Spark 1.5.2-1603 Release Notes
The notes below relate specifically to the MapR Converged Data Platform. You may also be
interested in the open source Spark 1.5.2 Release Notes.
Spark Version | 1.5.2 |
Release Date | April 4, 2016 |
MapR Version Interoperability | See the Ecosystem Support Matrix (Pre-5.2 releases) and Spark Support Matrix. |
Source on GitHub | https://github.com/mapr/spark/tree/1.5.2-mapr-1603 |
Package Names | The following packages are associated with this release:
|
New in This Release
This release of Apache Spark for MapR includes the
following new features or behavior changes:
For details on the features available in the open source version of this component,
see the Apache Spark documentation.- You can submit Spark jobs from a Windows client node.
- On a secure cluster that runs Spark on YARN, SSL encryption between SparkWorker and SparkMaster nodes is automatically enabled.
- On a secure cluster that runs Spark on YARN, authentication between SparkWorker and SparkMaster nodes is automatically enabled.
Fixes
This release by MapR includes the following fixes on the base Apache release. For complete details, refer to the commit log for this project in GitHub.
GitHub Commit | Date (YYYY-MM-DD) | Comment |
---|---|---|
03b314 | 2016-03-04 | MAPR-21699: When you run Spark on YARN on a secure cluster, encryption and authentication now are enabled by default. |
fbfaf1 | 2016-03-16 | MAPR-18865: spark-env.cmd script is now included in the
conf directory so that it can determine the hadoop classpath. |
d9a0e3 | 2016-03-16 | [MAPR-21699] When you run Spark on YARN on a secure cluster, SSL encryption is automatically enabled for Akka, broadcast, and MapR filesystem connections. |
Known Issues
- MAPR-17271: On secure clusters, the MapR Control System (MCS) does not display links for Spark-Master and Spark-HistoryServer.
- MAPR-19761: On a secure cluster, MapR does not support the Spark SQL Thrift JDBC server. When the cluster is secure, the Spark Thrift server will not start.
- Spark versions up to and including 2.3.0 have the following security vulnerability: CVE-2018-1334 Apache Spark local privilege escalation vulnerability