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Posted to issues@spark.apache.org by "Apache Spark (Jira)" <ji...@apache.org> on 2020/10/24 04:43:00 UTC
[jira] [Assigned] (SPARK-33229) UnsupportedOperationException when
group by with cube
[ https://issues.apache.org/jira/browse/SPARK-33229?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Apache Spark reassigned SPARK-33229:
------------------------------------
Assignee: (was: Apache Spark)
> UnsupportedOperationException when group by with cube
> -----------------------------------------------------
>
> Key: SPARK-33229
> URL: https://issues.apache.org/jira/browse/SPARK-33229
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 3.0.0, 3.0.1, 3.1.0
> Reporter: Yuming Wang
> Priority: Major
>
> How to reproduce this issue:
> {code:sql}
> create table test_cube using parquet as select id as a, id as b, id as c from range(10);
> select a, b, c, count(*) from test_cube group by 1, cube(2, 3);
> {code}
> {noformat}
> spark-sql> select a, b, c, count(*) from test_cube group by 1, cube(2, 3);
> 20/10/23 06:31:51 ERROR SparkSQLDriver: Failed in [select a, b, c, count(*) from test_cube group by 1, cube(2, 3)]
> java.lang.UnsupportedOperationException
> at org.apache.spark.sql.catalyst.expressions.GroupingSet.dataType(grouping.scala:35)
> at org.apache.spark.sql.catalyst.expressions.GroupingSet.dataType$(grouping.scala:35)
> at org.apache.spark.sql.catalyst.expressions.Cube.dataType(grouping.scala:60)
> at org.apache.spark.sql.catalyst.analysis.CheckAnalysis.checkValidGroupingExprs$1(CheckAnalysis.scala:268)
> at org.apache.spark.sql.catalyst.analysis.CheckAnalysis.$anonfun$checkAnalysis$12(CheckAnalysis.scala:284)
> at org.apache.spark.sql.catalyst.analysis.CheckAnalysis.$anonfun$checkAnalysis$12$adapted(CheckAnalysis.scala:284)
> at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
> at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
> at org.apache.spark.sql.catalyst.analysis.CheckAnalysis.$anonfun$checkAnalysis$1(CheckAnalysis.scala:284)
> at org.apache.spark.sql.catalyst.analysis.CheckAnalysis.$anonfun$checkAnalysis$1$adapted(CheckAnalysis.scala:92)
> at org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:177)
> at org.apache.spark.sql.catalyst.analysis.CheckAnalysis.checkAnalysis(CheckAnalysis.scala:92)
> at org.apache.spark.sql.catalyst.analysis.CheckAnalysis.checkAnalysis$(CheckAnalysis.scala:89)
> at org.apache.spark.sql.catalyst.analysis.Analyzer.checkAnalysis(Analyzer.scala:130)
> at org.apache.spark.sql.catalyst.analysis.Analyzer.$anonfun$executeAndCheck$1(Analyzer.scala:156)
> at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper$.markInAnalyzer(AnalysisHelper.scala:201)
> at org.apache.spark.sql.catalyst.analysis.Analyzer.executeAndCheck(Analyzer.scala:153)
> at org.apache.spark.sql.execution.QueryExecution.$anonfun$analyzed$1(QueryExecution.scala:68)
> at org.apache.spark.sql.catalyst.QueryPlanningTracker.measurePhase(QueryPlanningTracker.scala:111)
> at org.apache.spark.sql.execution.QueryExecution.$anonfun$executePhase$1(QueryExecution.scala:133)
> at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:764)
> at org.apache.spark.sql.execution.QueryExecution.executePhase(QueryExecution.scala:133)
> at org.apache.spark.sql.execution.QueryExecution.analyzed$lzycompute(QueryExecution.scala:68)
> at org.apache.spark.sql.execution.QueryExecution.analyzed(QueryExecution.scala:66)
> at org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:58)
> at org.apache.spark.sql.Dataset$.$anonfun$ofRows$2(Dataset.scala:99)
> {noformat}
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