szehon-ho commented on code in PR #57625:
URL: https://github.com/apache/spark/pull/57625#discussion_r3677364948
##########
sql/pipelines/src/main/scala/org/apache/spark/sql/pipelines/graph/DatasetManager.scala:
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@@ -453,6 +468,12 @@ object DatasetManager extends Logging {
targetTableIdentifier = autoCdcSpec.targetTableIdentifier,
expectedScdType = autoCdcSpec.expectedScdType
)
+ AutoCdcAuxiliaryTable.validateNoTrackHistoryDrift(
+ existingAuxiliaryTable = existingAuxiliaryTable,
+ targetTableIdentifier = autoCdcSpec.targetTableIdentifier,
+ expectedTrackHistoryColumnNames =
autoCdcSpec.expectedTrackHistoryColumnNames,
+ resolver = context.spark.sessionState.conf.resolver
+ )
Review Comment:
Nit: the `caseSensitiveAnalysis` used to *record* the set comes from
`inputAutoCdcFlow.df.sparkSession` (`AutoCdcAuxiliaryTable.scala:245`), while
the `resolver` used to *validate* it comes from `context.spark` here. Can we
source both from one session? The `val` on `AutoCdcMergeFlow` suggested in the
other comment would settle the recording side.
Also worth a test: a case-only rename of a source column across runs
(`value` -> `Value`) is the case that actually exercises this resolver, and
neither end-to-end test covers it - both vary the casing of the `TRACK HISTORY
ON` selection, which is normalized away before the comparison.
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