Description
Running test_parity_dataframe DataFrameParityTests.test_unpivot_negative fails as below:
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 "