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https://issues.apache.org/jira/browse/SPARK-60643?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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ASF GitHub Bot updated SPARK-60643:
-----------------------------------
Labels: pull-request-available (was: )
> pandas-on-Spark drop_duplicates cannot resolve a column name containing a dot
> -----------------------------------------------------------------------------
>
> Key: SPARK-60643
> URL: https://issues.apache.org/jira/browse/SPARK-60643
> Project: Spark
> Issue Type: Bug
> Components: Pandas API on Spark, PySpark
> Affects Versions: 4.2.0
> Environment: Platform: Ubuntu 24.04 Linux-6.17.0-29-generic x86_64
> Python: 3.11.17
> pyspark 4.2.0
> findspark 2.0.1
> pandas 3.0.6
> numpy 2.4.6
> Reporter: asddfl
> Priority: Critical
> Labels: pull-request-available
>
> Renaming a column from c0 to the literal name t0.c0 and calling
> drop_duplicates raises an unresolved-column error in the pandas API on Spark.
> Pandas returns the one-row DataFrame successfully.
> The error treats the dot as a qualifier separator instead of preserving the
> complete column name.
> {code:python}
> import pandas as pd
> from pyspark.sql import SparkSession
> import pyspark.pandas as ps
> t0 = pd.DataFrame({'c0': [1]})
> print("Pandas:", flush=True)
> result = t0.rename(columns={'c0': 't0.c0'}).drop_duplicates()
> print(result, flush=True)
> spark = (
> SparkSession.builder
> .master("local[2]")
> .config("spark.sql.ansi.enabled", "false")
> .config("spark.sql.shuffle.partitions", "2")
> .getOrCreate()
> )
> t0 = ps.DataFrame({'c0': [1]})
> print("PySpark Pandas:", flush=True)
> result = t0.rename(columns={'c0': 't0.c0'}).drop_duplicates()
> print(result, flush=True)
> spark.stop()
> {code}
> {code:bash}
> Pandas:
> t0.c0
> 0 1
> PySpark Pandas:
> Traceback (most recent call last):
> File "/test.py", line 24, in <module>
> result = t0.rename(columns={'c0': 't0.c0'}).drop_duplicates()
> ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
> File
> "/opt/conda/envs/lib/python3.11/site-packages/pyspark/pandas/frame.py", line
> 10311, in drop_duplicates
> sdf, column = self._mark_duplicates(subset, keep)
> ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
> File
> "/opt/conda/envs/lib/python3.11/site-packages/pyspark/pandas/frame.py", line
> 5155, in _mark_duplicates
> sdf = sdf.withColumn(column, F.row_number().over(window) > 1)
> ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
> File
> "/opt/conda/envs/lib/python3.11/site-packages/pyspark/sql/classic/dataframe.py",
> line 1801, in withColumn
> return DataFrame(self._jdf.withColumn(colName, col._jc),
> self.sparkSession)
> ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
> File "/opt/conda/envs/lib/python3.11/site-packages/py4j/java_gateway.py",
> line 1362, in __call__
> return_value = get_return_value(
> ^^^^^^^^^^^^^^^^^
> File
> "/opt/conda/envs/lib/python3.11/site-packages/pyspark/errors/exceptions/captured.py",
> line 257, in deco
> raise converted from None
> pyspark.errors.exceptions.captured.AnalysisException:
> [UNRESOLVED_COLUMN.WITH_SUGGESTION] A column, variable, or function parameter
> with name `t0`.`c0` cannot be resolved. Did you mean one of the following?
> [`t0.c0`, `__index_level_0__`, `__natural_order__`]. SQLSTATE: 42703;
> 'Project [__index_level_0__#0L, t0.c0#3L, __natural_order__#2L,
> '`>`(row_number() windowspecdefinition('t0.c0, __natural_order__#2L ASC NULLS
> FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())),
> 1) AS __duplicated__#4]
> +- Project [__index_level_0__#0L, c0#1L AS t0.c0#3L, __natural_order__#2L]
> +- Project [__index_level_0__#0L, c0#1L, monotonically_increasing_id() AS
> __natural_order__#2L]
> +- LocalRelation [__index_level_0__#0L, c0#1L]
> {code}
> *Expected behavior*
> Return one row with value 1 under the literal column name t0.c0, matching
> Pandas.
> *Actual behavior*
> The call raises AnalysisException with condition
> UNRESOLVED_COLUMN.WITH_SUGGESTION and SQLSTATE 42703. Spark attempts to
> resolve `t0`.`c0`, while its suggestions include the existing literal column
> `t0.c0`.
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