[
https://issues.apache.org/jira/browse/SPARK-59358?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Anish Mahto updated SPARK-59358:
--------------------------------
Summary: SCD2 Ignore-null support; Project missing columns to microbatch
during preprocessMicrobatch (was: SCD2 Ignore-null suport; Project missing
columns to microbatch during preprocessMicrobatch)
> SCD2 Ignore-null support; Project missing columns to microbatch during
> preprocessMicrobatch
> -------------------------------------------------------------------------------------------
>
> Key: SPARK-59358
> URL: https://issues.apache.org/jira/browse/SPARK-59358
> Project: Spark
> Issue Type: Sub-task
> Components: Declarative Pipelines
> Affects Versions: 4.4.0
> Reporter: Anish Mahto
> Priority: Major
>
> During SCD2 microbatch reconciliation, it's possible an incoming microbatch
> does not contain a column that the target table already contains - this can
> happen if the upstream change data feed undergoes reductive schema evolution
> and drops a column.
> When this happens, in `Scd2ForeachBatchHandler` we union the microbatch with
> the target/aux tables using `allowMissingColumns=true`. The microbatch then
> desirably gains null entries for columns it does not contain but the target
> table does contain (and vice versa).
> With ignore-null, we need to do the microbatch projection specifically before
> the version map is constructed, so that those projected null columns can obey
> the active ignore-null selection during version map construction.
> In isolation, this is a no-op change; we project null columns onto the
> microbatch the same as before, we just do it earlier during microbatch
> reconciliation.
--
This message was sent by Atlassian Jira
(v8.20.10#820010)
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
