etienne edited comment on SPARK-17606 at 10/13/16 1:17 PM:

Theses string are log as DEBUG  or in upper logs level ? ( because there is a 
lot of log to process )

edit : I found that 
log4j.logger.org.apache.spark.streaming.scheduler.JobGenerator=DEBUG I think 
this will help

was (Author: crakjie):
Theses string are log as DEBUG  or in upper logs level ? ( because there is a 
lot of log to process )

> New batches are not created when there are 1000 created after restarting 
> streaming from checkpoint.
> ---------------------------------------------------------------------------------------------------
>                 Key: SPARK-17606
>                 URL: https://issues.apache.org/jira/browse/SPARK-17606
>             Project: Spark
>          Issue Type: Bug
>          Components: Streaming
>    Affects Versions: 1.6.1
>            Reporter: etienne
> When spark restarts from a checkpoint after being down for a while.
> It recreates missing batch since the down time.
> When there are few missing batches, spark creates new incoming batch every 
> batchTime, but when there is enough missing time to create 1000 batches no 
> new batch is created.
> So when all these batch are completed the stream is idle ...
> I think there is a rigid limit set somewhere.
> I was expecting that spark continue to recreate missed batches, maybe not all 
> at once ( because it's look like it's cause driver memory problem ), and then 
> recreate batches each batchTime.
> Another solution would be to not create missing batches but still restart the 
> direct input.
> Right know for me the only solution to restart a stream after a long break it 
> to remove the checkpoint to allow the creation of a new stream. But losing 
> all my states.
> ps : I'm speaking about direct Kafka input because it's the source I'm 
> currently using, I don't know what happens with other sources.

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