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Posted to issues@spark.apache.org by "Yuming Wang (Jira)" <ji...@apache.org> on 2020/10/23 13:35:00 UTC
[jira] [Created] (SPARK-33229) UnsupportedOperationException when
group by with cube
Yuming Wang created SPARK-33229:
-----------------------------------
Summary: 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: 3.0.1, 3.0.0, 3.1.0
Reporter: Yuming Wang
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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