[
https://issues.apache.org/jira/browse/SPARK-10320?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14726076#comment-14726076
]
Cody Koeninger commented on SPARK-10320:
----------------------------------------
You would supply a function, similar to the way createDirectStream currently
takes a messageHandler: MessageAndMetadata[K, V] => R
The type of that function would be
(Time, Map[TopicAndPartition, Long], Map[TopicAndPartition, LeaderOffset]) =>
(Map[TopicAndPartition, Long, Map[TopicAndPartition, LeaderOffset])
in other words
(time, fromOffsets, untilOffsets) => (fromOffsets, untilOffsets)
Your function would be called in the compute() method of the dstream, after
contacting the leaders and before making the rdd for the next batch.
That would let you make arbitrary modifications to the topics / partitions /
offsets.
As far as the desire for a general solution, I think this is a kafka-specific
concern. Not all streams have topics.
> 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.
--
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
