mridulm commented on a change in pull request #34092:
URL: https://github.com/apache/spark/pull/34092#discussion_r715332397
##########
File path: core/src/main/scala/org/apache/spark/status/AppStatusListener.scala
##########
@@ -1253,44 +1254,46 @@ private[spark] class AppStatusListener(
toDelete.foreach { j => kvstore.delete(j.getClass(), j.info.jobId) }
}
+ private case class StageCompletionTime(
+ stageId: Int,
+ attemptId: Int,
+ completionTime: Long)
+
private def cleanupStages(count: Long): Unit = {
val countToDelete = calculateNumberToRemove(count,
conf.get(MAX_RETAINED_STAGES))
if (countToDelete <= 0L) {
return
}
+ val stageArray = new ArrayBuffer[StageCompletionTime]()
+ val stageDataCount = new mutable.HashMap[Int, Int]()
+ kvstore.view(classOf[StageDataWrapper]).forEach { s =>
+ // Here we keep track of the total number of StageDataWrapper entries
for each stage id.
+ // This will be used in cleaning up the RDDOperationGraphWrapper data.
+ if (stageDataCount.contains(s.info.stageId)) {
+ stageDataCount(s.info.stageId) += 1
+ } else {
+ stageDataCount(s.info.stageId) = 1
+ }
+ if (s.info.status != v1.StageStatus.ACTIVE && s.info.status !=
v1.StageStatus.PENDING) {
+ val candidate =
+ StageCompletionTime(s.info.stageId, s.info.attemptId,
s.completionTime)
+ stageArray.append(candidate)
+ }
+ }
+
// As the completion time of a skipped stage is always -1, we will remove
skipped stages first.
// This is safe since the job itself contains enough information to render
skipped stages in the
// UI.
- val view = kvstore.view(classOf[StageDataWrapper]).index("completionTime")
- val stages = KVUtils.viewToSeq(view, countToDelete.toInt) { s =>
- s.info.status != v1.StageStatus.ACTIVE && s.info.status !=
v1.StageStatus.PENDING
- }
-
- val stageIds = stages.map { s =>
Review comment:
I am trying to understand the last part - what is the difference w.r.t
new code for finding stage id ?
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