Can you file a JIRA please? On Tue, Jun 23, 2015 at 1:42 AM, StanZhai <m...@zhaishidan.cn> wrote:
> Hi all, > > 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: > > ===================Exception==================== > 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) > > =============The SQL is: =================== > select * from test where concat(year(date), '年') in ( '2015年', '2014年' ) > limit 10 > > 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. > > Is catalyst changed from 1.3 to 1.4? Any suggestion? > > Best, Stan > > > > -- > View this message in context: > http://apache-spark-developers-list.1001551.n3.nabble.com/SparkSQL-1-4-Could-not-use-concat-with-UDF-in-where-clause-tp12832.html > Sent from the Apache Spark Developers List mailing list archive at > Nabble.com. > > --------------------------------------------------------------------- > To unsubscribe, e-mail: dev-unsubscr...@spark.apache.org > For additional commands, e-mail: dev-h...@spark.apache.org > >
