[ https://issues.apache.org/jira/browse/HIVE-15272?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15753212#comment-15753212
]
Rui Li commented on HIVE-15272:
-------------------------------
OK I'll look into this.
[~VPareek], I think the two tables have same DDL right? Do they contain same data? Could you
upload some sample data that can reproduce the issue? Thanks!
> "LEFT OUTER JOIN" Is not populating correct records with Hive On Spark
> ----------------------------------------------------------------------
>
> Key: HIVE-15272
> URL: https://issues.apache.org/jira/browse/HIVE-15272
> Project: Hive
> Issue Type: Bug
> Components: Hive, Spark
> Affects Versions: 1.1.0
> Environment: Hive 1.1.0, CentOS, Cloudera 5.7.4
> Reporter: Vikash Pareek
>
> I ran following Hive query multiple times with execution engine as Hive on Spark and
Hive on MapReduce.
> {code}
> SELECT COUNT(DISTINCT t1.region, t1.amount)
> FROM my_db.my_table1 t1
> LEFT OUTER
> JOIN my_db.my_table2 t2 ON (t1.id = t2.id
> AND t1.name = t2.name)
> {code}
> With Hive on Spark: Result (count) were different of every execution.
> With Hive on MapReduce: Result (count) were same of every execution.
> Seems like Hive on Spark behaving differently in each execution and does not populating
correct result.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
|