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