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Posted to issues@spark.apache.org by "Wenchen Fan (Jira)" <ji...@apache.org> on 2026/05/19 18:13:00 UTC

[jira] [Resolved] (SPARK-56550) Support source with fewer columns/fields in INSERT INTO WITH SCHEMA EVOLUTION

     [ https://issues.apache.org/jira/browse/SPARK-56550?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Wenchen Fan resolved SPARK-56550.
---------------------------------
    Fix Version/s: 4.3.0
       Resolution: Fixed

Issue resolved by pull request 55427
[https://github.com/apache/spark/pull/55427]

> Support source with fewer columns/fields in INSERT INTO WITH SCHEMA EVOLUTION
> -----------------------------------------------------------------------------
>
>                 Key: SPARK-56550
>                 URL: https://issues.apache.org/jira/browse/SPARK-56550
>             Project: Spark
>          Issue Type: Improvement
>          Components: SQL
>    Affects Versions: 4.1.0
>            Reporter: Szehon Ho
>            Assignee: Szehon Ho
>            Priority: Major
>              Labels: pull-request-available
>             Fix For: 4.3.0
>
>
> When using INSERT INTO ... WITH SCHEMA EVOLUTION, if the source has fewer nested struct fields than the target table, the insert fails with INCOMPATIBLE_DATA_FOR_TABLE.CANNOT_FIND_DATA or STRUCT_MISSING_FIELDS errors.
> MERGE INTO already supports this via the spark.sql.mergeNestedTypeCoercion.enabled config flag, which enables RECURSE mode in TableOutputResolver to fill missing nested fields with null.
> This ticket adds the equivalent support for INSERT INTO, gated by a new spark.sql.insertNestedTypeCoercion.enabled config flag (default false). When enabled together with WITH SCHEMA EVOLUTION, missing nested struct fields, fields in structs nested within arrays/maps, and trailing by-position columns are filled with their default values or null.



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