Github user patrickbrownsync commented on a diff in the pull request: https://github.com/apache/spark/pull/22883#discussion_r229539016 --- Diff: core/src/main/scala/org/apache/spark/status/AppStatusListener.scala --- @@ -1105,6 +1095,15 @@ private[spark] class AppStatusListener( cleanupCachedQuantiles(key) } + + // Delete tasks for all stages in one pass, as deleting them for each stage individually is slow --- End diff -- Sure Take a look at the implementation of InMemoryView at spark/common/kvstore/src/main/java/org/apache/spark/util/kvstore/InMemoryStore.java line 179 specifically the implementation of iterator on line 193, here is an excerpt: ``` Collections.sort(sorted, (e1, e2) -> modifier * compare(e1, e2, getter)); Stream<T> stream = sorted.stream(); if (first != null) { stream = stream.filter(e -> modifier * compare(e, getter, first) >= 0); } if (last != null) { stream = stream.filter(e -> modifier * compare(e, getter, last) <= 0); } ``` and the original, in loop deletion code: ``` val tasks = kvstore.view(classOf[TaskDataWrapper]) .index("stage") .first(key) .last(key) .asScala tasks.foreach { t => kvstore.delete(t.getClass(), t.taskId) } ``` So you can see, if we do this each loop we actually sort the whole collection of TaskDataWrapper which are currently in the store, then go through and check each item based on the key set (the stage). Assuming we have a large number of stages and tasks this is an O(n^2) operation, which is what happens on my production application and the repro code. If we do this in one pass for all stages, we only sort and iterate the list of tasks one time. This same pattern happens fairly frequently using the KVStoreView interface and InMemoryView implementation. Since I am new to contributing to Spark I did not undertake a massive refactor, but I would suggest that this interface and implementation should be looked at and re-designed with efficiency in mind. The current implementation favors flexibility in terms of how the dataset is sorted and filtered, but enforcing a single sort order via something like a SortedSet would hopefully make it clear when the operation being performed was efficiently searching inside the collection, and when you were using an inefficient access pattern. I hope that explains the reasoning, if you have any more questions let me know.
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