You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "Hyukjin Kwon (Jira)" <ji...@apache.org> on 2025/08/26 22:59:00 UTC
[jira] [Assigned] (SPARK-53330) Fix Arrow UDF support for DayTimeIntervalType with bounds != start-end
[ https://issues.apache.org/jira/browse/SPARK-53330?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Hyukjin Kwon reassigned SPARK-53330:
------------------------------------
Assignee: Ben Hurdelhey
> Fix Arrow UDF support for DayTimeIntervalType with bounds != start-end
> ----------------------------------------------------------------------
>
> Key: SPARK-53330
> URL: https://issues.apache.org/jira/browse/SPARK-53330
> Project: Spark
> Issue Type: Bug
> Components: PySpark
> Affects Versions: 4.1.0
> Reporter: Ben Hurdelhey
> Assignee: Ben Hurdelhey
> Priority: Major
> Labels: pull-request-available
>
> When a pyspark udf (useArrow=true) returns interval type data, it currently errors with below error when the resultType (e.g., DayTimeIntervalType) has begin/end that don't span the maximum range.
> org.apache.spark.SparkException: [ARROW_TYPE_MISMATCH] Invalid schema from pandas_udf(): expected DayTimeIntervalType(1,3), got DayTimeIntervalType(0,3). SQLSTATE: 42K0G
>
> Repro:
> ```
> from pyspark.sql.types import DayTimeIntervalType
> from pyspark.sql.functions import udf
>
> @udf(useArrow=True, returnType=DayTimeIntervalType(0, 3)) # this works
> def return_interval1(x):
> return x
> @udf(useArrow=True, returnType=DayTimeIntervalType(1, 3)) # this fails
> def return_interval2(x):
> return x
> spark.sql("SELECT INTERVAL '1 10:30:45.123' DAY TO SECOND as value").select(return_interval2("value")).collect()
> ```
>
> YearToMonthIntervalType is not supported in arrow udfs, so that it's currently not a concern.
--
This message was sent by Atlassian Jira
(v8.20.10#820010)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org