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https://issues.apache.org/jira/browse/SPARK-5614?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14307073#comment-14307073
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Apache Spark commented on SPARK-5614:
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User 'ianluyan' has created a pull request for this issue:
https://github.com/apache/spark/pull/4394
> Predicate pushdown through Generate
> -----------------------------------
>
> Key: SPARK-5614
> URL: https://issues.apache.org/jira/browse/SPARK-5614
> Project: Spark
> Issue Type: Improvement
> Components: SQL
> Affects Versions: 1.2.0
> Reporter: Lu Yan
>
> Now in Catalyst's rules, predicates can not be pushed through "Generate"
> nodes. Further more, partition pruning in HiveTableScan can not be applied on
> those queries involves "Generate". This makes such queries very inefficient.
> For example, physical plan for query
> {quote}
> select len, bk
> from s_server lateral view explode(len_arr) len_table as len
> where len > 5 and day = '20150102';
> {quote}
> where 'day' is a partition column in metastore is like this in current
> version of Spark SQL:
> {quote}
> Project [len, bk]
> Filter ((len > "5") && "(day = "20150102")")
> Generate explode(len_arr), true, false
> HiveTableScan [bk, len_arr, day], (MetastoreRelation default, s_server,
> None), None
> {quote}
> But theoretically the plan should be like this
> {quote}
> Project [len, bk]
> Filter (len > "5")
> Generate explode(len_arr), true, false
> HiveTableScan [bk, len_arr, day], (MetastoreRelation default, s_server,
> None), Some(day = "20150102")
> {quote}
> Where partition pruning predicates can be pushed to HiveTableScan nodes.
> I've developed a solution on this issue. If you guys do not have a plan for
> this already, I could merge the solution back to master.
> And there is also a problem on column pruning for "Generate", I would file
> another issue about that.
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