You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "Rafik (JIRA)" <ji...@apache.org> on 2019/04/22 11:51:00 UTC
[jira] [Comment Edited] (SPARK-10925) Exception when joining
DataFrames
[ https://issues.apache.org/jira/browse/SPARK-10925?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16823045#comment-16823045 ]
Rafik edited comment on SPARK-10925 at 4/22/19 11:50 AM:
---------------------------------------------------------
I managed to solve this by renaming the column after group by to something temporary, and then renaming it again to the original column, then joining
was (Author: rafikamir):
I managed to solve this by renaming the column after group by to something temporary, and then renaming it again to the original column
> 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
> Priority: Major
> Attachments: Photo 05-10-2015 14 31 16.jpg, TestCase.scala, 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
--
This message was sent by Atlassian JIRA
(v7.6.3#76005)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org