Github user WeichenXu123 commented on the issue:
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I need to make a survey for better Cartesian implementation, especially in
shuffle way. Close this PR for now and when the new solution is done I will
reopen it.
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Github user WeichenXu123 commented on the issue:
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@mridulm
Year, I know you are worried about the shuffling cost here. Currently when
`spark.shuffle.reduceLocality.enabled` is true(by default), each shuffling
reducer will be launched on th
Github user mridulm commented on the issue:
https://github.com/apache/spark/pull/16574
Couple of points :
a) Can recomputation be expensive ? Unfortunately, yes if not used
properly. For better or for worse, this has been the implementation in spark
since early days - pr
Github user WeichenXu123 commented on the issue:
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@mridulm En...so that still keep `NarrowDependency` seems better, but I
think the recomputation is a serious problem when parents RDD not persisted, I
think in this case we should try to print
Github user mridulm commented on the issue:
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This is a behavior change and will break expectations from existing code
depending on cartesian to not go through shuffle (particularly when data is
already persisted).
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Jenkins, test this please.
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