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https://issues.apache.org/jira/browse/SPARK-17939?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Michael Armbrust updated SPARK-17939:
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Target Version/s: 2.2.0 (was: 2.1.0)
> Spark-SQL Nullability: Optimizations vs. Enforcement Clarification
> ------------------------------------------------------------------
>
> Key: SPARK-17939
> URL: https://issues.apache.org/jira/browse/SPARK-17939
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 2.0.0
> Reporter: Aleksander Eskilson
> Priority: Critical
>
> The notion of Nullability of of StructFields in DataFrames and Datasets
> creates some confusion. As has been pointed out previously [1], Nullability
> is a hint to the Catalyst optimizer, and is not meant to be a type-level
> enforcement. Allowing null fields can also help the reader successfully parse
> certain types of more loosely-typed data, like JSON and CSV, where null
> values are common, rather than just failing.
> There's already been some movement to clarify the meaning of Nullable in the
> API, but also some requests for a (perhaps completely separate) type-level
> implementation of Nullable that can act as an enforcement contract.
> This bug is logged here to discuss and clarify this issue.
> [1] -
> [https://issues.apache.org/jira/browse/SPARK-11319|https://issues.apache.org/jira/browse/SPARK-11319?focusedCommentId=15014535&page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel#comment-15014535]
> [2] - https://github.com/apache/spark/pull/11785
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