[
https://issues.apache.org/jira/browse/SPARK-42751?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
IonK updated SPARK-42751:
-------------------------
Description:
When you use the str.findall accessor method on a ps.series and you're passing
a regex pattern that will return match groups, it will return a pyarrow data
error.
In pandas the result is this:
{code:java}
df.to_pandas()[col].str.findall(regex_pattern, flags=re.IGNORECASE)
returns
[("value", , , , )],
[("value", , , , )],
[(, , ,"value", )]{code}
In pyspark.pandas the result is:
{code:java}
org.apache.spark.api.python.PythonException: 'pyarrow.lib.ArrowTypeError:
Expected bytes, got a 'tuple' object'.{code}
My temporary workaround is using
{code:java}
df.apply(lambda x: re.findall(regex_pattern, x, flags=re.IGNORECASE)[0]{code}
was:
When you use the str.findall accessor method on a ps.series and you're passing
a regex pattern that will return match groups, it will return a pyarrow data
error.
In pandas the result is this:
{code:java}
df.to_pandas()[col].str.findall(regex_pattern, flags=re.IGNORECASE)
returns
[("value", , , , )],
[("value", , , , )],
[(, , ,value , )]{code}
In pyspark.pandas the result is:
{code:java}
org.apache.spark.api.python.PythonException: 'pyarrow.lib.ArrowTypeError:
Expected bytes, got a 'tuple' object'.{code}
My temporary workaround is using
{code:java}
df.apply(lambda x: re.findall(regex_pattern, x, flags=re.IGNORECASE)[0]{code}
> Pyspark.pandas.series.str.findall can't handle tuples that are returned by
> regex
> --------------------------------------------------------------------------------
>
> Key: SPARK-42751
> URL: https://issues.apache.org/jira/browse/SPARK-42751
> Project: Spark
> Issue Type: Bug
> Components: Pandas API on Spark
> Affects Versions: 3.3.2
> Reporter: IonK
> Priority: Major
>
> When you use the str.findall accessor method on a ps.series and you're
> passing a regex pattern that will return match groups, it will return a
> pyarrow data error.
> In pandas the result is this:
> {code:java}
> df.to_pandas()[col].str.findall(regex_pattern, flags=re.IGNORECASE)
> returns
> [("value", , , , )],
> [("value", , , , )],
> [(, , ,"value", )]{code}
>
> In pyspark.pandas the result is:
> {code:java}
> org.apache.spark.api.python.PythonException: 'pyarrow.lib.ArrowTypeError:
> Expected bytes, got a 'tuple' object'.{code}
>
> My temporary workaround is using
> {code:java}
> df.apply(lambda x: re.findall(regex_pattern, x, flags=re.IGNORECASE)[0]{code}
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