Hemant Sakharkar created SPARK-47742:
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Summary: Spark Transformation with Multi Case filter can improve
efficiency
Key: SPARK-47742
URL: https://issues.apache.org/jira/browse/SPARK-47742
Project: Spark
Issue Type: New Feature
Components: Spark Core
Affects Versions: 4.0.0
Reporter: Hemant Sakharkar
In Feature Engineering we need to process the input data to create feature and
feature vectors which are required to train the model. For which we need to do
multiple spark transformations (etc:map, filter etc) the spark has very good
optimization for multiple transformations due to its lazy execution. It
combines multiple transformations into fewer transformations which helps to
optimize the overall execution time.
I found that we can still improve the execution time in the case of filters.
*Sample Run Results:*
Records :50,000,000
5 filter Execution Time: (t2-t1) 24854 millisec
5 filter with Map Execution Time: (t3-t2) 5212 millisec
We can very well improve multiple X times and reduce significant memory
footprint for a complex DAG of Spark Transformation.
Sample illustration can be found here
[https://docs.google.com/document/d/1gdWR2TwbCfiuRF51EHA1zRnD9ES_neIvIsgEvizrjuo/edit?usp=sharing]
Need support of such transformation in Spark Core so that more complex
transformation can be supported. Some illustration is provided in above
document.
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