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https://issues.apache.org/jira/browse/SPARK-21873?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Sean Owen updated SPARK-21873:
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Issue Type: Improvement (was: Bug)
> CachedKafkaConsumer throws NonLocalReturnControl during fetching from Kafka
> ---------------------------------------------------------------------------
>
> Key: SPARK-21873
> URL: https://issues.apache.org/jira/browse/SPARK-21873
> Project: Spark
> Issue Type: Improvement
> Components: Structured Streaming
> Affects Versions: 2.1.0, 2.1.1, 2.2.0
> Reporter: Yuval Itzchakov
> Priority: Minor
> Original Estimate: 0h
> Remaining Estimate: 0h
>
> In Scala, using `return` inside a function causes a `NonLocalReturnControl`
> exception to be thrown and caught in order to escape the current scope.
> While profiling Structured Streaming in production, it clearly shows:
> !https://user-images.githubusercontent.com/3448320/29743366-4149ef78-8a99-11e7-94d6-f0cbb691134a.png!
> This happens during a 1 minute profiling session on a single executor. The
> code is:
> {code:java}
> while (toFetchOffset != UNKNOWN_OFFSET) {
> try {
> return fetchData(toFetchOffset, untilOffset, pollTimeoutMs,
> failOnDataLoss)
> } catch {
> case e: OffsetOutOfRangeException =>
> // When there is some error thrown, it's better to use a new
> consumer to drop all cached
> // states in the old consumer. We don't need to worry about the
> performance because this
> // is not a common path.
> resetConsumer()
> reportDataLoss(failOnDataLoss, s"Cannot fetch offset
> $toFetchOffset", e)
> toFetchOffset = getEarliestAvailableOffsetBetween(toFetchOffset,
> untilOffset)
> }
> }
> {code}
> This happens because this method is converted to a function which is ran
> inside:
> {code:java}
> private def runUninterruptiblyIfPossible[T](body: => T): T
> {code}
> We should avoid using `return` in general, and here specifically as it is a
> hot path for applications using Kafka.
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