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https://issues.apache.org/jira/browse/SPARK-33952?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Marc de Lignie updated SPARK-33952:
-----------------------------------
Issue Type: Improvement (was: Task)
> Python-friendly dtypes for pyspark dataframes
> ---------------------------------------------
>
> Key: SPARK-33952
> URL: https://issues.apache.org/jira/browse/SPARK-33952
> Project: Spark
> Issue Type: Improvement
> Components: PySpark
> Affects Versions: 3.2.0
> Reporter: Marc de Lignie
> Priority: Minor
> Fix For: 3.2.0
>
>
> The pyspark.sql.DataFrame.dtypes attribute contains string representations of
> the column datatypes in terms of JVM datatypes. However, for a python user it
> is a significant mental step to translate these to the corresponding python
> types encountered in UDF's and collected dataframes. This holds in particular
> for nested composite datatypes (array, map and struct). It is proposed to
> provide python-friendly dtypes in pyspark (as an addition, not a replacement)
> in which array<>, map<> and struct<> are translated to [], {} and Row().
> Sample code, including tests, is available as [gist on
> github|https://gist.github.com/vtslab/81ded1a7af006100e00bf2a4a70a8147]. More
> explanation is provided at:
> [https://yaaics.blogspot.com/2020/12/python-friendly-dtypes-for-pyspark.html]
> If this proposal finds sufficient support, I can provide a PR.
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