afedulov commented on code in PR #711:
URL:
https://github.com/apache/flink-kubernetes-operator/pull/711#discussion_r1399055639
##########
flink-autoscaler/src/main/java/org/apache/flink/autoscaler/JobAutoScalerImpl.java:
##########
@@ -159,19 +161,24 @@ private void runScalingLogic(Context ctx,
AutoscalerFlinkMetrics autoscalerMetri
throws Exception {
var collectedMetrics = metricsCollector.updateMetrics(ctx, stateStore);
+ var jobTopology = collectedMetrics.getJobTopology();
if (collectedMetrics.getMetricHistory().isEmpty()) {
return;
}
LOG.debug("Collected metrics: {}", collectedMetrics);
- var evaluatedMetrics = evaluator.evaluate(ctx.getConfiguration(),
collectedMetrics);
+ var now = clock.instant();
+ // Scaling tracking data contains previous restart times that are
taken into account
+ var scalingTracking = getTrimmedScalingTracking(stateStore, ctx, now);
+ var evaluatedMetrics =
+ evaluator.evaluate(ctx.getConfiguration(), collectedMetrics,
scalingTracking);
Review Comment:
I don't think this works with the current metrics scoping since it would
lead to duplicating the restart time per vertex and we are striving to
minimizing the size of the config map. Also, instead of just checking one
tracking entry, should we instead iterate over all records of this metric
across all vertices and take the maximum over that? Or just trust one
observation? If we'll just use one observation, why would we need this data in
every vertex if we know it is supposed to be the same for all vertices, why
store it at the vertex level?
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