MapR brings Hadoop support to Ubuntu
MapR has also made its source code available on GitHub
By Sophie Curtis | Techworld | Published: 13:10, 02 April 2013
Hadoop distributor MapR Technologies has announced a new partnership with Canonical to package the MapR M3 Edition for Apache Hadoop with Ubuntu.
The free MapR M3 Edition includes HBase, Pig, Hive, Mahout, Cascading, Sqoop, Flume and other Hadoop-related components for unlimited production use. MapR M3 will be bundled with Ubuntu 12.04 LTS and 12.10 via the Ubuntu Partner Archive from 25 April.
“Ubuntu and MapR are a great combination for implementing an open source Hadoop cluster in any enterprise,” said Tomer Shiran, director of product management, MapR.
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“For OpenStack customers, this packaged offering of Ubuntu with MapR is a fast and simple means to enable Hadoop as a service in their environments.”
Canonical and MapR are also working to develop a Juju Charm that can be used by OpenStack and other customers to easily deploy MapR into into both private and public clouds.
Juju is Canonical’s package management system for implementing cloud technologies, and “Charms” are pre-configured deployment tools for specific products.
“With the launch of Ubuntu 12.04 LTS and the introduction of Juju, Canonical further established its lead in delivering easy access to the latest open cloud technology, including OpenStack,” said Kyle MacDonald, VP Cloud at Canonical.
“Our customers want optimised workloads to run in their cloud and now, with the addition of MapR M3 as an easily deployable and enterprise-grade Hadoop solution, we are providing Ubuntu customers with an effective way to implement Big Data into their operations.”
MapR has also announced that the source code for the component packages of the MapR Distribution for Apache Hadoop is now publicly available on GitHub, making it easy to access and modify components.
In addition, MapR is releasing binaries, source code and documentation in a public Maven repository making it easier for developers to develop, build and deploy their Hadoop-based applications.