[jira] [Resolved] (SPARK-7269) Incorrect aggregation analysis

["Michael Armbrust (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-7269?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Michael Armbrust resolved SPARK-7269.
-------------------------------------
       Resolution: Fixed
    Fix Version/s: 1.4.0

Issue resolved by pull request 6173
[https://github.com/apache/spark/pull/6173]

> Incorrect aggregation analysis
> ------------------------------
>
>                 Key: SPARK-7269
>                 URL: https://issues.apache.org/jira/browse/SPARK-7269
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>            Reporter: Cheng Hao
>             Fix For: 1.4.0
>
>
> In a case insensitive analyzer (HiveContext), the attribute name captial differences will fail the analysis check for aggregation.
> {code}
> test("check analysis failed in case in-sensitive") {
>     Seq(1,2,3).map(i => (i, i.toString)).toDF("key", "value").registerTempTable("df_analysis")
>     sql("SELECT kEy from df_analysis group by key")
> }
> {code}
> {noformat}
> expression 'kEy' is neither present in the group by, nor is it an aggregate function. Add to group by or wrap in first() if you don't care which value you get.;
> org.apache.spark.sql.AnalysisException: expression 'kEy' is neither present in the group by, nor is it an aggregate function. Add to group by or wrap in first() if you don't care which value you get.;
> 	at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$class.failAnalysis(CheckAnalysis.scala:38)
> 	at org.apache.spark.sql.catalyst.analysis.Analyzer.failAnalysis(Analyzer.scala:39)
> 	at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1.org$apache$spark$sql$catalyst$analysis$CheckAnalysis$class$$anonfun$$checkValidAggregateExpression$1(CheckAnalysis.scala:85)
> 	at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1$$anonfun$apply$4.apply(CheckAnalysis.scala:101)
> 	at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1$$anonfun$apply$4.apply(CheckAnalysis.scala:101)
> 	at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> 	at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
> 	at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1.apply(CheckAnalysis.scala:101)
> 	at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1.apply(CheckAnalysis.scala:50)
> 	at org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:89)
> 	at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$class.checkAnalysis(CheckAnalysis.scala:50)
> 	at org.apache.spark.sql.catalyst.analysis.Analyzer.checkAnalysis(Analyzer.scala:39)
> 	at org.apache.spark.sql.SQLContext$QueryExecution.assertAnalyzed(SQLContext.scala:1121)
> 	at org.apache.spark.sql.DataFrame.<init>(DataFrame.scala:133)
> 	at org.apache.spark.sql.DataFrame$.apply(DataFrame.scala:51)
> 	at org.apache.spark.sql.hive.HiveContext.sql(HiveContext.scala:97)
> 	at org.apache.spark.sql.hive.execution.SQLQuerySuite$$anonfun$15.apply$mcV$sp(SQLQuerySuite.scala:408)
> 	at org.apache.spark.sql.hive.execution.SQLQuerySuite$$anonfun$15.apply(SQLQuerySuite.scala:406)
> 	at org.apache.spark.sql.hive.execution.SQLQuerySuite$$anonfun$15.apply(SQLQuerySuite.scala:406)
> 	at org.scalatest.Transformer$$anonfun$apply$1.apply$mcV$sp(Transformer.scala:22)
> 	at org.scalatest.OutcomeOf$class.outcomeOf(OutcomeOf.scala:85)
> 	at org.scalatest.OutcomeOf$.outcomeOf(OutcomeOf.scala:104)
> 	at org.scalatest.Transformer.apply(Transformer.scala:22)
> 	at org.scalatest.Transformer.apply(Transformer.scala:20)
> 	at org.scalatest.FunSuiteLike$$anon$1.apply(FunSuiteLike.scala:166)
> 	at org.scalatest.Suite$class.withFixture(Suite.scala:1122)
> 	at org.scalatest.FunSuite.withFixture(FunSuite.scala:1555)
> 	at org.scalatest.FunSuiteLike$class.invokeWithFixture$1(FunSuiteLike.scala:163)
> {noformat}



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