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https://issues.apache.org/jira/browse/FLINK-18808?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17177475#comment-17177475
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ming li commented on FLINK-18808:
---------------------------------
Hi, [~pnowojski]. Sorry, I'm still a little confused. In fact, in
{{BroadcastingOutputCollector}} it will call the {{Output#collect}} method in
turn. In {{RecordWriterOutput#collect}}, the {{OutputTag}} will be compared,
and the data will be sent only if they are the same. If only the {{collect}}
method is called, we add 1 to the statistics, which is the same as direct
re-use operator level stats. So we may still need to determine whether this
record will actually be sent instead of just calling the {{collect}} method.
{code:java}
@Override
public void collect(StreamRecord<OUT> record) {
if (this.outputTag != null) {
// we are not responsible for emitting to the main output.
return;
}
pushToRecordWriter(record);
}
@Override
public <X> void collect(OutputTag<X> outputTag, StreamRecord<X> record) {
if (this.outputTag == null || !this.outputTag.equals(outputTag)) {
// we are not responsible for emitting to the side-output specified by
this
// OutputTag.
return;
}
pushToRecordWriter(record);
}{code}
We can consider grouping {{RecordWriterOutput}} and {{ChainingOutput}}
according to {{OutputTag}} in {{BroadcastingOutputCollector}} (not considering
the {{selector}} situation for now), so that when sending record, we can be
sure that this record will be sent instead of just calling the {{collect}}
method.
> Task-level numRecordsOut metric may be underestimated
> -----------------------------------------------------
>
> Key: FLINK-18808
> URL: https://issues.apache.org/jira/browse/FLINK-18808
> Project: Flink
> Issue Type: Improvement
> Components: Runtime / Metrics, Runtime / Task
> Affects Versions: 1.11.1
> Reporter: ming li
> Assignee: ming li
> Priority: Major
> Labels: pull-request-available, usability
> Attachments: image-2020-08-04-11-28-13-800.png,
> image-2020-08-04-11-32-20-678.png, image-2020-08-13-18-36-13-282.png
>
>
> At present, we only register task-level numRecordsOut metric by reusing
> operator output record counter at the end of OperatorChain.
> {code:java}
> if (config.isChainEnd()) {
> operatorMetricGroup.getIOMetricGroup().reuseOutputMetricsForTask();
> }
> {code}
> If we only send data out through the last operator of OperatorChain, there is
> no problem with this statistics. But consider the following scenario:
> !image-2020-08-04-11-28-13-800.png|width=507,height=174!
> In this JobGraph, we not only send data in the last operator, but also send
> data in the middle operator of OperatorChain (the map operator just returns
> the original value directly). Below is one of our test topology, we can see
> that the statistics actually only have half of the total data received by the
> downstream.
> !image-2020-08-04-11-32-20-678.png|width=648,height=251!
> I think the data sent out by the intermediate operator should also be counted
> into the numRecordsOut of the Task. But currently we are not reusing
> operators output record counters in the intermediate operators, which leads
> to our task-level numRecordsOut metric is underestimated (although this has
> no effect on the actual operation of the job, it may affect our monitoring).
> A simple idea of mine is to modify the condition of reusing operators
> output record counter:
> {code:java}
> if (!config.getNonChainedOutputs(getUserCodeClassloader()).isEmpty()) {
> operatorMetricGroup.getIOMetricGroup().reuseOutputMetricsForTask();
> }{code}
> In addition, I have another question: If a record is broadcast to all
> downstream, should the numRecordsOut counter increase by one or the
> downstream number? It seems that currently we are adding one to calculate the
> numRecordsOut metric.
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