uncleGen opened a new pull request #24400: [SPARK-27503][DStream] JobGenerator thread exit for some fatal errors but application keeps running URL: https://github.com/apache/spark/pull/24400 ## What changes were proposed in this pull request? JobGenerator thread (including some other EventLoop threads) may exit for some fatal error, like OOM, but Spark Streaming job keep running with no batch job generating. Currently, we only report any non-fatal error. ``` override def run(): Unit = { try { while (!stopped.get) { val event = eventQueue.take() try { onReceive(event) } catch { case NonFatal(e) => try { onError(e) } catch { case NonFatal(e) => logError("Unexpected error in " + name, e) } } } } catch { case ie: InterruptedException => // exit even if eventQueue is not empty case NonFatal(e) => logError("Unexpected error in " + name, e) } } ``` In some corner cases, these event threads may exit with OOM error, but driver thread can still keep running. ## How was this patch tested? existing unit tests
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