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Posted to issues@spark.apache.org by "Pen Xiao (JIRA)" <ji...@apache.org> on 2017/06/05 08:34:04 UTC
[jira] [Created] (SPARK-20983) AnalysisException when joining data
frames derived from the same duplicates-dropped one.
Pen Xiao created SPARK-20983:
--------------------------------
Summary: AnalysisException when joining data frames derived from the same duplicates-dropped one.
Key: SPARK-20983
URL: https://issues.apache.org/jira/browse/SPARK-20983
Project: Spark
Issue Type: Bug
Components: SQL
Affects Versions: 2.1.0
Reporter: Pen Xiao
reproduce steps:
val df = sc.parallelize(Array((1,1,1),(1,1,2),(1,2,1))).toDF("c1","c2","c3").dropDuplicates("c1", "c2")
val df1 = df.select("c1", "c2")
val df2 = df.withColumn("c4", udf((c3:Int)=>c3 + 1).apply($"c3")).select("c1", "c2", "c4")
df1.join(df2, Array("c1", "c2")).show
get Error as following:
org.apache.spark.sql.AnalysisException: resolved attribute(s) c3#197 missing from c1#195,c2#196,c3#175 in operator !Project [c1#195, c2#196, c3#197];;
Project [c1#173, c2#174, c4#185]
+- Join Inner, ((c1#173 = c1#195) && (c2#174 = c2#196))
:- Project [c1#173, c2#174]
: +- Project [c1#173, c2#174, c3#175]
: +- Aggregate [c1#173, c2#174], [c1#173, c2#174, first(c3#175, false) AS c3#175]
: +- Project [c1#173, c2#174, c3#175]
: +- Project [_1#169 AS c1#173, _2#170 AS c2#174, _3#171 AS c3#175]
: +- SerializeFromObject [assertnotnull(input[0, scala.Tuple3, true], top level Product input object)._1 AS _1#169, assertnotnull(input[0, scala.Tuple3, true], top level Product input object)._2 AS _2#170, assertnotnull(input[0, scala.Tuple3, true], top level Product input object)._3 AS _3#171]
: +- ExternalRDD [obj#168]
+- Project [c1#195, c2#196, c4#185]
+- Project [c1#195, c2#196, c3#197, if (isnull(c3#197)) null else if (isnull(c3#197)) null else if (isnull(c3#197)) null else UDF(c3#197) AS c4#185]
+- !Project [c1#195, c2#196, c3#197]
+- Aggregate [c1#195, c2#196], [c1#195, c2#196, first(c3#197, false) AS c3#175]
+- Project [c1#195, c2#196, c3#197]
+- Project [_1#169 AS c1#195, _2#170 AS c2#196, _3#171 AS c3#197]
+- SerializeFromObject [assertnotnull(input[0, scala.Tuple3, true], top level Product input object)._1 AS _1#169, assertnotnull(input[0, scala.Tuple3, true], top level Product input object)._2 AS _2#170, assertnotnull(input[0, scala.Tuple3, true], top level Product input object)._3 AS _3#171]
+- ExternalRDD [obj#168]
at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$class.failAnalysis(CheckAnalysis.scala:40)
at org.apache.spark.sql.catalyst.analysis.Analyzer.failAnalysis(Analyzer.scala:57)
at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1.apply(CheckAnalysis.scala:337)
at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1.apply(CheckAnalysis.scala:67)
at org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:128)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$foreachUp$1.apply(TreeNode.scala:127)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$foreachUp$1.apply(TreeNode.scala:127)
at scala.collection.immutable.List.foreach(List.scala:381)
at org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:127)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$foreachUp$1.apply(TreeNode.scala:127)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$foreachUp$1.apply(TreeNode.scala:127)
at scala.collection.immutable.List.foreach(List.scala:381)
at org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:127)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$foreachUp$1.apply(TreeNode.scala:127)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$foreachUp$1.apply(TreeNode.scala:127)
at scala.collection.immutable.List.foreach(List.scala:381)
at org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:127)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$foreachUp$1.apply(TreeNode.scala:127)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$foreachUp$1.apply(TreeNode.scala:127)
at scala.collection.immutable.List.foreach(List.scala:381)
at org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:127)
at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$class.checkAnalysis(CheckAnalysis.scala:67)
at org.apache.spark.sql.catalyst.analysis.Analyzer.checkAnalysis(Analyzer.scala:57)
at org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:48)
at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:63)
at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$withPlan(Dataset.scala:2822)
at org.apache.spark.sql.Dataset.join(Dataset.scala:775)
at org.apache.spark.sql.Dataset.join(Dataset.scala:748)
... 48 elided
What is strange is that the code works fine as following:
val df = sc.parallelize(Array((1,1,1),(1,1,2),(1,2,1))).toDF("c1","c2","c3")
val df1 = df.select("c1", "c2")
val df2 = df.withColumn("c4", udf((c3:Int)=>c3 + 1).apply($"c3")).select("c1", "c2", "c4")
df1.join(df2, Array("c1", "c2")).show
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