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Posted to issues@spark.apache.org by "Yin Huai (JIRA)" <ji...@apache.org> on 2016/04/08 20:59:25 UTC
[jira] [Commented] (SPARK-14495) Distinct aggregation cannot be
used in the having clause
[ https://issues.apache.org/jira/browse/SPARK-14495?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15232717#comment-15232717 ]
Yin Huai commented on SPARK-14495:
----------------------------------
The current workaround is to use a subquery and then use where.
> Distinct aggregation cannot be used in the having clause
> --------------------------------------------------------
>
> Key: SPARK-14495
> URL: https://issues.apache.org/jira/browse/SPARK-14495
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 1.6.1
> Reporter: Yin Huai
>
> {code}
> select date, count(distinct id)
> from (select '2010-01-01' as date, 1 as id) tmp
> group by date
> having count(distinct id) > 0;
> org.apache.spark.sql.AnalysisException: resolved attribute(s) gid#558,id#559 missing from date#554,id#555 in operator !Expand [List(date#554, null, 0, if ((gid#558 = 1)) id#559 else null),List(date#554, id#555, 1, null)], [date#554,id#561,gid#560,if ((gid = 1)) id else null#562];
> at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$class.failAnalysis(CheckAnalysis.scala:38)
> at org.apache.spark.sql.catalyst.analysis.Analyzer.failAnalysis(Analyzer.scala:44)
> at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1.apply(CheckAnalysis.scala:183)
> at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1.apply(CheckAnalysis.scala:50)
> at org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:121)
> at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$foreachUp$1.apply(TreeNode.scala:120)
> at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$foreachUp$1.apply(TreeNode.scala:120)
> at scala.collection.immutable.List.foreach(List.scala:318)
> at org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:120)
> at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$foreachUp$1.apply(TreeNode.scala:120)
> at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$foreachUp$1.apply(TreeNode.scala:120)
> at scala.collection.immutable.List.foreach(List.scala:318)
> at org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:120)
> at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$foreachUp$1.apply(TreeNode.scala:120)
> at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$foreachUp$1.apply(TreeNode.scala:120)
> at scala.collection.immutable.List.foreach(List.scala:318)
> at org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:120)
> at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$foreachUp$1.apply(TreeNode.scala:120)
> at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$foreachUp$1.apply(TreeNode.scala:120)
> at scala.collection.immutable.List.foreach(List.scala:318)
> at org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:120)
> at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$class.checkAnalysis(CheckAnalysis.scala:50)
> at org.apache.spark.sql.catalyst.analysis.Analyzer.checkAnalysis(Analyzer.scala:44)
> at org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:34)
> at org.apache.spark.sql.DataFrame.<init>(DataFrame.scala:133)
> at org.apache.spark.sql.DataFrame$.apply(DataFrame.scala:52)
> at org.apache.spark.sql.SQLContext.sql(SQLContext.scala:816)
> {code}
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