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Posted to issues@spark.apache.org by "Anish Mahto (Jira)" <ji...@apache.org> on 2026/09/08 19:54:00 UTC
[jira] [Created] (SPARK-59347) SCD2 Ignore-null support; apply version map key renames after union with target
Anish Mahto created SPARK-59347:
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Summary: SCD2 Ignore-null support; apply version map key renames after union with target
Key: SPARK-59347
URL: https://issues.apache.org/jira/browse/SPARK-59347
Project: Spark
Issue Type: Sub-task
Components: Declarative Pipelines
Affects Versions: 4.4.0
Reporter: Anish Mahto
Part of the contract for the SCD2 version map is the keys in the version map should track exactly with the data column names.
Complexity arises when case insensitivity is used, and the incoming microbatch has a different case-spelling for certain columns than the persisted target/aux tables.
When `Scd2ForeachBatchHandler` does a [union with the incoming microbatch rows and the existing target/aux table rows|https://github.com/apache/spark/blob/master/sql/pipelines/src/main/scala/org/apache/spark/sql/pipelines/autocdc/Scd2ForeachBatchHandler.scala#L104-L106], due to ordering of the union operators, the resulting DF will respect the case-spelling on the incoming microbatch.
But when this dataframe is eventually merged back into the target/aux tables, the existing case-spelling on those tables will win. This is no longer acceptable since the version map is constructed by referencing column names in the dataframe. If those column names change, the version map's keys need to also change for consistency.
The proposal is two-fold:
1. The 3-way union should setup target table's df as the first operator, so that from this point forward rows always respect the persisted target table's case-spellings
2. Rename the in-memory version map keys on `preprocessedBatchDf` to use the same case-spelling as the target table, right before the union operation
Then both before and after the union, the version map keys match 1:1 with data column names, under whatever case-sensitivity scheme is configured.
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