Hello, I'm using direct spark streaming (from kafka) with checkpointing, and everything works well until a restart. When I shut down (^C) the first streaming job, wait 1 minute, then re-submit, there is somehow a series of 0 event batches that get queued (corresponding to the 1 minute when the job was down). Eventually, the batches would resume processing, and I would see that each batch has roughly 2000 events.
I see that at the beginning of the second launch, the checkpoint dirs are found and "loaded", according to console output. Is this expected behavior? It seems like I might've configured something incorrectly, since I would expect with checkpointing that the streaming job would resume from checkpoint and continue processing from there (without seeing 0 event batches corresponding to when the job was down). Also, if I were to wait > 10 minutes or so before re-launching, there would be so many 0 event batches that the job would hang. Is this merely something to be "waited out", or should I set up some restart behavior/make a config change to discard checkpointing if the elapsed time has been too long? Thanks! <http://apache-spark-user-list.1001560.n3.nabble.com/file/n24450/Screen_Shot_2015-08-25_at_10.png> -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/Spark-Streaming-Checkpointing-Restarts-with-0-Event-Batches-tp24450.html Sent from the Apache Spark User List mailing list archive at Nabble.com. --------------------------------------------------------------------- To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional commands, e-mail: user-h...@spark.apache.org
