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https://issues.apache.org/jira/browse/SPARK-23173?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16333855#comment-16333855
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Hyukjin Kwon commented on SPARK-23173:
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I believe this one is related with SPARK-17763. My first try was 2 (roughly 1.5
years ago).
The root cause seems the same - I just double checked the Jackson parsers
produce {{null}} regardless of the nullability.
Just FYI, there was a related discussion in SPARK-16472 too. If I understood
correctly, seems the guys roughly rather prefer to leave it as nullable rather
than failure during runtime.
So, +1 for 1. to me given the past discussion and It seems simplest and less
invasion.
cc [~cloud_fan] too who was in the discussion of SPARK-16472.
> 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
>
> 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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