[jira] [Commented] (SPARK-18942) Support output operations for kinesis

["Shixiong Zhu (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-18942?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15785953#comment-15785953 ] 

Shixiong Zhu commented on SPARK-18942:
--------------------------------------

Thanks for your prototype. Actually, you can just implement an RDD action, or DataFrame DataSource and put them as a Spark package like [spark-redshift|https://github.com/databricks/spark-redshift]. [Spark Packages|https://spark-packages.org/] is a better place for such third-party data sources.

> Support output operations for kinesis
> -------------------------------------
>
>                 Key: SPARK-18942
>                 URL: https://issues.apache.org/jira/browse/SPARK-18942
>             Project: Spark
>          Issue Type: New Feature
>          Components: DStreams
>    Affects Versions: 2.0.2
>            Reporter: Takeshi Yamamuro
>            Priority: Trivial
>
> Spark does not support output operations (e.g. DStream#saveAsTextFile) for Kinesis. So, officially supporting this is useful for some AWS users, I think. An usage of the output operations is assumed as follows;
> {code}
> // Import a class that includes an output function
> scala> import org.apache.spark.streaming.kinesis.KinesisDStreamFunctions._
> // Create a DStream
> scala> val stream: DStream[String] = ...
> // Define a handler to convert the DStream type for output
> scala> val msgHandler = (s: String) => s.getBytes("UTF-8")
> // Define the output operation
> scala> kinesisStream.count().saveAsKinesisStream(streamName, endpointUrl, msgHandler)
> {code}
> A prototype I made is here: https://github.com/apache/spark/compare/master...maropu:OutputOpForKinesis



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