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Posted to issues@spark.apache.org by "Hyukjin Kwon (Jira)" <ji...@apache.org> on 2023/01/10 09:28:00 UTC
[jira] [Updated] (SPARK-41963) Different exception message in DataFrame.unpivot
[ https://issues.apache.org/jira/browse/SPARK-41963?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Hyukjin Kwon updated SPARK-41963:
---------------------------------
Summary: Different exception message in DataFrame.unpivot (was: Different exception in DataFrame.unpivot)
> Different exception message in DataFrame.unpivot
> ------------------------------------------------
>
> Key: SPARK-41963
> URL: https://issues.apache.org/jira/browse/SPARK-41963
> Project: Spark
> Issue Type: Sub-task
> Components: Connect
> Affects Versions: 3.4.0
> Reporter: Hyukjin Kwon
> Priority: Major
>
> Running {{test_parity_dataframe DataFrameParityTests.test_unpivot_negative}} fails as below:
> {code}
> with self.subTest(desc="with no value columns"):
> for values in [[], ()]:
> with self.subTest(values=values):
> with self.assertRaisesRegex(
> Exception, # (AnalysisException, SparkConnectException)
> r".*\[UNPIVOT_REQUIRES_VALUE_COLUMNS] At least one value column "
> r"needs to be specified for UNPIVOT, all columns specified as ids.*",
> ):
> > df.unpivot("id", values, "var", "val").collect()
> E AssertionError: ".*\[UNPIVOT_REQUIRES_VALUE_COLUMNS] At least one value column needs to be specified for UNPIVOT, all columns specified as ids.*" does not match "[UNPIVOT_VALUE_DATA_TYPE_MISMATCH] Unpivot value columns must share a least common type, some types do not: ["BIGINT" (`int`), "DOUBLE" (`double`), "STRING" (`str`)]
> E Plan: 'Unpivot ArraySeq(id#2947L), List(List(int#2948L), List(double#2949), List(str#2950)), var, [val]
> E +- Project [id#2939L AS id#2947L, int#2940L AS int#2948L, double#2941 AS double#2949, str#2942 AS str#2950]
> E +- LocalRelation [id#2939L, int#2940L, double#2941, str#2942]
> E "
> {code}
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