AbsaOSS / AbsaOSS/enceladus

Caching of DataFrame between processing phases

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cloud Conformance feature priority: undecided Standardization under discussion
Dominant language
Scala
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33
Forks
16
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No merged PRs in 30d

Description

## Background
Right now, based on #1538, the DataFrame is re-read between each phase. This is potentially ineffective and results it extra IO (possible extra cost in cloud)

## Feature
Investigate and eventually implement some Spark caching strategy resistant to node failure.

## Proposed Solution
This might be a source reading for possible solution
https://sparkbyexamples.com/spark/spark-dataframe-cache-and-persist-explained/

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