and distribution terms for this software are covered by the Apache License, Version 2.0 (http://www.apache.org/licenses/LICENSE-2.0.html).