1996fanrui commented on code in PR #22985:
URL: https://github.com/apache/flink/pull/22985#discussion_r1321654007
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flink-runtime/src/main/java/org/apache/flink/runtime/scheduler/adaptive/Executing.java:
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@@ -124,17 +154,33 @@ private void handleDeploymentFailure(ExecutionVertex
executionVertex, JobExcepti
@Override
public void onNewResourcesAvailable() {
- maybeRescale();
+ rescaleWhenCooldownPeriodIsOver();
}
@Override
public void onNewResourceRequirements() {
- maybeRescale();
+ rescaleWhenCooldownPeriodIsOver();
}
private void maybeRescale() {
- if (context.shouldRescale(getExecutionGraph())) {
- getLogger().info("Can change the parallelism of job. Restarting
job.");
+ final Duration timeSinceLastRescale = timeSinceLastRescale();
+ rescaleScheduled = false;
+ final boolean shouldForceRescale =
+ (scalingIntervalMax != null)
+ && (timeSinceLastRescale.compareTo(scalingIntervalMax)
> 0)
+ && (lastRescale != Instant.EPOCH); // initial rescale
is not forced
+ if (shouldForceRescale || context.shouldRescale(getExecutionGraph())) {
+ if (shouldForceRescale) {
+ getLogger()
+ .info(
+ "Time since last rescale ({}) > {} ({}).
Force-changing the parallelism of the job. Restarting the job.",
+ timeSinceLastRescale,
+
JobManagerOptions.SCHEDULER_SCALING_INTERVAL_MAX.key(),
+ scalingIntervalMax);
+ } else {
+ getLogger().info("Can change the parallelism of the job.
Restarting the job.");
+ }
+ lastRescale = Instant.now();
context.goToRestarting(
getExecutionGraph(),
Review Comment:
>> Do you mean we force trigger a rescale when new resources comes and the
current time > lastRescaleTime + scalingIntervalMax?
>
> yes, that is what is what the community agreed on in the FLIP.
I think this strategy just solve one case: the last resource comes after
scalingIntervalMax. The job can rescale directly.
However, it cannot solve the case: the last resource comes before
scalingIntervalMax. Assuming the scalingIntervalMax is 5 miuntes, the
`jobmanager.adaptive-scheduler.min-parallelism-increase` is 2, and the expected
paralleslim is 100.
- The job has 99 TMs at 09:00:00, it run with parallelism 99.
- At 09:03:00, the last TM comes.
- The `Executing` will ignore the rescale due to the parallelism diff is 1,
it less than `min-parallelism-increase` and `current time < lastRescaleTime +
scalingIntervalMax`.
And then the job doesn't need the new resource and the expected parallelism
isn't change, so the job won't rescale anymore.
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