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Posted to issues@spark.apache.org by "Apache Spark (Jira)" <ji...@apache.org> on 2023/02/23 03:08:00 UTC
[jira] [Assigned] (SPARK-42444) DataFrame.drop should handle multi columns properly
[ https://issues.apache.org/jira/browse/SPARK-42444?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Apache Spark reassigned SPARK-42444:
------------------------------------
Assignee: Apache Spark
> DataFrame.drop should handle multi columns properly
> ---------------------------------------------------
>
> Key: SPARK-42444
> URL: https://issues.apache.org/jira/browse/SPARK-42444
> Project: Spark
> Issue Type: Bug
> Components: PySpark
> Affects Versions: 3.4.0
> Reporter: Ruifeng Zheng
> Assignee: Apache Spark
> Priority: Blocker
>
> {code:java}
> from pyspark.sql import Row
> df1 = spark.createDataFrame([(14, "Tom"), (23, "Alice"), (16, "Bob")], ["age", "name"])
> df2 = spark.createDataFrame([Row(height=80, name="Tom"), Row(height=85, name="Bob")])
> df1.join(df2, df1.name == df2.name, 'inner').drop('name', 'age').show()
> {code}
> This works in 3.3
> {code:java}
> +------+
> |height|
> +------+
> | 85|
> | 80|
> +------+
> {code}
> but fails in 3.4
> {code:java}
> ---------------------------------------------------------------------------
> AnalysisException Traceback (most recent call last)
> Cell In[1], line 4
> 2 df1 = spark.createDataFrame([(14, "Tom"), (23, "Alice"), (16, "Bob")], ["age", "name"])
> 3 df2 = spark.createDataFrame([Row(height=80, name="Tom"), Row(height=85, name="Bob")])
> ----> 4 df1.join(df2, df1.name == df2.name, 'inner').drop('name', 'age').show()
> File ~/Dev/spark/python/pyspark/sql/dataframe.py:4913, in DataFrame.drop(self, *cols)
> 4911 jcols = [_to_java_column(c) for c in cols]
> 4912 first_column, *remaining_columns = jcols
> -> 4913 jdf = self._jdf.drop(first_column, self._jseq(remaining_columns))
> 4915 return DataFrame(jdf, self.sparkSession)
> File ~/Dev/spark/python/lib/py4j-0.10.9.7-src.zip/py4j/java_gateway.py:1322, in JavaMember.__call__(self, *args)
> 1316 command = proto.CALL_COMMAND_NAME +\
> 1317 self.command_header +\
> 1318 args_command +\
> 1319 proto.END_COMMAND_PART
> 1321 answer = self.gateway_client.send_command(command)
> -> 1322 return_value = get_return_value(
> 1323 answer, self.gateway_client, self.target_id, self.name)
> 1325 for temp_arg in temp_args:
> 1326 if hasattr(temp_arg, "_detach"):
> File ~/Dev/spark/python/pyspark/errors/exceptions/captured.py:159, in capture_sql_exception.<locals>.deco(*a, **kw)
> 155 converted = convert_exception(e.java_exception)
> 156 if not isinstance(converted, UnknownException):
> 157 # Hide where the exception came from that shows a non-Pythonic
> 158 # JVM exception message.
> --> 159 raise converted from None
> 160 else:
> 161 raise
> AnalysisException: [AMBIGUOUS_REFERENCE] Reference `name` is ambiguous, could be: [`name`, `name`].
> {code}
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