[jira] [Resolved] (SPARK-38353) Instrument __enter__ and __exit__ magic methods for pandas API on Spark

["Hyukjin Kwon (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-38353?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Hyukjin Kwon resolved SPARK-38353.
----------------------------------
    Fix Version/s: 3.3.0
                   3.2.2
       Resolution: Fixed

Issue resolved by pull request 35687
[https://github.com/apache/spark/pull/35687]

> Instrument __enter__ and __exit__ magic methods for pandas API on Spark
> -----------------------------------------------------------------------
>
>                 Key: SPARK-38353
>                 URL: https://issues.apache.org/jira/browse/SPARK-38353
>             Project: Spark
>          Issue Type: Improvement
>          Components: PySpark
>    Affects Versions: 3.2.1
>            Reporter: Yihong He
>            Priority: Minor
>             Fix For: 3.3.0, 3.2.2
>
>
> Create the ticket since instrumenting _{_}enter{_}_ and _{_}exit{_}_ magic methods for pandas API on Spark can help improve accuracy of the usage data. Besides, we are interested in extending the pandas-on-Spark usage logger to other PySpark modules in the future so it will help improve accuracy of usage data of other PySpark modules.
> For example, for the following code:
>  
> {code:java}
> pdf = pd.DataFrame(
>     [(0.2, 0.3), (0.0, 0.6), (0.6, 0.0), (0.2, 0.1)], columns=["dogs", "cats"]
> )
> psdf = ps.from_pandas(pdf)
> with psdf.spark.cache() as cached_df:
>     self.assert_eq(isinstance(cached_df, CachedDataFrame), True)
>     self.assert_eq(
>         repr(cached_df.spark.storage_level), repr(StorageLevel(True, True, False, True))
>     ){code}
>  
> pandas-on-Spark usage logger records the internal call [self.spark.unpersist()|https://github.com/apache/spark/blob/master/python/pyspark/pandas/frame.py#L12518] since __enter__ and __exit__ methods of [CachedDataFrame|https://github.com/apache/spark/blob/master/python/pyspark/pandas/frame.py#L12492] are not instrumented.



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