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Dongjoon Hyun commented on SPARK-30065: --------------------------------------- This is backported to `branch-2.4` via [https://github.com/apache/spark/pull/27411] . > Unable to drop na with duplicate columns > ---------------------------------------- > > Key: SPARK-30065 > URL: https://issues.apache.org/jira/browse/SPARK-30065 > Project: Spark > Issue Type: Bug > Components: SQL > Affects Versions: 2.0.2, 2.1.3, 2.2.3, 2.3.4, 2.4.4, 3.0.0 > Reporter: Terry Kim > Assignee: Terry Kim > Priority: Major > Fix For: 2.4.5, 3.0.0 > > > Trying to drop rows with null values fails even when no columns are > specified. This should be allowed: > {code:java} > scala> val left = Seq(("1", null), ("3", "4")).toDF("col1", "col2") > left: org.apache.spark.sql.DataFrame = [col1: string, col2: string] > scala> val right = Seq(("1", "2"), ("3", null)).toDF("col1", "col2") > right: org.apache.spark.sql.DataFrame = [col1: string, col2: string] > scala> val df = left.join(right, Seq("col1")) > df: org.apache.spark.sql.DataFrame = [col1: string, col2: string ... 1 more > field] > scala> df.show > +----+----+----+ > |col1|col2|col2| > +----+----+----+ > | 1|null| 2| > | 3| 4|null| > +----+----+----+ > scala> df.na.drop("any") > org.apache.spark.sql.AnalysisException: Reference 'col2' is ambiguous, could > be: col2, col2.; > at > org.apache.spark.sql.catalyst.expressions.package$AttributeSeq.resolve(package.scala:240) > {code} -- This message was sent by Atlassian Jira (v8.3.4#803005) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org