You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "Saisai Shao (JIRA)" <ji...@apache.org> on 2014/08/20 08:32:25 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=14103486#comment-14103486 ] 

Saisai Shao commented on SPARK-3146:
------------------------------------

This issue can actually solve the problem mentioned in SPARK-2388, besides offer a more general way.

> 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
>            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.
> 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.



--
This message was sent by Atlassian JIRA
(v6.2#6252)

---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org