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In eXpress-D, we've implemented a distributed EM solution to the fragment assignment problem using Spark, a data analytics framework that can scale by leveraging compute clusters within datacenters - "the cloud". The selections below offer guides to running eXpress-D locally and on EC2. More advanced users can check out the tuning and configuration guides, which document eXpress-D, Spark, and JVM parameters that can be used to optimize eXpress-D performance.

Downloads | User Documentation | More Information

User Documentation

All issues and source code is monitored through GitHub (i.e commits, pull requests). For any questions about running locally or distributedly, you can post on the eXpress users group.

Running Locally

Running on EC2

eXpress-D Tuning Guide

eXpress-D Configuration Guide

More Information

Our paper, "Fragment assignment in the cloud with eXpress-D", is under submission!