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Posted to issues@spark.apache.org by "Cody Koeninger (JIRA)" <ji...@apache.org> on 2014/11/03 22:36:33 UTC
[jira] [Commented] (SPARK-3146) Improve the flexibility of Spark
Streaming Kafka API to offer user the ability to process message before
storing into BM
[ https://issues.apache.org/jira/browse/SPARK-3146?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14195146#comment-14195146 ]
Cody Koeninger commented on SPARK-3146:
---------------------------------------
I think this PR is an elegant way to solve SPARK-2388, which is an otherwise blocking bug for our usage of kafka.
Absent a concrete design for doing something equivalent for all InputDStreams, I'd encourage merging it.
> Improve the flexibility of Spark Streaming Kafka API to offer user the ability to process message before storing into BM
> ------------------------------------------------------------------------------------------------------------------------
>
> Key: SPARK-3146
> URL: https://issues.apache.org/jira/browse/SPARK-3146
> Project: Spark
> Issue Type: Improvement
> Components: Streaming
> Affects Versions: 1.0.2, 1.1.0
> Reporter: Saisai Shao
>
> Currently Spark Streaming Kafka API stores the key and value of each message into BM for processing, potentially this may lose the flexibility for different requirements:
> 1. currently topic/partition/offset information for each message is discarded by KafkaInputDStream. In some scenarios people may need this information to better filter the message, like SPARK-2388 described.
> 2. People may need to add timestamp for each message when feeding into Spark Streaming, which can better measure the system latency.
> 3. Checkpointing the partition/offsets or others...
> So here we add a messageHandler in interface to give people the flexibility to preprocess the message before storing into BM. In the meantime time this improvement keep compatible with current API.
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