Details
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New Feature
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Status: Open
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P3
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Resolution: Unresolved
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None
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None
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None
Description
The source watermark metrics show the consumer latency of Source.
It allows the user to know the health of the job, or it can be used to monitor and alarm.
Since each runner is likely already tracking a watermark, another option here is to just have the runner report it appropriately, rather than having the source report it using metrics. This also addresses the fact that even if the source has advanced to 8:00, the runner may still know about buffered elements at 7:00, and so not advance the watermark all the way to 8:00. bchambers
Includes:
1.Source watermark (`min` amongst all splits):
type = Gauge, namespace = io, name = source_watermark
2.Source watermark per split:
type = Gauge, namespace = io.splits, name = <split_id>.source_watermark
Attachments
Issue Links
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- In Progress
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- links to
1.
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Add Watermark Metrics in Flink Runner |
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Open | Unassigned |
2.
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Add Watermark Metrics in Dataflow runner |
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Open | Unassigned |
3.
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Add Watermark Metrics in Spark runner |
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Open | Unassigned |
4.
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Add Watermark Metrics in Apex runner |
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Resolved | Unassigned |