Hive 1.2.1-1608 Release Notes
Below are release notes for the Hive component included in the MapR Converged Data Platform. You may also be interested in the Apache Hive 1.2.1 changelog or the Apache Hive homepage.
Hive Version | 1.2.1 |
Release Date | September 1, 2016 |
MapR Version Interoperability | See Hive and HCatalog Support Matrix and Ecosystem Support Matrix (Pre-5.2 releases) |
Source on GitHub | https://github.com/mapr/hive/tree/1.2.0-mapr-1608 |
Maven Artifacts | https://repository.mapr.com/maven/ |
Package Names | The following packages are associated with this release:
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Feature Support
MapR does not support Hive on Spark. Therefore, you cannot use Spark as an execution engine for Hive. However, you can run Hive and Spark on the same cluster. You can also use Spark SQL and Drill to query Hive tables.
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.
Commit | Date (YYYY-MM-DD) | Comment |
---|---|---|
1fbbaa04 | 2016-08-16 | HIVE-13120: The issue causing the ORC split generation in HiveServer2 to return permission errors is now fixed. |
ee26f8a0 | 2016-08-15 | MAPR-24242: The incorrect timestamp format in the partition name when table was partitioned by timestamp and LOAD DATA was used is now fixed. |
04034276 | 2016-08-12 | MAPR-24248: The isNonLocalScratchDirUsed in
getLocalScratchDir() method is now set to
false to allow operations with scratch directories to use
the local filesystem instead of the MapR filesystem. |
cabc37a4f | 2016-08-10 | HIVE-11617: The issue causing explain job to (sometimes) not finish or be very slow when there are many lateral views is now fixed. |
82de9cc3 | 2016-08-01 | MAPR-24105: The issue causing Spark engine for Hive to fail with an execution error is now fixed. |
5115eef0 | 2016-05-04 | HIVE-13677: When folding CASE expressions, Hive no longer throws exception during Serialization. |
79dc6054 | 2015-09-14 | HIVE-11817: A query with OVER statement will no longer fail when table contains null values. |