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https://issues.apache.org/jira/browse/FLINK-3480?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Greg Hogan updated FLINK-3480:
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Comment: was deleted
(was: Today I bumped into the performance discrepancy where a forwarding ship
strategy can hurt performance since we can only do a sorted reduce whereas with
a partition hash we can use the new hash-combiner.
What would be the spilling strategy for a hash-reducer and would this look much
different from using the hash-combiner followed by the sort-reducer?)
> Add hash-based strategy for ReduceFunction
> ------------------------------------------
>
> Key: FLINK-3480
> URL: https://issues.apache.org/jira/browse/FLINK-3480
> Project: Flink
> Issue Type: Sub-task
> Components: Local Runtime
> Reporter: Fabian Hueske
>
> This issue is related to FLINK-3477.
> While FLINK-3477 proposes to add hash-based combine strategy for
> ReduceFunction, this issue aims to add a hash-based strategy for the final
> aggregation.
> This will need again a special hash-table aggregation which allows for
> in-place updates and append updates. However, it also needs to support
> spilling to disk in case of too tight memory budgets.
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