spark-issues mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From "StanZhai (JIRA)" <j...@apache.org>
Subject [jira] [Created] (SPARK-8588) Could not use concat with UDF in where clause
Date Wed, 24 Jun 2015 07:25:42 GMT
StanZhai created SPARK-8588:
-------------------------------

             Summary: Could not use concat with UDF in where clause
                 Key: SPARK-8588
                 URL: https://issues.apache.org/jira/browse/SPARK-8588
             Project: Spark
          Issue Type: Bug
          Components: SQL
    Affects Versions: 1.4.0
         Environment: Centos 7, java 1.7.0_67, scala 2.10.5, run in a spark standalone cluster(or
local).
            Reporter: StanZhai
            Priority: Blocker


After upgraded the cluster from spark 1.3.1 to 1.4.0(rc4), I encountered the following exception
when use concat with UDF in where clause: 

{code}
org.apache.spark.sql.catalyst.analysis.UnresolvedException: Invalid call to dataType on unresolved
object, tree: 'concat(HiveSimpleUdf#org.apache.hadoop.hive.ql.udf.UDFYear(date#1776),年)

        at org.apache.spark.sql.catalyst.analysis.UnresolvedFunction.dataType(unresolved.scala:82)

        at org.apache.spark.sql.catalyst.analysis.HiveTypeCoercion$InConversion$$anonfun$apply$5$$anonfun$applyOrElse$15.apply(HiveTypeCoercion.scala:299)

        at org.apache.spark.sql.catalyst.analysis.HiveTypeCoercion$InConversion$$anonfun$apply$5$$anonfun$applyOrElse$15.apply(HiveTypeCoercion.scala:299)

        at scala.collection.LinearSeqOptimized$class.exists(LinearSeqOptimized.scala:80) 
        at scala.collection.immutable.List.exists(List.scala:84) 
        at org.apache.spark.sql.catalyst.analysis.HiveTypeCoercion$InConversion$$anonfun$apply$5.applyOrElse(HiveTypeCoercion.scala:299)

        at org.apache.spark.sql.catalyst.analysis.HiveTypeCoercion$InConversion$$anonfun$apply$5.applyOrElse(HiveTypeCoercion.scala:298)

        at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:222)

        at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:222)

        at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:51)

        at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:221)

        at org.apache.spark.sql.catalyst.plans.QueryPlan.org$apache$spark$sql$catalyst$plans$QueryPlan$$transformExpressionDown$1(QueryPlan.scala:75)

        at org.apache.spark.sql.catalyst.plans.QueryPlan$$anonfun$1.apply(QueryPlan.scala:85)

        at scala.collection.Iterator$$anon$11.next(Iterator.scala:328) 
        at scala.collection.Iterator$class.foreach(Iterator.scala:727) 
        at scala.collection.AbstractIterator.foreach(Iterator.scala:1157) 
        at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48) 
        at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103) 
        at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47) 
        at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:273) 
        at scala.collection.AbstractIterator.to(Iterator.scala:1157) 
        at scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:265) 
        at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1157) 
        at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:252) 
        at scala.collection.AbstractIterator.toArray(Iterator.scala:1157) 
        at org.apache.spark.sql.catalyst.plans.QueryPlan.transformExpressionsDown(QueryPlan.scala:94)

        at org.apache.spark.sql.catalyst.plans.QueryPlan.transformExpressions(QueryPlan.scala:64)

        at org.apache.spark.sql.catalyst.plans.QueryPlan$$anonfun$transformAllExpressions$1.applyOrElse(QueryPlan.scala:136)

        at org.apache.spark.sql.catalyst.plans.QueryPlan$$anonfun$transformAllExpressions$1.applyOrElse(QueryPlan.scala:135)

        at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:222)

        at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:222)

        at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:51)

        at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:221)

        at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:242)

        at scala.collection.Iterator$$anon$11.next(Iterator.scala:328) 
        at scala.collection.Iterator$class.foreach(Iterator.scala:727) 
        at scala.collection.AbstractIterator.foreach(Iterator.scala:1157) 
        at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48) 
        at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103) 
        at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47) 
        at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:273) 
        at scala.collection.AbstractIterator.to(Iterator.scala:1157) 
        at scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:265) 
        at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1157) 
        at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:252) 
        at scala.collection.AbstractIterator.toArray(Iterator.scala:1157) 
        at org.apache.spark.sql.catalyst.trees.TreeNode.transformChildrenDown(TreeNode.scala:272)

        at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:227)

        at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:242)

        at scala.collection.Iterator$$anon$11.next(Iterator.scala:328) 
        at scala.collection.Iterator$class.foreach(Iterator.scala:727) 
        at scala.collection.AbstractIterator.foreach(Iterator.scala:1157) 
        at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48) 
        at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103) 
        at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47) 
        at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:273) 
        at scala.collection.AbstractIterator.to(Iterator.scala:1157) 
        at scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:265) 
        at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1157) 
        at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:252) 
        at scala.collection.AbstractIterator.toArray(Iterator.scala:1157) 
        at org.apache.spark.sql.catalyst.trees.TreeNode.transformChildrenDown(TreeNode.scala:272)

        at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:227)

        at org.apache.spark.sql.catalyst.trees.TreeNode.transform(TreeNode.scala:212) 
        at org.apache.spark.sql.catalyst.plans.QueryPlan.transformAllExpressions(QueryPlan.scala:135)

        at org.apache.spark.sql.catalyst.analysis.HiveTypeCoercion$InConversion$.apply(HiveTypeCoercion.scala:298)

        at org.apache.spark.sql.catalyst.analysis.HiveTypeCoercion$InConversion$.apply(HiveTypeCoercion.scala:297)

        at org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:61)

        at org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:59)

        at scala.collection.LinearSeqOptimized$class.foldLeft(LinearSeqOptimized.scala:111)

        at scala.collection.immutable.List.foldLeft(List.scala:84) 
        at org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:59)

        at org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:51)

        at scala.collection.immutable.List.foreach(List.scala:318) 
        at org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:51)

        at org.apache.spark.sql.SQLContext$QueryExecution.analyzed$lzycompute(SQLContext.scala:922)

        at org.apache.spark.sql.SQLContext$QueryExecution.analyzed(SQLContext.scala:922) 
        at org.apache.spark.sql.SQLContext$QueryExecution.assertAnalyzed(SQLContext.scala:920)

        at org.apache.spark.sql.DataFrame.<init>(DataFrame.scala:131) 
        at org.apache.spark.sql.DataFrame$.apply(DataFrame.scala:51) 
        at org.apache.spark.sql.SQLContext.sql(SQLContext.scala:744) 
        at test.service.SparkHiveService.query(SparkHiveService.scala:79) 
        ... 
        at java.lang.Thread.run(Thread.java:745) 
{code}

The SQL is: 
{quote}
select * from test where concat(year(date), '年') in ( '2015年', '2014年' ) limit 10 {quote}

This SQL can be run in spark 1.3.1 but error in spark 1.4. I've tried run some similar sql
in spark 1.4.0, found the following sql could be run correctly: 

select * from test where concat(year(date), '年') = '2015年' limit 10 
select * from test where concat(sex, 'T') in ( 'MT' ) limit 10 

In short, when I use 'concat', UDF and 'in' together in sql, I will get the exception:  Invalid
call to dataType on unresolved object. 



--
This message was sent by Atlassian JIRA
(v6.3.4#6332)

---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org


Mime
View raw message