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https://issues.apache.org/jira/browse/FLINK-14712?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16974957#comment-16974957
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lining commented on FLINK-14712:
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No problem.
> Improve back-pressure reporting mechanism
> -----------------------------------------
>
> Key: FLINK-14712
> URL: https://issues.apache.org/jira/browse/FLINK-14712
> Project: Flink
> Issue Type: Improvement
> Components: Runtime / Metrics, Runtime / Network, Runtime / REST
> Reporter: lining
> Assignee: lining
> Priority: Major
> Attachments: image-2019-11-12-14-30-16-130.png
>
>
> h4. (1) The current monitor is heavy-weight.
> * Backpressure monitoring works by repeatedly taking stack trace samples
> of your running tasks.
> h4. (2) It is difficult to find out which vertex is the source of
> backpressure.
> * User need to know current and upstream's network metric to judge current
> whether is the source of backpressure. Now user has to record relevant
> information.
> h3. Proposed Changes
> 1. expose the new mechanism implemented in FLINK-14472 as a "is
> back-pressured" metric.
> 2. show the vertex that produces the backpressure source for the job.
> 3. expose network pool usage in IOMetricsInfo:
> # if sub task is not back pressured, but it is causing a back pressure (full
> input, empty output)
> # by comparing exclusive/floating buffers usage, whether all channels are
> back-pressured or only some of them
> {code:java}
> public final class IOMetricsInfo {
> private final float outPoolUsage;
> private final float inputExclusiveBuffersUsage;
> private final float inputFloatingBuffersUsage;
> }
> {code}
> JobDetailsInfo.JobVertexDetailsInfo merge use Math.max.(ps: outPoolUsage is
> from upstream)
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