[ 
https://issues.apache.org/jira/browse/SPARK-17908?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15572278#comment-15572278
 ] 

Harish commented on SPARK-17908:
--------------------------------

Traceback (most recent call last):
  File 
"/home/hpcuser/iri/spark-2.0.1-bin-hadoop2.7/python/lib/pyspark.zip/pyspark/sql/utils.py",
 line 63, in deco
  File 
"/home/hpcuser/iri/spark-2.0.1-bin-hadoop2.7/python/lib/py4j-0.10.3-src.zip/py4j/protocol.py",
 line 319, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling o376.select.
: org.apache.spark.sql.AnalysisException: cannot resolve '`key2`' given input 
columns: [columns];
        at 
org.apache.spark.sql.catalyst.analysis.package$AnalysisErrorAt.failAnalysis(package.scala:42)
        at 
org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1$$anonfun$apply$2.applyOrElse(CheckAnalysis.scala:77)
        at 
org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1$$anonfun$apply$2.applyOrElse(CheckAnalysis.scala:74)
        at 
org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp$1.apply(TreeNode.scala:301)
        at 
org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp$1.apply(TreeNode.scala:301)
        at 
org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:69)
        at 
org.apache.spark.sql.catalyst.trees.TreeNode.transformUp(TreeNode.scala:300)
        at 
org.apache.spark.sql.catalyst.plans.QueryPlan.transformExpressionUp$1(QueryPlan.scala:191)
        at 
org.apache.spark.sql.catalyst.plans.QueryPlan.org$apache$spark$sql$catalyst$plans$QueryPlan$$recursiveTransform$2(QueryPlan.scala:201)
        at 
org.apache.spark.sql.catalyst.plans.QueryPlan$$anonfun$org$apache$spark$sql$catalyst$plans$QueryPlan$$recursiveTransform$2$1.apply(QueryPlan.scala:205)
        at 
scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
        at 
scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
        at 
scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
        at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
        at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
        at scala.collection.AbstractTraversable.map(Traversable.scala:104)
        at 
org.apache.spark.sql.catalyst.plans.QueryPlan.org$apache$spark$sql$catalyst$plans$QueryPlan$$recursiveTransform$2(QueryPlan.scala:205)
        at 
org.apache.spark.sql.catalyst.plans.QueryPlan$$anonfun$5.apply(QueryPlan.scala:210)
        at 
org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:179)
        at 
org.apache.spark.sql.catalyst.plans.QueryPlan.transformExpressionsUp(QueryPlan.scala:210)
        at 
org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1.apply(CheckAnalysis.scala:74)
        at 
org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1.apply(CheckAnalysis.scala:67)
        at 
org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:126)
        at 
org.apache.spark.sql.catalyst.analysis.CheckAnalysis$class.checkAnalysis(CheckAnalysis.scala:67)
        at 
org.apache.spark.sql.catalyst.analysis.Analyzer.checkAnalysis(Analyzer.scala:58)
        at 
org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:49)
        at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:64)
        at 
org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$withPlan(Dataset.scala:2603)
        at org.apache.spark.sql.Dataset.select(Dataset.scala:969)
        at sun.reflect.GeneratedMethodAccessor52.invoke(Unknown Source)
        at 
sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
        at java.lang.reflect.Method.invoke(Method.java:498)
        at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:237)
        at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
        at py4j.Gateway.invoke(Gateway.java:280)
        at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
        at py4j.commands.CallCommand.execute(CallCommand.java:79)
        at py4j.GatewayConnection.run(GatewayConnection.java:214)
        at java.lang.Thread.run(Thread.java:745)

> Column names Corrupted in pysaprk dataframe groupBy
> ---------------------------------------------------
>
>                 Key: SPARK-17908
>                 URL: https://issues.apache.org/jira/browse/SPARK-17908
>             Project: Spark
>          Issue Type: Bug
>          Components: PySpark
>    Affects Versions: 1.6.0, 1.6.1, 1.6.2, 2.0.0, 2.0.1
>            Reporter: Harish
>            Priority: Minor
>
> I have DF say df
> df1= df.groupBy('key1', 'key2', 
> 'key3').agg(func.count(func.col('val')).alias('total'))
> df3 =df.join(df1, ['key1', 'key2', 'key3'])\
>              .withcolumn('newcol', func.col('val')/func.col('total'))
> I am getting key2 is not present in df1, which is not truw becuase df1.show 
> () is having the data with the key2.
> Then i added this code  before join-- df1 = df1.columnRenamed('key2', 'key2') 
> renamed with same name. Then it works.
> Stack trace will say column missing, but it is npt.



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