[ https://issues.apache.org/jira/browse/SPARK-46349?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Majid Hajiheidari updated SPARK-46349: -------------------------------------- Labels: (was: pull-request-available) > Prevent SortOrder from Accepting Nested SortOrder Instances > ----------------------------------------------------------- > > Key: SPARK-46349 > URL: https://issues.apache.org/jira/browse/SPARK-46349 > Project: Spark > Issue Type: Bug > Components: PySpark, SQL > Affects Versions: 4.0.0 > Reporter: Majid Hajiheidari > Priority: Minor > > Hello everyone, > This is my first contribution to the project. I welcome any feedback and > edits to improve this pull request.Currently, it's possible to create > redundant sort expressions in both Scala and Python APIs, leading to > potentially incorrect and confusing SQL statements. For example: > Scala: > {code:java} > spark.range(10).orderBy($"id".desc.asc).show(){code} > Python: > {code:java} > spark.range(10).orderBy(f.desc('id'), ascending=False).show(){code} > > Such usage generates SQL like order by id DESC NULLS LAST DESC NULLS LAST, > causing non-descriptive error messages. > I created a pull request for handling the issue. This pull request introduces > a constraint in the SortOrder class, ensuring that its child cannot be > another instance of SortOrder. This change prevents the creation of nested, > redundant sort expressions. > Additionally, in PySpark's DataFrame.sort, there's an ascending keyword > argument that could conflict with already sorted expressions. I've added an > exception handler to generate more descriptive error messages in such cases. > A test case has been added to verify that no double ordering occurs after > this fix. > > I look forward to your feedback and thank you for considering this > contribution. -- This message was sent by Atlassian Jira (v8.20.10#820010) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org