sunchao commented on a change in pull request #30019:
URL: https://github.com/apache/spark/pull/30019#discussion_r508729593
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File path: core/src/main/scala/org/apache/spark/util/HadoopFSUtils.scala
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@@ -207,18 +207,14 @@ private[spark] object HadoopFSUtils extends Logging {
// Note that statuses only include FileStatus for the files and dirs
directly under path,
// and does not include anything else recursively.
val statuses: Array[FileStatus] = try {
- fs match {
- // DistributedFileSystem overrides listLocatedStatus to make 1 single
call to namenode
- // to retrieve the file status with the file block location. The
reason to still fallback
- // to listStatus is because the default implementation would
potentially throw a
- // FileNotFoundException which is better handled by doing the lookups
manually below.
- case (_: DistributedFileSystem | _: ViewFileSystem) if !ignoreLocality
=>
- val remoteIter = fs.listLocatedStatus(path)
- new Iterator[LocatedFileStatus]() {
- def next(): LocatedFileStatus = remoteIter.next
- def hasNext(): Boolean = remoteIter.hasNext
- }.toArray
- case _ => fs.listStatus(path)
+ if (ignoreLocality) {
+ fs.listStatus(path)
+ } else {
+ val remoteIter = fs.listLocatedStatus(path)
+ new Iterator[LocatedFileStatus]() {
+ def next(): LocatedFileStatus = remoteIter.next
+ def hasNext(): Boolean = remoteIter.hasNext
+ }.toArray
Review comment:
Yes it would be lovely if we can get async listing here, but I think it
requires a much bigger surgery - up to the top level currently Spark's RDD
model requires all the input partitions to be ready before it can start
processing (deeply embedded in its primitives such as map/reduce).
We can perhaps add the async logic here in this class but I think "local"
processing we're doing here is far cheaper than the remote listing and perhaps
can't gain much from the change.
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