viirya commented on a change in pull request #29498:
URL: https://github.com/apache/spark/pull/29498#discussion_r474330233
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File path: docs/tuning.md
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@@ -264,6 +264,13 @@ parent RDD's number of partitions. You can pass the level
of parallelism as a se
or set the config property `spark.default.parallelism` to change the default.
In general, we recommend 2-3 tasks per CPU core in your cluster.
+Sometimes you may also need to increase directory listing parallelism when job
input has large number of directories,
+otherwise the process could take a very long time, especially when against
object store like S3.
+If your job works on RDD with Hadoop input formats (e.g., via
`SparkContext#sequenceFile`), the parallelism is
+controlled via
`spark.hadoop.mapreduce.input.fileinputformat.list-status.num-threads` (default
is 1). For other
Review comment:
This seems having a limitation that multiple threads cannot be used with
non thread-safe path filter?
https://hadoop.apache.org/docs/r2.7.2/hadoop-mapreduce-client/hadoop-mapreduce-client-core/mapred-default.xml
> The number of threads to use to list and fetch block locations for the
specified input paths. Note: multiple threads should not be used if a custom
non thread-safe path filter is used.
Should we also mention it together?
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