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https://issues.apache.org/jira/browse/SPARK-54923?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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ASF GitHub Bot updated SPARK-54923:
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Labels: pull-request-available (was: )
> org.apache.spark.util.HadoopFSUtils.parallelListLeafFilesInternal parallelism
> configuration not respected
> ---------------------------------------------------------------------------------------------------------
>
> Key: SPARK-54923
> URL: https://issues.apache.org/jira/browse/SPARK-54923
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 4.0.1
> Reporter: Romain Manni-Bucau
> Priority: Major
> Labels: pull-request-available
>
> Hi,
>
> assuming there is no paralleism threshold (or nothing preventing parallelism
> at least)
> and that a s3 bucket has 10k+ files
> but with a hierarchy which looks like root/subpath/\{year}/...
> then org.apache.spark.util.HadoopFSUtils.parallelListLeafFilesInternal will
> not parallelize because root has a single child (and once parallelize is
> called, workers don't get spark context and a threshold of int.max, two
> criterias preventing parallelism on workers).
> While this seems intentional it is a big perf killer preventing to use SQL
> and forcing to superseed the listing manually in the driver and explicitly
> pass paths.
> Any hope the design is rethought to add a config to force the driver to visit
> multiple level before calling parallelize(), in the previous case I could say
> visit 2 (3 actually since there is the month after) levels then delegate to
> the workers.
> If needed I would work on a patch.
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