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https://issues.apache.org/jira/browse/HIVE-4963?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13735068#comment-13735068
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Ashutosh Chauhan commented on HIVE-4963:
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I would also suggest to take a look at how Join Operator handles this. It has a
same problem to solve and it solves nearly in same fashion (atleast
conceptually). Instead of building an alternative infra for spilling to disk
under memory load, it will be better to reuse those classes and mechanism, if
possible.
> Support in memory PTF partitions
> --------------------------------
>
> Key: HIVE-4963
> URL: https://issues.apache.org/jira/browse/HIVE-4963
> Project: Hive
> Issue Type: Bug
> Components: PTF-Windowing
> Reporter: Harish Butani
> Attachments: HIVE-4963.D11955.1.patch
>
>
> PTF partitions apply the defensive mode of assuming that partitions will not
> fit in memory. Because of this there is a significant deserialization
> overhead when accessing elements.
> Allow the user to specify that there is enough memory to hold partitions
> through a 'hive.ptf.partition.fits.in.mem' option.
> Savings depends on partition size and in case of windowing the number of
> UDAFs and the window ranges. For eg for the following (admittedly extreme)
> case the PTFOperator exec times went from 39 secs to 8 secs.
>
> {noformat}
> select t, s, i, b, f, d,
> min(t) over(partition by 1 rows between unbounded preceding and current row),
> min(s) over(partition by 1 rows between unbounded preceding and current row),
> min(i) over(partition by 1 rows between unbounded preceding and current row),
> min(b) over(partition by 1 rows between unbounded preceding and current row)
> from over10k
> {noformat}
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