Aleksander Eskilson created SPARK-17939:

             Summary: Spark-SQL Nullability: Optimizations vs. Enforcement 
                 Key: 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.

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