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Posted to issues@beam.apache.org by "ASF GitHub Bot (Jira)" <ji...@apache.org> on 2019/10/08 07:39:00 UTC

[jira] [Work logged] (BEAM-5690) Issue with GroupByKey in BeamSql using SparkRunner

     [ https://issues.apache.org/jira/browse/BEAM-5690?focusedWorklogId=324908&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-324908 ]

ASF GitHub Bot logged work on BEAM-5690:
----------------------------------------

                Author: ASF GitHub Bot
            Created on: 08/Oct/19 07:38
            Start Date: 08/Oct/19 07:38
    Worklog Time Spent: 10m 
      Work Description: echauchot commented on issue #9567: [BEAM-5690] Fix Zero value issue with GroupByKey/CountByKey in SparkRunner
URL: https://github.com/apache/beam/pull/9567#issuecomment-539387837
 
 
   @bmv126 currently taking a look at the watermark logic in your PR. Sorry for the delay once again
   
   
 
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Issue Time Tracking
-------------------

    Worklog Id:     (was: 324908)
    Time Spent: 1h  (was: 50m)

> Issue with GroupByKey in BeamSql using SparkRunner
> --------------------------------------------------
>
>                 Key: BEAM-5690
>                 URL: https://issues.apache.org/jira/browse/BEAM-5690
>             Project: Beam
>          Issue Type: Task
>          Components: runner-spark
>            Reporter: Kenneth Knowles
>            Priority: Major
>          Time Spent: 1h
>  Remaining Estimate: 0h
>
> Reported on user@
> {quote}We are trying to setup a pipeline with using BeamSql and the trigger used is default (AfterWatermark crosses the window). 
> Below is the pipeline:
>   
>    KafkaSource (KafkaIO) 
>        ---> Windowing (FixedWindow 1min)
>        ---> BeamSql
>        ---> KafkaSink (KafkaIO)
>                          
> We are using Spark Runner for this. 
> The BeamSql query is:
> {code}select Col3, count(*) as count_col1 from PCOLLECTION GROUP BY Col3{code}
> We are grouping by Col3 which is a string. It can hold values string[0-9]. 
>              
> The records are getting emitted out at 1 min to kafka sink, but the output record in kafka is not as expected.
> Below is the output observed: (WST and WET are indicators for window start time and window end time)
> {code}
> {"count_col1":1,"Col3":"string5","WST":"2018-10-09  09-55-00 0000  +0000","WET":"2018-10-09  09-56-00 0000  +0000"}
> {"count_col1":3,"Col3":"string7","WST":"2018-10-09  09-55-00 0000  +0000","WET":"2018-10-09  09-56-00 0000  +0000"}
> {"count_col1":2,"Col3":"string8","WST":"2018-10-09  09-55-00 0000  +0000","WET":"2018-10-09  09-56-00 0000  +0000"}
> {"count_col1":1,"Col3":"string2","WST":"2018-10-09  09-55-00 0000  +0000","WET":"2018-10-09  09-56-00 0000  +0000"}
> {"count_col1":1,"Col3":"string6","WST":"2018-10-09  09-55-00 0000  +0000","WET":"2018-10-09  09-56-00 0000  +0000"}
> {"count_col1":0,"Col3":"string6","WST":"2018-10-09  09-55-00 0000  +0000","WET":"2018-10-09  09-56-00 0000  +0000"}
> {"count_col1":0,"Col3":"string6","WST":"2018-10-09  09-55-00 0000  +0000","WET":"2018-10-09  09-56-00 0000  +0000"}
> {"count_col1":0,"Col3":"string6","WST":"2018-10-09  09-55-00 0000  +0000","WET":"2018-10-09  09-56-00 0000  +0000"}
> {"count_col1":0,"Col3":"string6","WST":"2018-10-09  09-55-00 0000  +0000","WET":"2018-10-09  09-56-00 0000  +0000"}
> {"count_col1":0,"Col3":"string6","WST":"2018-10-09  09-55-00 0000  +0000","WET":"2018-10-09  09-56-00 0000  +0000"}
> {"count_col1":0,"Col3":"string6","WST":"2018-10-09  09-55-00 0000  +0000","WET":"2018-10-09  09-56-00 0}
> {code}
> {quote}



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