AnishMahto opened a new pull request, #56686:
URL: https://github.com/apache/spark/pull/56686
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### What changes were proposed in this pull request?
Today, the auxiliary table is managed (created, full-refreshed, etc.) during
flow execution. For SCD1 this is functionally correct but is poor timing. The
auxiliary table should be managed side-by-side with the target table that it is
a companion to, and table-level validations for the AutoCDC auxiliary table
(ex. key/scd type drifts) should happen well before flow execution.
For SCD2 which is coming soon, the existing control flow is incompatible.
SCD2 auxiliary tables will contain data columns (SCD1 auxiliary tables only
contain keys columns + CDC metadata column), and therefore will actually need
to undergo schema evolution the same way that target tables do.
The proposal here is to refactor the auxiliary table management such that
DatasetManager recognizes the general concept of an auxiliary table, and manage
full-refresh/schema evolution/catalog table validations along side the target
table it companions.
We should no longer be materializing or validating tables during flow
execution.
### Why are the changes needed?
Refactor lifecycle management to `DatasetManager` for better control flow
for SCD1, and necessary for schema evolution of auxiliary table for SCD2 (which
will be introduced in a future PR).
### Does this PR introduce _any_ user-facing change?
Validation now happens earlier and during dataset materialization, rather
than during flow execution. The validations themselves remain unchanged, and
one new validation for SCD-type change was introduced in preparation for SCD2
flows.
### How was this patch tested?
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