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https://issues.apache.org/jira/browse/SPARK-61244?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Hyukjin Kwon reassigned SPARK-61244:
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Assignee: Hyukjin Kwon
> Convert pandas frames with MultiIndex or CategoricalIndex labels through
> Arrow, as PySpark does
> -----------------------------------------------------------------------------------------------
>
> Key: SPARK-61244
> URL: https://issues.apache.org/jira/browse/SPARK-61244
> Project: Spark
> Issue Type: Bug
> Components: Connect
> Affects Versions: connect-rust-4.3.0
> Reporter: Hyukjin Kwon
> Assignee: Hyukjin Kwon
> Priority: Major
> Labels: pull-request-available
> Fix For: connect-rust-4.3.0
>
>
> The Python drop-in's createDataFrame of a pandas frame whose column labels
> are a plain MultiIndex or CategoricalIndex takes the native row path, which
> converts its cells differently from PySpark.
> A list of naive datetimes becomes array<timestamp> (the session time zone),
> not array<timestamp_ntz>: under Asia/Seoul, datetime(2020, 1, 2, 3) reads
> back as 12:00.
> A list of Decimals takes decimal(38,s) instead of the smallest precision, and
> a dict cell of mixed value types fails with "Type mismatch in row data"
> (PySpark gives a struct).
> PySpark converts these frames with Arrow, as frames with default labels
> already do; the Row scan of object columns on the row path also becomes cheap.
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