[
https://issues.apache.org/jira/browse/FLINK-31977?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Tan Kim updated FLINK-31977:
----------------------------
Description:
The code below is a function to detect inefficient scaleups.
It returns a result if the value of SCALING_EFFECTIVENESS_DETECTION_ENABLED
(scaling.effectiveness.detection.enabled) is true after all the necessary
computations for detection, but this is an unnecessary computation.
{code:java}
JobVertexScaler.java #175
private boolean detectIneffectiveScaleUp(
AbstractFlinkResource<?, ?> resource,
JobVertexID vertex,
Configuration conf,
Map<ScalingMetric, EvaluatedScalingMetric> evaluatedMetrics,
ScalingSummary lastSummary) {
double lastProcRate =
lastSummary.getMetrics().get(TRUE_PROCESSING_RATE).getAverage(); //
22569.315633422066
double lastExpectedProcRate =
lastSummary.getMetrics().get(EXPECTED_PROCESSING_RATE).getCurrent(); // 37340.0
var currentProcRate =
evaluatedMetrics.get(TRUE_PROCESSING_RATE).getAverage();
// To judge the effectiveness of the scale up operation we compute how much
of the expected
// increase actually happened. For example if we expect a 100 increase in
proc rate and only
// got an increase of 10 we only accomplished 10% of the desired increase.
If this number is
// below the threshold, we mark the scaling ineffective.
double expectedIncrease = lastExpectedProcRate - lastProcRate;
double actualIncrease = currentProcRate - lastProcRate;
boolean withinEffectiveThreshold =
(actualIncrease / expectedIncrease)
>=
conf.get(AutoScalerOptions.SCALING_EFFECTIVENESS_THRESHOLD);
if (withinEffectiveThreshold) {
return false;
}
var message = String.format(INNEFFECTIVE_MESSAGE_FORMAT, vertex);
eventRecorder.triggerEvent(
resource,
EventRecorder.Type.Normal,
EventRecorder.Reason.IneffectiveScaling,
EventRecorder.Component.Operator,
message);
if (conf.get(AutoScalerOptions.SCALING_EFFECTIVENESS_DETECTION_ENABLED)) {
LOG.info(message);
return true;
} else {
return false;
}
} {code}
It's better to check SCALING_EFFECTIVENESS_DETECTION_ENABLED beforehand and
then call the function, as shown in the if statement in the code below, which
is the caller of this function.
{code:java}
JobVertexScaler.java #150
if (currentParallelism == lastSummary.getNewParallelism() &&
lastSummary.isScaledUp()) {
if (scaledUp) {
if(conf.get(AutoScalerOptions.SCALING_EFFECTIVENESS_DETECTION_ENABLED))
{
return detectIneffectiveScaleUp(resource, vertex, conf,
evaluatedMetrics, lastSummary);
} else {
return true;
}
} else {
return detectImmediateScaleDownAfterScaleUp(vertex, conf,
lastScalingTs);
}
}{code}
was:
The code below is a function to detect inefficient scaleups.
It returns a result if the value of SCALING_EFFECTIVENESS_DETECTION_ENABLED
(scaling.effectiveness.detection.enabled) is true after all the necessary
computations for detection, but this is an unnecessary computation.
{code:java}
JobVertexScaler.java #175
private boolean detectIneffectiveScaleUp(
AbstractFlinkResource<?, ?> resource,
JobVertexID vertex,
Configuration conf,
Map<ScalingMetric, EvaluatedScalingMetric> evaluatedMetrics,
ScalingSummary lastSummary) {
double lastProcRate =
lastSummary.getMetrics().get(TRUE_PROCESSING_RATE).getAverage(); //
22569.315633422066
double lastExpectedProcRate =
lastSummary.getMetrics().get(EXPECTED_PROCESSING_RATE).getCurrent(); // 37340.0
var currentProcRate =
evaluatedMetrics.get(TRUE_PROCESSING_RATE).getAverage();
// To judge the effectiveness of the scale up operation we compute how much
of the expected
// increase actually happened. For example if we expect a 100 increase in
proc rate and only
// got an increase of 10 we only accomplished 10% of the desired increase.
