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https://issues.apache.org/jira/browse/BEAM-5690?focusedWorklogId=325078&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-325078
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ASF GitHub Bot logged work on BEAM-5690:
----------------------------------------
Author: ASF GitHub Bot
Created on: 08/Oct/19 13:51
Start Date: 08/Oct/19 13:51
Worklog Time Spent: 10m
Work Description: echauchot commented on pull request #9567: [BEAM-5690]
Fix Zero value issue with GroupByKey/CountByKey in SparkRunner
URL: https://github.com/apache/beam/pull/9567#discussion_r332478533
##########
File path:
runners/spark/src/test/java/org/apache/beam/runners/spark/translation/streaming/CreateStreamTest.java
##########
@@ -451,6 +457,47 @@ public void
testAdvanceWatermarkEqualToPositiveInfinityThrows() {
source.advanceWatermarkForNextBatch(BoundedWindow.TIMESTAMP_MAX_VALUE);
}
+ @Test
+ public void testInStreamingModeCountByKey() throws Exception {
Review comment:
First thought that this could be a validatesRunner test but then I
remembered that spark has its own validates runner tests for streaming. So,
this place is not perfect but will be fine
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Issue Time Tracking
-------------------
Worklog Id: (was: 325078)
Time Spent: 1.5h (was: 1h 20m)
> 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: 1.5h
> 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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