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https://issues.apache.org/jira/browse/FLINK-6109?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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aitozi reassigned FLINK-6109:
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Assignee: aitozi
> Add "consumer lag" report metric to FlinkKafkaConsumer
> ------------------------------------------------------
>
> Key: FLINK-6109
> URL: https://issues.apache.org/jira/browse/FLINK-6109
> Project: Flink
> Issue Type: New Feature
> Components: Kafka Connector, Streaming Connectors
> Reporter: Tzu-Li (Gordon) Tai
> Assignee: aitozi
>
> This is a feature discussed in this ML:
> http://apache-flink-user-mailing-list-archive.2336050.n4.nabble.com/Telling-if-a-job-has-caught-up-with-Kafka-td12261.html.
> As discussed, we can expose two kinds of "consumer lag" metrics for this:
> - *current consumer lag per partition:* the current difference between the
> latest offset and the last collected record. This metric is calculated and
> updated at a configurable interval. This metric basically serves as an
> indicator of how the consumer is keeping up with the head of partitions. I
> propose to name this {{currentOffsetLag}}.
> - *Consumer lag of last checkpoint per partition:* the difference between
> the latest offset and the offset stored in the checkpoint. This metric is
> only updated when checkpoints are completed. It serves as an indicator of how
> much data may need to be replayed in case of a failure. I propose to name
> this {{lastCheckpointedOffsetLag}}.
> I don't think it is reasonable to define a metric of whether or not a
> consumer has "caught up" with the HEAD. That would imply a threshold for the
> offset difference. We should probably leave this "caught up" logic for the
> user to determine themselves when they query this metric.
> The granularity of the metric is per-FlinkKafkaConsumer, and independent of
> the consumer group.id used (the offset used to calculate consumer lag is the
> internal offset state of the FlinkKafkaConsumer, not the consumer group's
> committed offsets in Kafka).
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