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https://issues.apache.org/jira/browse/SPARK-677?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Josh Rosen resolved SPARK-677.
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Resolution: Fixed
Fix Version/s: 1.2.2
1.3.1
1.4.0
Target Version/s: 1.3.1, 1.2.2, 1.4.0 (was: 1.2.2, 1.3.1, 1.4.0)
This was fixed for 1.3.1, 1.2.2, and 1.4.0. I don't think that we'l do a 1.1.x
backport, so I'm going to mark this as resolved.
> PySpark should not collect results through local filesystem
> -----------------------------------------------------------
>
> Key: SPARK-677
> URL: https://issues.apache.org/jira/browse/SPARK-677
> Project: Spark
> Issue Type: Improvement
> Components: PySpark
> Affects Versions: 1.0.2, 1.1.1, 1.2.1, 1.3.0, 1.4.0
> Reporter: Josh Rosen
> Assignee: Davies Liu
> Fix For: 1.4.0, 1.3.1, 1.2.2
>
>
> Py4J is slow when transferring large arrays, so PySpark currently dumps data
> to the disk and reads it back in order to collect() RDDs. On large enough
> datasets, this data will spill from the buffer cache and write to the
> physical disk, resulting in terrible performance.
> Instead, we should stream the data from Java to Python over a local socket or
> a FIFO.
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