[jira] [Updated] (SPARK-34805) PySpark loses metadata in DataFrame fields when selecting nested columns

2021-03-19 Thread Mark Ressler (Jira) 


 [ 
https://issues.apache.org/jira/browse/SPARK-34805?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Mark Ressler updated SPARK-34805:
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Attachment: jsonMetadataTest.py

> PySpark loses metadata in DataFrame fields when selecting nested columns
> 
>
> Key: SPARK-34805
> URL: https://issues.apache.org/jira/browse/SPARK-34805
> Project: Spark
>  Issue Type: Bug
>  Components: PySpark
>Affects Versions: 3.0.1, 3.1.1
>Reporter: Mark Ressler
>Priority: Major
> Attachments: jsonMetadataTest.py
>
>
> For a DataFrame schema with nested StructTypes, where metadata is set for 
> fields in the schema, that metadata is lost when a DataFrame selects nested 
> fields.  For example, suppose
> {code:java}
> df.schema.fields[0].dataType.fields[0].metadata
> {code}
> returns a non-empty dictionary, then
> {code:java}
> df.select('Field0.SubField0').schema.fields[0].metadata{code}
> returns an empty dictionary, where "Field0" is the name of the first field in 
> the DataFrame and "SubField0" is the name of the first nested field under 
> "Field0".
>  



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[jira] [Created] (SPARK-34805) PySpark loses metadata in DataFrame fields when selecting nested columns

2021-03-19 Thread Mark Ressler (Jira) 
Mark Ressler created SPARK-34805:


 Summary: PySpark loses metadata in DataFrame fields when selecting 
nested columns
 Key: SPARK-34805
 URL: https://issues.apache.org/jira/browse/SPARK-34805
 Project: Spark
  Issue Type: Bug
  Components: PySpark
Affects Versions: 3.1.1, 3.0.1
Reporter: Mark Ressler


For a DataFrame schema with nested StructTypes, where metadata is set for 
fields in the schema, that metadata is lost when a DataFrame selects nested 
fields.  For example, suppose
{code:java}
df.schema.fields[0].dataType.fields[0].metadata
{code}
returns a non-empty dictionary, then
{code:java}
df.select('Field0.SubField0').schema.fields[0].metadata{code}
returns an empty dictionary, where "Field0" is the name of the first field in 
the DataFrame and "SubField0" is the name of the first nested field under 
"Field0".

 



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