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Posted to issues@spark.apache.org by "Jose Torres (Jira)" <ji...@apache.org> on 2026/06/04 21:57:00 UTC

[jira] [Resolved] (SPARK-57134) Implement SCD2 Batch Processor; Preprocess Microbatch

     [ https://issues.apache.org/jira/browse/SPARK-57134?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Jose Torres resolved SPARK-57134.
---------------------------------
    Fix Version/s: 4.3.0
       Resolution: Fixed

Issue resolved by pull request 56208
[https://github.com/apache/spark/pull/56208]

> Implement SCD2 Batch Processor; Preprocess Microbatch
> -----------------------------------------------------
>
>                 Key: SPARK-57134
>                 URL: https://issues.apache.org/jira/browse/SPARK-57134
>             Project: Spark
>          Issue Type: Sub-task
>          Components: Declarative Pipelines
>    Affects Versions: 4.3.0
>            Reporter: Anish Mahto
>            Assignee: Anish Mahto
>            Priority: Major
>              Labels: pull-request-available
>             Fix For: 4.3.0
>
>
> {*}Preamble{*}:
> The SCD type 2 flow is a foreachBatch streaming query on an input change-data-feed, and is responsible for reconciling the incoming change data onto some target table that follows SCD2 replication semantics.
> SCD2 flows also maintain an "auxiliary" table to keep track of early-arriving out-of-order received events state. Each microbatch will need to reconcile against this auxiliary table as well, and update the auxiliary table's state appropriately for future microbatches.
>  
> *Preprocess Microbatch*
> For SCD2, preprocessing the microbatch is all about getting it in the right shape, aligned with the shape of the target table the microbatch will be merged into + the shape that SCD2 itself as a standard demands.
> That is:
>  * The microbatch must have a start-at and end-at columns projected as per the SCD2 standard, to indicate that a historical/alive record was active between those sequence stamps
>  * The microbatch will have the operational CDC metadata column projected, which is needed to reconcile late arriving events/bookkeeping
>  * As per the Spark AutoCDC API, the microbatch should project down to just the user-specified column selection
> Implement the part of the core SCD2 microbatch processor that does this microbatch preprocessing.



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