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Posted to issues@spark.apache.org by "Ted Chester Jenks (Jira)" <ji...@apache.org> on 2023/06/22 12:06:00 UTC
[jira] [Updated] (SPARK-44142) Utility to convert python types to spark types compares Python "type" object rather than user's "tpe" for categorical data types
[ https://issues.apache.org/jira/browse/SPARK-44142?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Ted Chester Jenks updated SPARK-44142:
--------------------------------------
Description:
In the typehints utility that converts python types to spark types, the line:
{code:java}
# categorical types
elif isinstance(tpe, CategoricalDtype) or (isinstance(tpe, str) and type == "category"):
return types.LongType() {code}
uses Python's 'type' keyword in the comparison. Hence, it will always be false. Here, the user's type is actually stored in the variable 'tpe'.
See line [here|https://github.com/apache/spark/blob/1b4048bf62dddae7d324c4b12aa409a1bd456dc5/python/pyspark/pandas/typedef/typehints.py#LL217C7-L217C7].
was:
In the typehints utility that converts python types to spark types, the line:
{code:java}
# categorical types
elif isinstance(tpe, CategoricalDtype) or (isinstance(tpe, str) and type == "category"):
return types.LongType() {code}
uses Python's 'type' keyword in the comparison. Hence, it will always be false. Here, the user's type is actually stored in the variable 'tpe'.
See line [here|https://github.com/apache/spark/blob/1b4048bf62dddae7d324c4b12aa409a1bd456dc5/python/pyspark/pandas/typedef/typehints.py#LL217C7-L217C7].
> Utility to convert python types to spark types compares Python "type" object rather than user's "tpe" for categorical data types
> --------------------------------------------------------------------------------------------------------------------------------
>
> Key: SPARK-44142
> URL: https://issues.apache.org/jira/browse/SPARK-44142
> Project: Spark
> Issue Type: Bug
> Components: PySpark
> Affects Versions: 3.4.0
> Reporter: Ted Chester Jenks
> Priority: Major
>
> In the typehints utility that converts python types to spark types, the line:
> {code:java}
> # categorical types
> elif isinstance(tpe, CategoricalDtype) or (isinstance(tpe, str) and type == "category"):
> return types.LongType() {code}
> uses Python's 'type' keyword in the comparison. Hence, it will always be false. Here, the user's type is actually stored in the variable 'tpe'.
>
>
> See line [here|https://github.com/apache/spark/blob/1b4048bf62dddae7d324c4b12aa409a1bd456dc5/python/pyspark/pandas/typedef/typehints.py#LL217C7-L217C7].
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