MapR Updates Hadoop Distribution With Virtual Machine, New Client Support

MapR Technologies, Inc., an Apache Hadoop distribution, announced a new release that expands support for C/C++ API access and Windows and Mac clients, as well as being available as a virtual machine. MapR version 1.2 also includes the underpinnings to support MapReduce 2.0, which expands the types of applications that can take advantage of a Hadoop cluster.

Version 1.2 provides installation packages for Mac and Windows, in addition to Linux, enabling users of all major platforms to run Hadoop applications without having to install third-party libraries such as cygwin. This is a major expansion of the range of applications MapR now supports, Jack Norris, vice president of marketing, MapR Technologies, tells 5 Minute Briefing. "While Hadoop has always supported a variety of applications and use cases, version 1.2 expands the platforms and languages that can directly integrate with Hadoop. We can now tap the wealth of applications and libraries that exist in organizations today and help companies dramatically improve their ability to benefit from better analysis of big data."

An additional component, MapR Virtual Machine (VM), provides a VMware virtual machine that allows users to experiment with the MapR Distribution. This version makes it easy to experiment with MapR capabilities such as NFS and snapshots.

Version 1.2 also includes a greater ability to take advantage of next generation resource management framework, the vendor says. MapR users will be able to take advantage of MapReduce 2.0 once it is ready for production use. Although it is expected to take several months for the community to stabilize Hadoop 0.23, users will be able to take advantage of the combined benefits of MapReduce 2.0, such as backward-compatibility and scalability and MapR's unique capabilities, such as HA (no lost tasks or jobs during a JobTracker or ApplicationMaster failure) and the high-performance shuffle.

The new release adds a native access library. With Version 1.2, MapR provides a libhdfs implementation that bypasses Java altogether and provides high-performance access to the distributed file system from C/C++ applications and other compatible scripting languages. There is no need to recompile applications that use libhdfs, since the API (header file) is identical.

The latest MapR distribution download is available at