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https://issues.apache.org/jira/browse/HIVE-15272?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15693243#comment-15693243
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Vikash Pareek edited comment on HIVE-15272 at 11/24/16 3:10 PM:
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I am just calculating count of the records, result (count) does not dependent
on ordering.
Result should be same for each execution as in case of MR.
my_table1 (left) is having ~30 million records
my_table2 (right) is having ~85 million records
was (Author: vpareek):
I am just calculating count of the records, result (count) does not dependent
on ordering.
Result should be same for each execution as in case of MR.
I have around 30 million data in my_table1 (left) and 85 million data in
my_table2 (right).
> "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.
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