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From "Johannes (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (FLINK-4586) NumberSequenceIterator and Accumulator threading issue
Date Wed, 07 Sep 2016 22:00:22 GMT

     [ https://issues.apache.org/jira/browse/FLINK-4586?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Johannes updated FLINK-4586:
----------------------------
    Attachment:     (was: FLINK4586Test.scala)

> NumberSequenceIterator and Accumulator threading issue
> ------------------------------------------------------
>
>                 Key: FLINK-4586
>                 URL: https://issues.apache.org/jira/browse/FLINK-4586
>             Project: Flink
>          Issue Type: Bug
>          Components: DataSet API
>    Affects Versions: 1.1.2
>            Reporter: Johannes
>            Priority: Minor
>
> There is a strange problem when using the NumberSequenceIterator in combination with
an AverageAccumulator.
> It seems like the individual accumulators are reinitialized and overwrite parts of intermediate
solutions.
> The following scala snippit exemplifies the problem.
> Instead of printing the correct average, the result should be {{50.5}} but is something
completely different, like {{8.08}}, dependent on the number of cores used.
> If the parallelism is set to {{1}} the result is correct, which indicates a likely threading
problem. 
> The problem occurs using the java and scala API.
> {code}
> env
>   .fromParallelCollection(new NumberSequenceIterator(1, 100))
>   .map(new RichMapFunction[Long, Long] {
> 	var a : AverageAccumulator = _
> 	override def map(value: Long): Long = {
> 	  a.add(value)
> 	  value
> 	}
> 	override def open(parameters: Configuration): Unit = {
> 	  a = new AverageAccumulator
> 	  getRuntimeContext.addAccumulator("test", a)
> 	}
>   })
>   .reduce((a, b) => a + b)
>   .print()
> val lastJobExecutionResult: JobExecutionResult = env.getLastJobExecutionResult
> println(lastJobExecutionResult.getAccumulatorResult("test"))
> {code}



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