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Currently, RFS has two core responsibilities:
- Reading from snapshots
- Writing to the target cluster
There are other potential use cases where only reading from snapshots is valuable.
For example, embedding the snapshot-reading logic into a Spark/EMR application could enable:
- Running parity/data quality checks across clusters by taking snapshots from both and comparing them directly in Spark.
- During production data issues, taking a snapshot of the affected indices before mitigation, and then using Spark to assess the impact by reading directly from the snapshot.
Extracting the snapshot-reader logic into a standalone library would unlock these types of use cases outside of RFS.
sumobrian
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