[
https://issues.apache.org/jira/browse/FLINK-5652?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Dmitry Golubets updated FLINK-5652:
-----------------------------------
Description:
When async operation timeout is > 0, the number of StreamRecordQueueEntry
instances keeps growing.
It can be easily reproduced with the following code:
{code}
val src: DataStream[Int] = env.fromCollection((1 to Int.MaxValue).iterator)
val asyncFunction = new AsyncFunction[Int, Int] with Serializable {
override def asyncInvoke(input: Int, collector: AsyncCollector[Int]): Unit
= {
collector.collect(List(input))
}
}
AsyncDataStream.unorderedWait(src, asyncFunction, 1, TimeUnit.MINUTES,
1).print()
{code}
was:
When async operation timeout is > 0, the number of StreamRecordQueueEntry
instances keeps growing.
It can be easily reproduced with the following code:
{code}
val src: DataStream[Int] = env.fromCollection((1 to Int.MaxValue).iterator)
val asyncFunction = new AsyncFunction[Int, Int] with Serializable {
override def asyncInvoke(input: Int, collector: AsyncCollector[Int]): Unit
= {
collector.collect(List(input))
}
}
AsyncDataStream.unorderedWait(src, asyncFunction, 0, TimeUnit.MINUTES,
1).print()
{code}
> Memory leak in AsyncDataStream
> ------------------------------
>
> Key: FLINK-5652
> URL: https://issues.apache.org/jira/browse/FLINK-5652
> Project: Flink
> Issue Type: Bug
> Components: DataStream API
> Affects Versions: 1.3.0
> Reporter: Dmitry Golubets
>
> When async operation timeout is > 0, the number of StreamRecordQueueEntry
> instances keeps growing.
> It can be easily reproduced with the following code:
> {code}
> val src: DataStream[Int] = env.fromCollection((1 to Int.MaxValue).iterator)
>
> val asyncFunction = new AsyncFunction[Int, Int] with Serializable {
> override def asyncInvoke(input: Int, collector: AsyncCollector[Int]):
> Unit = {
> collector.collect(List(input))
> }
> }
>
> AsyncDataStream.unorderedWait(src, asyncFunction, 1, TimeUnit.MINUTES,
> 1).print()
> {code}
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