Our additional question on checkpointing is basically the logistics of it --
At which point does the data get written into checkpointing? Is it written
as soon as the driver program retrieves an RDD from Kafka (or another
source)? Or, is it written after that RDD has been processed and we're
basically moving on to the next RDD?
What I'm driving at is, what happens if the driver program is killed? The
next time it's started, will it know, from Spark Streaming's checkpointing,
to resume from the same RDD that was being processed at the time of the
program getting killed? In other words, will we, upon restarting the
consumer, resume from the RDD that was unfinished, or will we be looking at
the next RDD?
Will we pick up from the last known *successfully processed* topic offset?
Thanks.
On Fri, Jul 31, 2015 at 1:52 PM, Sean Owen <so...@cloudera.com> wrote:
> If you've set the checkpoint dir, it seems like indeed the intent is
> to use a default checkpoint interval in DStream:
>
> private[streaming] def initialize(time: Time) {
> ...
> // Set the checkpoint interval to be slideDuration or 10 seconds,
> which ever is larger
> if (mustCheckpoint && checkpointDuration == null) {
> checkpointDuration = slideDuration * math.ceil(Seconds(10) /
> slideDuration).toInt
> logInfo("Checkpoint interval automatically set to " +
> checkpointDuration)
> }
>
> Do you see that log message? what's the interval? that could at least
> explain why it's not doing anything, if it's quite long.
>
> It sort of seems wrong though since
> https://spark.apache.org/docs/latest/streaming-programming-guide.html
> suggests it was intended to be a multiple of the batch interval. The
> slide duration wouldn't always be relevant anyway.
>
> On Fri, Jul 31, 2015 at 6:16 PM, Dmitry Goldenberg
> <dgoldenberg...@gmail.com> wrote:
> > I've instrumented checkpointing per the programming guide and I can tell
> > that Spark Streaming is creating the checkpoint directories but I'm not
> > seeing any content being created in those directories nor am I seeing the
> > effects I'd expect from checkpointing. I'd expect any data that comes
> into
> > Kafka while the consumers are down, to get picked up when the consumers
> are
> > restarted; I'm not seeing that.
> >
> > For now my checkpoint directory is set to the local file system with the
> > directory URI being in this form: file:///mnt/dir1/dir2. I see a
> > subdirectory named with a UUID being created under there but no files.
> >
> > I'm using a custom JavaStreamingContextFactory which creates a
> > JavaStreamingContext with the directory set into it via the
> > checkpoint(String) method.
> >
> > I'm currently not invoking the checkpoint(Duration) method on the DStream
> > since I want to first rely on Spark's default checkpointing interval. My
> > streaming batch duration millis is set to 1 second.
> >
> > Anyone have any idea what might be going wrong?
> >
> > Also, at which point does Spark delete files from checkpointing?
> >
> > Thanks.
>
