steveloughran commented on a change in pull request #29959:
URL: https://github.com/apache/spark/pull/29959#discussion_r503347661
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File path: core/src/main/scala/org/apache/spark/util/HadoopFSUtils.scala
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@@ -207,18 +166,14 @@ 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)
Review comment:
HDFS and S3A both do this; ABFS merits minor optimisation too. Because
they return a remote iterator they can do paged fetch of data
* HDFS/webHDFS: paged download for better scalability
* S3A (3.3.1+): async prefetch of next page of data
ABFS should copy the S3A approach; it's listing API is paged too.
Better to rely on the FS to do the work *but make clear you expect the
maintainers to do so*
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