You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "Michael Armbrust (JIRA)" <ji...@apache.org> on 2018/02/15 19:35:00 UTC
[jira] [Updated] (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:all-tabpanel ]
Michael Armbrust updated SPARK-23173:
-------------------------------------
Labels: release-notes (was: )
> 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]
--
This message was sent by Atlassian JIRA
(v7.6.3#76005)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org