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https://issues.apache.org/jira/browse/FLINK-2237?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15154224#comment-15154224
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ASF GitHub Bot commented on FLINK-2237:
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Github user fhueske commented on the pull request:
https://github.com/apache/flink/pull/1517#issuecomment-186219363
OK, then lets keep the data in one partition for now. In case of var-length
updates, this can default to a memory usage / combine behavior which is
somewhat similar to the sort-based strategy: Filling the memory with records
and emitting it (putting compaction aside).
I'll review the PR once more will run a few end-to-end benchmarks as well.
What kind of benchmarks have you done so far?
- Did you check the combine rate (input / output ratio) compared to the
sort-based strategy?
- How much memory did you use for tests (upper bound)? Did you vary the
memory?
- Have you checked heap memory consumption / GC activity compared to the
sort-based strategy?
It might take a few more days before I actually get to this, but it is on
my list.
Thanks,
Fabian
> Add hash-based Aggregation
> --------------------------
>
> Key: FLINK-2237
> URL: https://issues.apache.org/jira/browse/FLINK-2237
> Project: Flink
> Issue Type: New Feature
> Reporter: Rafiullah Momand
> Assignee: Gabor Gevay
> Priority: Minor
>
> Aggregation functions at the moment are implemented in a sort-based way.
> How can we implement hash based Aggregation for Flink?
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