Github user srowen commented on a diff in the pull request:
https://github.com/apache/spark/pull/16157#discussion_r91445291
--- Diff: docs/programming-guide.md ---
@@ -347,7 +347,7 @@ Some notes on reading files with Spark:
Apart from text files, Spark's Scala API also supports several other data
formats:
-* `SparkContext.wholeTextFiles` lets you read a directory containing
multiple small text files, and returns each of them as (filename, content)
pairs. This is in contrast with `textFile`, which would return one record per
line in each file.
+* `SparkContext.wholeTextFiles` lets you read a directory containing
multiple small text files, and returns each of them as (filename, content)
pairs. This is in contrast with `textFile`, which would return one record per
line in each file. It takes an optional second argument for controlling the
minimal number of partitions (by default this is 2). It uses
[CombineFileInputFormat](https://hadoop.apache.org/docs/current/api/org/apache/hadoop/mapreduce/lib/input/CombineFileInputFormat.html)
internally in order to process large numbers of small files effectively by
grouping files on the same executor into a single partition. This can lead to
sub-optimal partitioning when the file sets would benefit from residing in
multiple partitions (e.g., larger partitions would not fit in memory, files are
replicated but a large subset is locally reachable from a single executor,
subsequent transformations would benefit from multi-core processing). In those
cases, set the `minPartitions` argume
nt to enforce splitting.
--- End diff --
Every element of the result is a file; it's fundamentally different from
`textFile`, and can't be that each file therefore ends up in a partition. I
don't think this merges files, right?
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