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https://issues.apache.org/jira/browse/HIVE-7956?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14120807#comment-14120807
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Rui Li commented on HIVE-7956:
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Yes [~brocknoland], with {{set hive.enforce.bucketing = true;}}, spark also
launches a proper number of reducers (according to # of buckets). But all
mappers write shuffle data for just one reducer so all other buckets are empty.
Therefore I think there's something wrong with the partitioning. I can try
cloning the extra hashcode in {{HiveKey}}.
> When inserting into a bucketed table, all data goes to a single bucket [Spark
> Branch]
> -------------------------------------------------------------------------------------
>
> Key: HIVE-7956
> URL: https://issues.apache.org/jira/browse/HIVE-7956
> Project: Hive
> Issue Type: Bug
> Components: Spark
> Reporter: Rui Li
>
> I created a bucketed table:
> {code}
> create table testBucket(x int,y string) clustered by(x) into 10 buckets;
> {code}
> Then I run a query like:
> {code}
> set hive.enforce.bucketing = true;
> insert overwrite table testBucket select intCol,stringCol from src;
> {code}
> Here {{src}} is a simple textfile-based table containing 40000000 records
> (not bucketed). The query launches 10 reduce tasks but all the data goes to
> only one of them.
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