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https://issues.apache.org/jira/browse/SPARK-27943?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Reece Robinson updated SPARK-27943:
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Attachment: Screenshot 2023-10-04 at 11.11.28 AM.png
> 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: 3.0.0
> Reporter: Jiaan Geng
> Priority: Major
> Attachments: Screenshot 2023-10-04 at 11.11.28 AM.png
>
>
>
> *Background*
> 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.
> *Design*
> 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 three points to
> pay attention to in design:
> _First_, Spark SQL should reduce coupling with Hive.
> _Second_, default constraint could compatible with different versions of Hive.
> _Thrid_, Which expression of default constraint should Spark SQL support? I
> think should support `literal`, `current_date()`, `current_timestamp()`.
> Maybe other expression should also supported, like `Cast(1 as float)`, `1 +
> 2` and so on.
> 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.
>
> *Tasks*
> This is a big work, wo I want to split this work into some sub tasks, as
> follows:
>
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