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From "ASF GitHub Bot (JIRA)" <>
Subject [jira] [Work logged] (BEAM-5063) Watermark does not progress for low traffic streams
Date Fri, 10 Aug 2018 14:51:00 GMT


ASF GitHub Bot logged work on BEAM-5063:

                Author: ASF GitHub Bot
            Created on: 10/Aug/18 14:50
            Start Date: 10/Aug/18 14:50
    Worklog Time Spent: 10m 
      Work Description: iemejia commented on issue #6178: [BEAM-5063] Fix Watermark does not
progress for low traffic streams
   R: @rangadi Can you please help me TAL since this is watermark related (like the other
PR), and also to validate that the change on `MovingFunction` does not have a side effect
on the watermark calculation for Pubsub. 

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Issue Time Tracking

    Worklog Id:     (was: 133623)
    Time Spent: 50m  (was: 40m)

> Watermark does not progress for low traffic streams
> ---------------------------------------------------
>                 Key: BEAM-5063
>                 URL:
>             Project: Beam
>          Issue Type: Bug
>          Components: io-java-kinesis
>    Affects Versions: 2.5.0
>            Reporter: Krzysztof Trubalski
>            Assignee: Jean-Baptiste Onofré
>            Priority: Major
>          Time Spent: 50m
>  Remaining Estimate: 0h
> We have a Dataflow Job copying data from multiple Kinesis streams into Big Query. Recently
we have noticed that the watermark on one of the streams frequently gets stuck although data
from that stream is still being processed (it progress only when the traffic increases or
Dataflow autoscaling feature kicks in).
>  Looking at the CloudWatch statistics for the affected stream, it has a really low traffic
rate - only ~1 event every few minutes . After investigation and consulting the issue with
Google's Dataflow Team, it looks like with such small amount of data on the stream, the function
calculating the watermark in KinesisReader reports progress incorrectly.
>  From my initial investigation, I suspect that the issue might be related to usage of
MovingFunction in KinesisReader. In the current implementation, it covers 1 minute period
of samples, since obtaining the min value flushes stale values, if the traffic is very low
the following call to significance check always returns false (as it relies on the number
of samples, and most of them were flushed by get() invocation).

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