ryan-johnson-databricks commented on code in PR #37531:
URL: https://github.com/apache/spark/pull/37531#discussion_r947422496
##########
core/src/main/scala/org/apache/spark/scheduler/Task.scala:
##########
@@ -136,44 +136,27 @@ private[spark] abstract class Task[T](
plugins.foreach(_.onTaskStart())
try {
- runTask(context)
- } catch {
- case e: Throwable =>
- // Catch all errors; run task failure callbacks, and rethrow the
exception.
- try {
- context.markTaskFailed(e)
- } catch {
- case t: Throwable =>
- e.addSuppressed(t)
- }
- context.markTaskCompleted(Some(e))
- throw e
+ context.runTaskWithListeners(this)
} finally {
try {
- // Call the task completion callbacks. If "markTaskCompleted" is
called twice, the second
- // one is no-op.
- context.markTaskCompleted(None)
- } finally {
- try {
- Utils.tryLogNonFatalError {
- // Release memory used by this thread for unrolling blocks
-
SparkEnv.get.blockManager.memoryStore.releaseUnrollMemoryForThisTask(MemoryMode.ON_HEAP)
-
SparkEnv.get.blockManager.memoryStore.releaseUnrollMemoryForThisTask(
- MemoryMode.OFF_HEAP)
- // Notify any tasks waiting for execution memory to be freed to
wake up and try to
- // acquire memory again. This makes impossible the scenario where
a task sleeps forever
- // because there are no other tasks left to notify it. Since this
is safe to do but may
- // not be strictly necessary, we should revisit whether we can
remove this in the
- // future.
- val memoryManager = SparkEnv.get.memoryManager
- memoryManager.synchronized { memoryManager.notifyAll() }
- }
- } finally {
- // Though we unset the ThreadLocal here, the context member variable
itself is still
- // queried directly in the TaskRunner to check for
FetchFailedExceptions.
- TaskContext.unset()
- InputFileBlockHolder.unset()
+ Utils.tryLogNonFatalError {
Review Comment:
Indentation-only change, best viewed with whitespace ignored:
https://github.com/apache/spark/pull/37531/files?diff=split&w=1
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