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https://issues.apache.org/jira/browse/SPARK-10925?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14956367#comment-14956367
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Xiao Li edited comment on SPARK-10925 at 10/14/15 7:16 AM:
-----------------------------------------------------------

Also hit the same problem, but this is not related to UDF. Trying to narrow 
down the root cause of the analyzer internal. 


was (Author: smilegator):
Also hit the same problem. Trying to narrow down the root cause of the analyzer 
internal. 

> Exception when joining DataFrames
> ---------------------------------
>
>                 Key: SPARK-10925
>                 URL: https://issues.apache.org/jira/browse/SPARK-10925
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>    Affects Versions: 1.5.0, 1.5.1
>         Environment: Tested with Spark 1.5.0 and Spark 1.5.1
>            Reporter: Alexis Seigneurin
>         Attachments: Photo 05-10-2015 14 31 16.jpg, TestCase2.scala
>
>
> I get an exception when joining a DataFrame with another DataFrame. The 
> second DataFrame was created by performing an aggregation on the first 
> DataFrame.
> My complete workflow is:
> # read the DataFrame
> # apply an UDF on column "name"
> # apply an UDF on column "surname"
> # apply an UDF on column "birthDate"
> # aggregate on "name" and re-join with the DF
> # aggregate on "surname" and re-join with the DF
> If I remove one step, the process completes normally.
> Here is the exception:
> {code}
> Exception in thread "main" org.apache.spark.sql.AnalysisException: resolved 
> attribute(s) surname#20 missing from id#0,birthDate#3,name#10,surname#7 in 
> operator !Project [id#0,birthDate#3,name#10,surname#20,UDF(birthDate#3) AS 
> birthDate_cleaned#8];
>       at 
> org.apache.spark.sql.catalyst.analysis.CheckAnalysis$class.failAnalysis(CheckAnalysis.scala:37)
>       at 
> org.apache.spark.sql.catalyst.analysis.Analyzer.failAnalysis(Analyzer.scala:44)
>       at 
> org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1.apply(CheckAnalysis.scala:154)
>       at 
> org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1.apply(CheckAnalysis.scala:49)
>       at 
> org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:103)
>       at 
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$foreachUp$1.apply(TreeNode.scala:102)
>       at 
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$foreachUp$1.apply(TreeNode.scala:102)
>       at scala.collection.immutable.List.foreach(List.scala:318)
>       at 
> org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:102)
>       at 
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$foreachUp$1.apply(TreeNode.scala:102)
>       at 
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$foreachUp$1.apply(TreeNode.scala:102)
>       at scala.collection.immutable.List.foreach(List.scala:318)
>       at 
> org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:102)
>       at 
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$foreachUp$1.apply(TreeNode.scala:102)
>       at 
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$foreachUp$1.apply(TreeNode.scala:102)
>       at scala.collection.immutable.List.foreach(List.scala:318)
>       at 
> org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:102)
>       at 
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$foreachUp$1.apply(TreeNode.scala:102)
>       at 
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$foreachUp$1.apply(TreeNode.scala:102)
>       at scala.collection.immutable.List.foreach(List.scala:318)
>       at 
> org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:102)
>       at 
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$foreachUp$1.apply(TreeNode.scala:102)
>       at 
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$foreachUp$1.apply(TreeNode.scala:102)
>       at scala.collection.immutable.List.foreach(List.scala:318)
>       at 
> org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:102)
>       at 
> org.apache.spark.sql.catalyst.analysis.CheckAnalysis$class.checkAnalysis(CheckAnalysis.scala:49)
>       at 
> org.apache.spark.sql.catalyst.analysis.Analyzer.checkAnalysis(Analyzer.scala:44)
>       at 
> org.apache.spark.sql.SQLContext$QueryExecution.assertAnalyzed(SQLContext.scala:914)
>       at org.apache.spark.sql.DataFrame.<init>(DataFrame.scala:132)
>       at 
> org.apache.spark.sql.DataFrame.org$apache$spark$sql$DataFrame$$logicalPlanToDataFrame(DataFrame.scala:154)
>       at org.apache.spark.sql.DataFrame.join(DataFrame.scala:553)
>       at org.apache.spark.sql.DataFrame.join(DataFrame.scala:520)
>       at TestCase2$.main(TestCase2.scala:51)
>       at TestCase2.main(TestCase2.scala)
>       at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
>       at 
> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
>       at 
> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
>       at java.lang.reflect.Method.invoke(Method.java:497)
>       at com.intellij.rt.execution.application.AppMain.main(AppMain.java:140)
> {code}
> I'm attaching a test case that I tried with Spark 1.5.0 and 1.5.1. Please 
> note it used to work with version 1.4.1



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