Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/17617#discussion_r119275510
--- Diff: core/src/main/scala/org/apache/spark/deploy/SparkHadoopUtil.scala
---
@@ -143,14 +144,18 @@ class SparkHadoopUtil extends Logging {
* Returns a function that can be called to find Hadoop FileSystem bytes
read. If
* getFSBytesReadOnThreadCallback is called from thread r at time t, the
returned callback will
* return the bytes read on r since t.
- *
- * @return None if the required method can't be found.
*/
private[spark] def getFSBytesReadOnThreadCallback(): () => Long = {
- val threadStats =
FileSystem.getAllStatistics.asScala.map(_.getThreadStatistics)
- val f = () => threadStats.map(_.getBytesRead).sum
- val baselineBytesRead = f()
- () => f() - baselineBytesRead
+ val f = () =>
FileSystem.getAllStatistics.asScala.map(_.getThreadStatistics.getBytesRead).sum
+ val baseline = (Thread.currentThread().getId, f())
+ val bytesReadMap = new ConcurrentHashMap[Long, Long]()
+
+ () => {
--- End diff --
I think it's better to create an anonymous `Function0` instance and treat
`bytesReadMap` as a member variable and document the multi-thread semantic for
the `apply` method.
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