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https://issues.apache.org/jira/browse/SPARK-10320?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14725951#comment-14725951
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Sudarshan Kadambi commented on SPARK-10320:
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"it's almost certainly not the same thread".
Yes, you're right. The new topic additions would happen in a different thread
than the one that initialized the spark context and started the streaming
context.
Could you describe how the map of topic-partition and consumption offsets would
be supplied? As an additional argument to createDirectStream() (callable even
after the streaming context is started?) Perhaps a more complete sketch of the
possible solution (even from just an end user API perspective) would help.
Also, while we're looking to solve this problem in the context of Kafka, it'd
be better to generalize the solution over all sorts of channels over which data
can stream over.
> Kafka Support new topic subscriptions without requiring restart of the
> streaming context
> ----------------------------------------------------------------------------------------
>
> Key: SPARK-10320
> URL: https://issues.apache.org/jira/browse/SPARK-10320
> Project: Spark
> Issue Type: New Feature
> Components: Streaming
> Reporter: Sudarshan Kadambi
>
> Spark Streaming lacks the ability to subscribe to newer topics or unsubscribe
> to current ones once the streaming context has been started. Restarting the
> streaming context increases the latency of update handling.
> Consider a streaming application subscribed to n topics. Let's say 1 of the
> topics is no longer needed in streaming analytics and hence should be
> dropped. We could do this by stopping the streaming context, removing that
> topic from the topic list and restarting the streaming context. Since with
> some DStreams such as DirectKafkaStream, the per-partition offsets are
> maintained by Spark, we should be able to resume uninterrupted (I think?)
> from where we left off with a minor delay. However, in instances where
> expensive state initialization (from an external datastore) may be needed for
> datasets published to all topics, before streaming updates can be applied to
> it, it is more convenient to only subscribe or unsubcribe to the incremental
> changes to the topic list. Without such a feature, updates go unprocessed for
> longer than they need to be, thus affecting QoS.
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