Distributed Graph Mining, Made Easy

Arabesque is a distributed graph mining system that enables quick and easy development of graph mining algorithms, while providing a scalable and efficient implementation that runs on top of Hadoop/Spark.

Benefits of Arabesque:

Simple intuitive API, tuned for Graph Mining Problems
Handles all the complexity of Graph Mining Algorithms transparently
Highly Scalable
Efficient implementation: negligible overhead compared to equivalent centralized solutions
Support of large graphs with over a billion edges. It can process trillion of subgraphs in a commodity cluster.
Runs as an Apache Spark or Giraph Job.

News

We have a new Spark 2.0 based version download page.
"Graph Data Mining with Arabesque", SIGMOD 2017 demo paper

Documentation

Check our SOSP 2015 paper that describes the system.

Follow our programming guide to learn how to program graph mining applications on Arabesque. You can then try to run your code!

How to Use

Arabesque can be used in one of 2 ways:

Standalone - If you simply want to test/execute one of the example algorithms included in Arabesque, you can simply download the JAR file from our download page and use the supporting execution scripts to run your desired algorithm.
Framework - If you want to code your own graph mining algorithm on top of Arabesque, the easiest way to accomplish this is by forking our Arabeque skeleton project and follow the instructions in the README file.

Source code

Arabesque is open-sourced under the Apache 2.0 license.

The source code can be accessed from github.