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https://issues.apache.org/jira/browse/SPARK-27943?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16856595#comment-16856595
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Apache Spark commented on SPARK-27943:
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User 'beliefer' has created a pull request for this issue:
https://github.com/apache/spark/pull/24372
> Implement default constraint with Column for Hive table
> -------------------------------------------------------
>
> Key: SPARK-27943
> URL: https://issues.apache.org/jira/browse/SPARK-27943
> Project: Spark
> Issue Type: New Feature
> Components: SQL
> Affects Versions: 2.3.0, 2.4.0
> Reporter: jiaan.geng
> Priority: Major
>
> Default constraint with column is ANSI standard.
> Hive 3.0+ has supported default constraint
> ref:https://issues.apache.org/jira/browse/HIVE-18726
> But Spark SQL implement this feature not yet.
> Hive is widely used in production environments and is the standard in the
> field of big data in fact. But Hive exists many version used in production
> and the feature between each version are different.
> Spark SQL need to implement default constraint, but there are two points to
> pay attention to in design:
> One is Spark SQL should reduce coupling with Hive.
> Another is default constraint could compatible with different versions of
> Hive.
> We want to save the metadata of default constraint into properties of Hive
> table, and then we restore metadata from the properties after client gets
> newest metadata.
> The implement is the same as other metadata (e.g.
> partition,bucket,statistics).
> Because default constraint is part of column, so I think could reuse the
> metadata of StructField. The default constraint will cached by metadata of
> StructField.
> This is a big work, wo I want to split this work into some sub tasks, as
> follows:
>
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