[ https://issues.apache.org/jira/browse/SPARK-24565?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Apache Spark reassigned SPARK-24565: ------------------------------------ Assignee: Apache Spark (was: Tathagata Das) > 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: Apache Spark > Priority: Major > > 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`. -- This message was sent by Atlassian JIRA (v7.6.3#76005) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org