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Posted to issues@spark.apache.org by "Apache Spark (JIRA)" <ji...@apache.org> on 2018/02/28 12:52:01 UTC
[jira] [Commented] (SPARK-23173) from_json can produce nulls for
fields which are marked as non-nullable
[ https://issues.apache.org/jira/browse/SPARK-23173?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16380250#comment-16380250 ]
Apache Spark commented on SPARK-23173:
--------------------------------------
User 'mswit-databricks' has created a pull request for this issue:
https://github.com/apache/spark/pull/20694
> 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
> 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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