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https://issues.apache.org/jira/browse/SPARK-16938?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15943382#comment-15943382
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Michel Lemay commented on SPARK-16938:
--------------------------------------
I just stumbled upon a similar issue with 'union' on two dataframes.. Anybody
still working on this issue and if not, could it be revived?
> Cannot resolve column name after a join
> ---------------------------------------
>
> Key: SPARK-16938
> URL: https://issues.apache.org/jira/browse/SPARK-16938
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 2.0.0
> Reporter: Mathieu D
> Priority: Minor
>
> Found a change of behavior on spark-2.0.0, which breaks a query in our code
> base.
> The following works on previous spark versions, 1.6.1 up to 2.0.0-preview :
> {code}
> val dfa = Seq((1, 2), (2, 3)).toDF("id", "a").alias("dfa")
> val dfb = Seq((1, 0), (1, 1)).toDF("id", "b").alias("dfb")
> dfa.join(dfb, dfa("id") === dfb("id")).dropDuplicates(Array("dfa.id",
> "dfb.id"))
> {code}
> but fails with spark-2.0.0 with the exception :
> {code}
> Cannot resolve column name "dfa.id" among (id, a, id, b);
> org.apache.spark.sql.AnalysisException: Cannot resolve column name "dfa.id"
> among (id, a, id, b);
> at
> org.apache.spark.sql.Dataset$$anonfun$dropDuplicates$1$$anonfun$36$$anonfun$apply$12.apply(Dataset.scala:1819)
> at
> org.apache.spark.sql.Dataset$$anonfun$dropDuplicates$1$$anonfun$36$$anonfun$apply$12.apply(Dataset.scala:1819)
> at scala.Option.getOrElse(Option.scala:121)
> at
> org.apache.spark.sql.Dataset$$anonfun$dropDuplicates$1$$anonfun$36.apply(Dataset.scala:1818)
> at
> org.apache.spark.sql.Dataset$$anonfun$dropDuplicates$1$$anonfun$36.apply(Dataset.scala:1817)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:245)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:245)
> at
> scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
> at scala.collection.mutable.WrappedArray.foreach(WrappedArray.scala:35)
> at scala.collection.TraversableLike$class.map(TraversableLike.scala:245)
> at scala.collection.AbstractTraversable.map(Traversable.scala:104)
> at
> org.apache.spark.sql.Dataset$$anonfun$dropDuplicates$1.apply(Dataset.scala:1817)
> at
> org.apache.spark.sql.Dataset$$anonfun$dropDuplicates$1.apply(Dataset.scala:1814)
> at org.apache.spark.sql.Dataset.withTypedPlan(Dataset.scala:2594)
> at org.apache.spark.sql.Dataset.dropDuplicates(Dataset.scala:1814)
> at org.apache.spark.sql.Dataset.dropDuplicates(Dataset.scala:1840)
> ...
> {code}
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