Github user jerryshao commented on a diff in the pull request:
https://github.com/apache/spark/pull/17480#discussion_r110804952
--- Diff:
core/src/main/scala/org/apache/spark/ExecutorAllocationManager.scala ---
@@ -249,7 +249,14 @@ private[spark] class ExecutorAllocationManager(
* yarn-client mode when AM re-registers after a failure.
*/
def reset(): Unit = synchronized {
- initializing = true
+ /**
+ * When some tasks need to be scheduled and initial executor = 0,
resetting the initializing
+ * field may cause it to not be set to false in yarn.
+ * SPARK-20079: https://issues.apache.org/jira/browse/SPARK-20079
+ */
+ if (maxNumExecutorsNeeded() == 0) {
+ initializing = true
--- End diff --
I think the purpose of "initializing" is to avoid unnecessary executors
ramp down before the stage submitted or executor timeout. For example if min
executor number is 0, initial number is 10. If "initializing" is set to false,
executor number will ramp down to 0 immediately, and during this time if stage
is submitted, then still requires unnecessary executor ramp up to meet this
stage's requirement.
In the AM restart scenario, if we set "initializing" to false in `reset`,
then we will may also meet the situation mentioned above, I think that's
possible.
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