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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