If this number is
// below the threshold, we mark the scaling ineffective.
double expectedIncrease = lastExpectedProcRate - lastProcRate;
double actualIncrease = currentProcRate - lastProcRate;
boolean withinEffectiveThreshold =
(actualIncrease / expectedIncrease)
>=
conf.get(AutoScalerOptions.SCALING_EFFECTIVENESS_THRESHOLD);
if (withinEffectiveThreshold) {
return false;
}
var message = String.format(INNEFFECTIVE_MESSAGE_FORMAT, vertex);
eventRecorder.triggerEvent(
resource,
EventRecorder.Type.Normal,
EventRecorder.Reason.IneffectiveScaling,
EventRecorder.Component.Operator,
message);
if (conf.get(AutoScalerOptions.SCALING_EFFECTIVENESS_DETECTION_ENABLED)) {
LOG.info(message);
return true;
} else {
return false;
}
} {code}
It's better to check SCALING_EFFECTIVENESS_DETECTION_ENABLED beforehand and
then call the function, as shown in the if statement in the code below, which
is the caller of this function.
{code:java}
JobVertexScaler.java #150
if (currentParallelism == lastSummary.getNewParallelism() &&
lastSummary.isScaledUp()) {
if (scaledUp) {
if(conf.get(AutoScalerOptions.SCALING_EFFECTIVENESS_DETECTION_ENABLED))
{
detectIneffectiveScaleUp(resource, vertex, conf, evaluatedMetrics,
lastSummary);
} else {
return true;
}
} else {
return detectImmediateScaleDownAfterScaleUp(vertex, conf,
lastScalingTs);
}
}{code}
> If scaling.effectiveness.detection.enabled is false, the call to the
> detectIneffectiveScaleUp() function is unnecessary
> -----------------------------------------------------------------------------------------------------------------------
>
> Key: FLINK-31977
> URL: https://issues.apache.org/jira/browse/FLINK-31977
> Project: Flink
> Issue Type: Improvement
> Components: Autoscaler
> Affects Versions: 1.17.0
> Reporter: Tan Kim
> Priority: Minor
>
> The code below is a function to detect inefficient scaleups.
> It returns a result if the value of SCALING_EFFECTIVENESS_DETECTION_ENABLED
> (scaling.effectiveness.detection.enabled) is true after all the necessary
> computations for detection, but this is an unnecessary computation.
> {code:java}
> JobVertexScaler.java #175
> private boolean detectIneffectiveScaleUp(
> AbstractFlinkResource<?, ?> resource,
> JobVertexID vertex,
> Configuration conf,
> Map<ScalingMetric, EvaluatedScalingMetric> evaluatedMetrics,
> ScalingSummary lastSummary) {
> double lastProcRate =
> lastSummary.getMetrics().get(TRUE_PROCESSING_RATE).getAverage(); //
> 22569.315633422066
> double lastExpectedProcRate =
>
> lastSummary.getMetrics().get(EXPECTED_PROCESSING_RATE).getCurrent(); //
> 37340.0
> var currentProcRate =
> evaluatedMetrics.get(TRUE_PROCESSING_RATE).getAverage();
> // To judge the effectiveness of the scale up operation we compute how
> much of the expected
> // increase actually happened. For example if we expect a 100 increase in
> proc rate and only
> // got an increase of 10 we only accomplished 10% of the desired
> increase. If this number is
> // below the threshold, we mark the scaling ineffective.
> double expectedIncrease = lastExpectedProcRate - lastProcRate;
> double actualIncrease = currentProcRate - lastProcRate;
> boolean withinEffectiveThreshold =
> (actualIncrease / expectedIncrease)
> >=
> conf.get(AutoScalerOptions.SCALING_EFFECTIVENESS_THRESHOLD);
> if (withinEffectiveThreshold) {
> return false;
> }
> var message = String.format(INNEFFECTIVE_MESSAGE_FORMAT, vertex);
> eventRecorder.triggerEvent(
> resource,
> EventRecorder.Type.Normal,
> EventRecorder.Reason.IneffectiveScaling,
> EventRecorder.Component.Operator,
> message);
> if (conf.get(AutoScalerOptions.SCALING_EFFECTIVENESS_DETECTION_ENABLED)) {
> LOG.info(message);
> return true;
> } else {
> return false;
> }
> } {code}
> It's better to check SCALING_EFFECTIVENESS_DETECTION_ENABLED beforehand and
> then call the function, as shown in the if statement in the code below, which
> is the caller of this function.
> {code:java}
> JobVertexScaler.java #150
> if (currentParallelism == lastSummary.getNewParallelism() &&
> lastSummary.isScaledUp()) {
> if (scaledUp) {
>
> if(conf.get(AutoScalerOptions.SCALING_EFFECTIVENESS_DETECTION_ENABLED)) {
> return detectIneffectiveScaleUp(resource, vertex, conf,
> evaluatedMetrics, lastSummary);
> } else {
> return true;
> }
> } else {
> return detectImmediateScaleDownAfterScaleUp(vertex, conf,
> lastScalingTs);
> }
> }{code}
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