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Shixiong Zhu commented on SPARK-19233: -------------------------------------- I don't think filtering "generatedRDDs" will work. "generateJobs" will change states of DStreamGraph and DStreams. Filtering "generatedRDDs" will make the checkpoint inconsistent and break a lot of things. Will this behavior affect correctness? > Inconsistent Behaviour of Spark Streaming Checkpoint > ---------------------------------------------------- > > Key: SPARK-19233 > URL: https://issues.apache.org/jira/browse/SPARK-19233 > Project: Spark > Issue Type: Improvement > Components: DStreams > Affects Versions: 2.0.0, 2.0.1, 2.0.2, 2.1.0 > Reporter: Nan Zhu > > When checking one of our application logs, we found the following behavior > (simplified) > 1. Spark application recovers from checkpoint constructed at timestamp 1000ms > 2. The log shows that Spark application can recover RDDs generated at > timestamp 2000, 3000 > The root cause is that generateJobs event is pushed to the queue by a > separate thread (RecurTimer), before doCheckpoint event is pushed to the > queue, there might have been multiple generatedJobs being processed. As a > result, when doCheckpoint for timestamp 1000 is processed, the generatedRDDs > data structure containing RDDs generated at 2000, 3000 is serialized as part > of checkpoint of 1000. > It brings overhead for debugging and coordinate our offset management > strategy with Spark Streaming's checkpoint strategy when we are developing a > new type of DStream which integrates Spark Streaming with an internal message > middleware. > The proposed fix is to filter generatedRDDs according to checkpoint timestamp > when serializing it. -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org