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From "Apache Spark (JIRA)" <j...@apache.org>
Subject [jira] [Assigned] (SPARK-23173) from_json can produce nulls for fields which are marked as non-nullable
Date Wed, 28 Feb 2018 12:52:01 GMT

     [ https://issues.apache.org/jira/browse/SPARK-23173?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Apache Spark reassigned SPARK-23173:
------------------------------------

    Assignee: Apache Spark

> from_json can produce nulls for fields which are marked as non-nullable
> -----------------------------------------------------------------------
>
>                 Key: SPARK-23173
>                 URL: https://issues.apache.org/jira/browse/SPARK-23173
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>    Affects Versions: 2.2.1
>            Reporter: Herman van Hovell
>            Assignee: Apache Spark
>            Priority: Major
>              Labels: release-notes
>
> The {{from_json}} function uses a schema to convert a string into a Spark SQL struct.
This schema can contain non-nullable fields. The underlying {{JsonToStructs}} expression does
not check if a resulting struct respects the nullability of the schema. This leads to very
weird problems in consuming expressions. In our case parquet writing would produce an illegal
parquet file.
> There are roughly solutions here:
>  # Assume that each field in schema passed to {{from_json}} is nullable, and ignore
the nullability information set in the passed schema.
>  # Validate the object during runtime, and fail execution if the data is null where we
are not expecting this.
> I currently am slightly in favor of option 1, since this is the more performant option
and a lot easier to do.
> WDYT? cc [~rxin] [~marmbrus] [~hyukjin.kwon] [~brkyvz]



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