maropu commented on a change in pull request #29498:
URL: https://github.com/apache/spark/pull/29498#discussion_r474340280
##########
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
+cases such as Spark SQL, you can tune
`spark.sql.sources.parallelPartitionDiscovery.threshold` to improve the listing
Review comment:
I think the last statement should be described in the SQL side:
https://github.com/apache/spark/blob/master/docs/sql-performance-tuning.md
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