[
https://issues.apache.org/jira/browse/SPARK-61140?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Hyukjin Kwon updated SPARK-61140:
---------------------------------
Fix Version/s: connect-rust-4.3.0
> Send the renames of DataFrame.withColumnsRenamed in their order, in the Rust
> core and the Python client, as PySpark does
> ------------------------------------------------------------------------------------------------------------------------
>
> Key: SPARK-61140
> URL: https://issues.apache.org/jira/browse/SPARK-61140
> Project: Spark
> Issue Type: Bug
> Components: Connect
> Affects Versions: connect-rust-4.3.0
> Reporter: Hyukjin Kwon
> Priority: Major
> Fix For: connect-rust-4.3.0
>
>
> PySpark's DataFrame.withColumnsRenamed sends its renames in the order of
> their dict (the repeated renames of WithColumnsRenamed), and the server
> applies them in that order. So df.withColumnsRenamed({"id": "a", "a": "b"})
> has the columns ["b"], and df.withColumnsRenamed({"a": "b", "id": "a"}) has
> ["a"].
> The Rust core of spark-connect-rust keeps the renames of a WithColumnsRenamed
> plan in a HashMap. So it sends them in the order of their hashes, not in the
> order given, and the columns of such renames depend on that order. Apache
> Spark's test_ordering_of_with_columns_renamed fails on the client: ['a'] !=
> ['b'].
> The core should keep the renames in their order, and send them in it, as
> PySpark does.
--
This message was sent by Atlassian Jira
(v10.3.26#10030026)
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
