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MapR Releases New Ecosystem Pack with Optimized Security for Apache Spark

By   /  April 11, 2017  /  No Comments

by Angela Guess

A new press release reports, “MapR Technologies, Inc., the provider of the Converged Data Platform that converges the essential data management and application processing technologies on a single, horizontally scalable platform, today announced its next major release of the MapR Ecosystem Pack (MEP) program. MEP is a broad set of open source ecosystem projects that enable big data applications running on the MapR Converged Data Platform with inter-project compatibility. Version 3.0 of MEP provides enhanced security for Spark, new Spark connectors for MapR-DB and HBase, significant updates and integrations with Drill, and a faster version of Hive. ‘The adoption of Spark and Drill continues to advance at a fast pace with enterprises worldwide,’ said Will Ochandarena, senior director, product management, MapR Technologies. ‘With a regular cadence of ecosystem updates that make it easier to adopt for production use, our customers immediately benefit from rapid open source innovation with the reliability, scale and performance of the Converged Data Platform’.”

The release continues, “The MapR Ecosystem Pack removes the complexity of coordinating many different community projects and versions. MapR develops, tests, and integrates open source ecosystem projects such as Apache Drill, Spark, Hive, and Myriad, among others. The new MapR Ecosystem Pack version 3.0 includes: (1) Apache Spark 2.1.0. The Spark 2.1 release focuses on improvements in enterprise-ready stability and security including: Scalable partition handling; Data Type APIs graduate to ‘stable’; More than 1200 fixes on the Spark 2.X line; Provides for secure connections using MapR-SASL in addition to Kerberos for inbound client connections to the Spark Thrift server and Spark connections to Hive Metastore; Support for impersonation on SELECT statements. (2) Native Spark Connector for MapR-DB JSON. The Native Spark Connector for MapR-DB JSON makes it easier to build real-time or batch pipelines between data and MapR-DB while leveraging Spark or Spark Streaming within the pipeline.”

Read more at Marketwired.

Photo credit: MapR

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