[ https://issues.apache.org/jira/browse/HIVE-19480?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16469539#comment-16469539 ]
Gopal V commented on HIVE-19480: -------------------------------- >From the HiveConf in Hive2 and 3. {code} While MR remains the default engine for historical reasons, it is itself a historical engine and is deprecated in Hive 2 line. It may be removed without further warning. {code} > Implement and Incorporate MAPREDUCE-207 > --------------------------------------- > > Key: HIVE-19480 > URL: https://issues.apache.org/jira/browse/HIVE-19480 > Project: Hive > Issue Type: New Feature > Components: HiveServer2 > Affects Versions: 1.2.3 > Reporter: BELUGA BEHR > Priority: Major > > * HiveServer2 has the ability to run many MapReduce jobs in parallel. > * Each MapReduce application calculates the job's file splits at the client > level > * = HiveServer2 loading many file splits at the same time, putting pressure > on memory > {quote}"The client running the job calculates the splits for the job by > calling getSplits(), then sends them to the application master, which uses > their storage locations to schedule map tasks that will process them on the > cluster." > - "Hadoop: The Definitive Guide"{quote} > MAPREDUCE-207 should address this memory pressure by moving split > calculations into ApplicationMaster. Spark and Tez already take this approach. > Once MAPREDUCE-207 is completed, leverage the capability in HiveServer2. -- This message was sent by Atlassian JIRA (v7.6.3#76005)