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https://issues.apache.org/jira/browse/SPARK-11032?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Michael Armbrust resolved SPARK-11032.
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Resolution: Fixed
Fix Version/s: 1.6.0
Issue resolved by pull request 9105
[https://github.com/apache/spark/pull/9105]
> Failure to resolve having correctly
> -----------------------------------
>
> Key: SPARK-11032
> URL: https://issues.apache.org/jira/browse/SPARK-11032
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 1.5.1, 1.6.0
> Reporter: Michael Armbrust
> Priority: Blocker
> Fix For: 1.6.0
>
>
> This is a regression from Spark 1.4
> {code}
> Seq(("michael", 30)).toDF("name", "age").registerTempTable("people")
> sql("SELECT MIN(t0.age) FROM (SELECT * FROM PEOPLE WHERE age > 0) t0
> HAVING(COUNT(1) > 0)").explain(true)
> == Parsed Logical Plan ==
> 'Filter cast(('COUNT(1) > 0) as boolean)
> 'Project [unresolvedalias('MIN('t0.age))]
> 'Subquery t0
> 'Project [unresolvedalias(*)]
> 'Filter ('age > 0)
> 'UnresolvedRelation [PEOPLE], None
> == Analyzed Logical Plan ==
> _c0: int
> Filter cast((count(1) > cast(0 as bigint)) as boolean)
> Aggregate [min(age#6) AS _c0#9]
> Subquery t0
> Project [name#5,age#6]
> Filter (age#6 > 0)
> Subquery people
> Project [_1#3 AS name#5,_2#4 AS age#6]
> LocalRelation [_1#3,_2#4], [[michael,30]]
> == Optimized Logical Plan ==
> Filter (count(1) > 0)
> Aggregate [min(age#6) AS _c0#9]
> Project [_2#4 AS age#6]
> Filter (_2#4 > 0)
> LocalRelation [_1#3,_2#4], [[michael,30]]
> == Physical Plan ==
> Filter (count(1) > 0)
> TungstenAggregate(key=[],
> functions=[(min(age#6),mode=Final,isDistinct=false)], output=[_c0#9])
> TungstenExchange SinglePartition
> TungstenAggregate(key=[],
> functions=[(min(age#6),mode=Partial,isDistinct=false)], output=[min#12])
> TungstenProject [_2#4 AS age#6]
> Filter (_2#4 > 0)
> LocalTableScan [_1#3,_2#4], [[michael,30]]
> Code Generation: true
> {code}
> {code}
> Caused by: java.lang.UnsupportedOperationException: Cannot evaluate
> expression: count(1)
> at
> org.apache.spark.sql.catalyst.expressions.Unevaluable$class.eval(Expression.scala:188)
> at
> org.apache.spark.sql.catalyst.expressions.Count.eval(aggregates.scala:156)
> at
> org.apache.spark.sql.catalyst.expressions.BinaryExpression.eval(Expression.scala:327)
> at
> org.apache.spark.sql.catalyst.expressions.InterpretedPredicate$$anonfun$create$2.apply(predicates.scala:38)
> at
> org.apache.spark.sql.catalyst.expressions.InterpretedPredicate$$anonfun$create$2.apply(predicates.scala:38)
> at
> org.apache.spark.sql.execution.Filter$$anonfun$4$$anonfun$apply$4.apply(basicOperators.scala:117)
> at
> org.apache.spark.sql.execution.Filter$$anonfun$4$$anonfun$apply$4.apply(basicOperators.scala:115)
> at scala.collection.Iterator$$anon$14.hasNext(Iterator.scala:390)
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
> {code}
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