Mark Ressler created SPARK-34805:
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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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