Tathagata Das created SPARK-24565:
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Summary: 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
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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