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https://issues.apache.org/jira/browse/SPARK-9377?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Jem Tucker updated SPARK-9377:
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Comment: was deleted
(was: Yes I will do)
> Shuffle tuning should discuss task size optimisation
> ----------------------------------------------------
>
> Key: SPARK-9377
> URL: https://issues.apache.org/jira/browse/SPARK-9377
> Project: Spark
> Issue Type: Documentation
> Components: Documentation, Shuffle
> Reporter: Jem Tucker
> Priority: Minor
>
> Recent issue SPARK-9310 highlighted the negative effects of having too high
> parallelism caused by task overhead. Although large task numbers is
> unavoidable with high volumes of data, more in detail in the documentation
> will be very beneficial to newcomers when optimising the performance of their
> applications.
> Areas to discuss could be:
> - What are the overheads of a Spark task?
> -- Does this overhead chance with task size etc?
> - How to dynamically calculate a suitable parallelism for a Spark job
> - Examples of designing code to minimise shuffles
> -- How to minimise the data volumes when shuffles are required
> - Differences between sort-based and hash-based shuffles
> -- Benefits and weaknesses of each
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