[ https://issues.apache.org/jira/browse/HIVE-3652?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Owen O'Malley updated HIVE-3652: -------------------------------- Fix Version/s: (was: 0.11.0) > Join optimization for star schema > --------------------------------- > > Key: HIVE-3652 > URL: https://issues.apache.org/jira/browse/HIVE-3652 > Project: Hive > Issue Type: Improvement > Components: Query Processor > Reporter: Amareshwari Sriramadasu > Assignee: Vikram Dixit K > Attachments: HIVE-3652-tests.patch, HIVE-3652-tests.patch > > > Currently, if we join one fact table with multiple dimension tables, it > results in multiple mapreduce jobs for each join with dimension table, > because join would be on different keys for each dimension. > Usually all the dimension tables will be small and can fit into memory and so > map-side join can used to join with fact table. > In this issue I want to look at optimizing such query to generate single > mapreduce job sothat mapper loads dimension tables into memory and joins with > fact table on different keys as well. -- This message is automatically generated by JIRA. If you think it was sent incorrectly, please contact your JIRA administrators For more information on JIRA, see: http://www.atlassian.com/software/jira