[jira] [Resolved] (SPARK-12137) Spark Streaming State Recovery limitations

["Sean Owen (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-12137?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Sean Owen resolved SPARK-12137.
-------------------------------
    Resolution: Not A Problem

> Spark Streaming State Recovery limitations
> ------------------------------------------
>
>                 Key: SPARK-12137
>                 URL: https://issues.apache.org/jira/browse/SPARK-12137
>             Project: Spark
>          Issue Type: Improvement
>          Components: Streaming
>    Affects Versions: 1.4.1
>            Reporter: Ravindar
>            Priority: Critical
>
> There was multiple threads in forums asking similar question without a clear answer and hence entering it here.
> We have a streaming application that goes through multi-step processing. In some of these steps stateful operations like *updateStateByKey* are used to maintain an accumulated running state (and other state info) with incoming RDD streams. As streaming application is incremental, it is imperative that we recover/restore from previous known state in the following two scenarios
>   1. On spark driver/streaming application failure.
>      In this scenario the driver/streaming application shutdown and restarted. The recommended approach is enable the *checkpoint(checkpointDir)* and use *StreamingContext.getOrCreate* to restore the context from checkpoint state.
>   2. Upgrade driver/streaming application with additional steps in the processing
>      In this scenario, we introduced new steps with downstream processing for new functionality without changes to existing steps.  Upgrading the streaming application with the new fails on  *StreamingContext.getOrCreate* as there is mismatch in checkpoint saved.
> Both of the above scenarios needs a unified approach where accumulated state has to be saved and restored. The first approach of restoring from checkpoint works for driver failure but not code upgrade. When the application code changed, there is a recommendation to delete checkpoint data when new code is deployed. If so, how do you reconstitute all of the stateful (e.g: updateStateByKey) information from the last run. Every streaming application has to save  up-to-date state for each session represented by key and then initialize it from this when a new session starts for the same key. Does every application have to create their own mechanism given this is very similar to current state checkpointing to HDFS. 



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