The ARC-TS Data Science Platform is an upgraded Hadoop cluster currently available as a technology preview with no associated charges to U-M researchers. The ARC-TS Hadoop cluster is an on-campus resource that provides a different service level than most cloud-based Hadoop offerings, including:

  • high-bandwidth data transfer to and from other campus data storage locations with no data transfer costs
  • very high-speed inter-node connections using 40Gb/s Ethernet

The cluster provides 112TB of total usable disk space, 40GbE inter-node networking, Hadoop version 2.3.0, and several additional data science tools.

Aside from Hadoop and its Distributed File System, the ARC-TS data science service includes:

  • Pig, a high-level language that enables substantial parallelization, allowing the analysis of very large data sets.
  • Hive, data warehouse software that facilitates querying and managing large datasets residing in distributed storage using a SQL-like language called HiveQL.
  • Sqoop, a tool for transferring data between SQL databases and the Hadoop Distributed File System.
  • Rmr, an extension of the R Statistical Language to support distributed processing of large datasets stored in the Hadoop Distributed File System.
  • Spark, a general processing engine compatible with Hadoop data
  • mrjob, allows MapReduce jobs in Python to run on Hadoop

The software versions are as follows:

Title Version
Hadoop 2.5.0
Hive 0.13.1
Sqoop 1.4.5
Pig 0.12.0
R/rhdfs/rmr 3.0.3
Spark 1.2.0
mrjob 0.4.3-dev, commit


If a cloud-based system is more suitable for your research, ARC-TS can support your use of Amazon cloud resources through MCloud, the UM-ITS cloud service.

For more information on the Hadoop cluster, please see this documentation or contact us at

A Flux account is required to access the Hadoop cluster. Visit the Establishing a Flux allocation page for more information.