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https://issues.apache.org/jira/browse/SPARK-43775?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17726767#comment-17726767
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Snoot.io commented on SPARK-43775:
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User 'aokolnychyi' has created a pull request for this issue:
https://github.com/apache/spark/pull/41300
> DataSource V2: Allow representing updates as deletes and inserts
> ----------------------------------------------------------------
>
> Key: SPARK-43775
> URL: https://issues.apache.org/jira/browse/SPARK-43775
> Project: Spark
> Issue Type: Sub-task
> Components: SQL
> Affects Versions: 3.5.0
> Reporter: Anton Okolnychyi
> Priority: Major
>
> It may be beneficial for data sources to represent updates as deletes and
> inserts for delta-based implementations. Specifically, it may be helpful to
> properly distribute and order records on write. Remember that delete records
> have only row ID and metadata attributes set. Update records have data, row
> ID, metadata attributes set. Insert records have only data attributes set.
> For instance, a data source may rely on a metadata column _row_id (synthetic
> internally generated) to identify the row and is partitioned by
> bucket(product_id). Splitting updates into inserts and deletes would allow
> data sources to cluster all update and insert records for the same partition
> into a single task. Otherwise, the clustering key for updates and inserts
> will be different (updates have _row_id set). This is critical to reduce the
> number of generated files.
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