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Posted to issues@spark.apache.org by "Wenchen Fan (Jira)" <ji...@apache.org> on 2026/05/20 12:59:00 UTC

[jira] [Resolved] (SPARK-56931) Support ArrayType/MapType/StructType constant metadata in row materialization path

     [ https://issues.apache.org/jira/browse/SPARK-56931?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Wenchen Fan resolved SPARK-56931.
---------------------------------
    Fix Version/s:     (was: 5.0.0)
       Resolution: Fixed

Issue resolved by pull request 55962
[https://github.com/apache/spark/pull/55962]

> Support ArrayType/MapType/StructType constant metadata in row materialization path
> ----------------------------------------------------------------------------------
>
>                 Key: SPARK-56931
>                 URL: https://issues.apache.org/jira/browse/SPARK-56931
>             Project: Spark
>          Issue Type: Improvement
>          Components: SQL
>    Affects Versions: 4.2.0
>            Reporter: Matt Zhang
>            Assignee: Matt Zhang
>            Priority: Major
>              Labels: pull-request-available
>             Fix For: 4.2.0
>
>
> Follow-up to SPARK-56844, which enabled ArrayType/MapType/StructType in FileSourceMetadataAttribute and added the populate() branches for ConstantColumnVector. That covered the columnar metadata path (ColumnarBatch output).
> For file scans that produce row output (Batched=false: text, JSON, CSV, or any reader that does not vectorize), the metadata row is filled via FileFormat.updateMetadataInternalRow -> getFileConstantMetadataColumnValue -> Literal(extractor.apply(file)).
> Literal.apply(Any) dispatches on the value class and has no case for ArrayData / MapData / InternalRow, so a complex constant metadata column trips UNSUPPORTED_FEATURE.LITERAL_TYPE before the row is populated.
> Separately, SchemaPruning.sortLeftFieldsByRight recurses through the metadata schema and prunes nested struct fields inside an array/map/struct subfield. That is correct for data files (the reader projects the requested columns) but wrong for constant metadata, where each subfield is produced whole by a single extractor; pruning shaves catalyst row positions out from under the extractor.



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