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Posted to issues@spark.apache.org by "Shixiong Zhu (JIRA)" <ji...@apache.org> on 2018/06/19 20:58:00 UTC
[jira] [Resolved] (SPARK-24565) Add API for in Structured Streaming
for exposing output rows of each microbatch as a DataFrame
[ https://issues.apache.org/jira/browse/SPARK-24565?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Shixiong Zhu resolved SPARK-24565.
----------------------------------
Resolution: Fixed
Fix Version/s: 2.4.0
Issue resolved by pull request 21571
[https://github.com/apache/spark/pull/21571]
> Add API for in Structured Streaming for exposing output rows of each microbatch as a DataFrame
> ----------------------------------------------------------------------------------------------
>
> Key: SPARK-24565
> URL: https://issues.apache.org/jira/browse/SPARK-24565
> Project: Spark
> Issue Type: Improvement
> Components: Structured Streaming
> Affects Versions: 2.3.0
> Reporter: Tathagata Das
> Assignee: Tathagata Das
> Priority: Major
> Fix For: 2.4.0
>
>
> Currently, the micro-batches in the MicroBatchExecution is not exposed to the user through any public API. This was because we did not want to expose the micro-batches, so that all the APIs we expose, we can eventually support them in the Continuous engine. But now that we have a better sense of building a ContinuousExecution, I am considering adding APIs which will run only the MicroBatchExecution. I have quite a few use cases where exposing the micro-batch output as a dataframe is useful.
> - Pass the output rows of each batch to a library that is designed only the batch jobs (example, uses many ML libraries need to collect() while learning).
> - Reuse batch data sources for output whose streaming version does not exist (e.g. redshift data source).
> - Writer the output rows to multiple places by writing twice for each batch. This is not the most elegant thing to do for multiple-output streaming queries but is likely to be better than running two streaming queries processing the same data twice.
> The proposal is to add a method {{foreachBatch(f: Dataset[T] => Unit)}} to Scala/Java/Python {{DataStreamWriter}}.
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