You are perhaps hitting an issue that was fixed by #3248 <https://github.com/apache/spark/pull/3248>?
On Mon, Nov 17, 2014 at 9:58 AM, Sadhan Sood <sadhan.s...@gmail.com> wrote: > While testing sparkSQL, we were running this group by with expression > query and got an exception. The same query worked fine on hive. > > SELECT from_unixtime(floor(xyz.whenrequestreceived/1000.0 - 25200), > 'yyyy/MM/dd') as pst_date, > count(*) as num_xyzs > FROM > all_matched_abc > GROUP BY > from_unixtime(floor(xyz.whenrequestreceived/1000.0 - 25200), > 'yyyy/MM/dd') > > 14/11/17 17:41:46 ERROR thriftserver.SparkSQLDriver: Failed in [SELECT > from_unixtime(floor(xyz.whenrequestreceived/1000.0 - 25200), > 'yyyy/MM/dd') as pst_date, > count(*) as num_xyzs > FROM > all_matched_abc > GROUP BY > from_unixtime(floor(xyz.whenrequestreceived/1000.0 - 25200), > 'yyyy/MM/dd') > ] > org.apache.spark.sql.catalyst.errors.package$TreeNodeException: Expression > not in GROUP BY: > HiveSimpleUdf#org.apache.hadoop.hive.ql.udf.UDFFromUnixTime(HiveGenericUdf#org.apache.hadoop.hive.ql.udf.generic.GenericUDFFloor(((CAST(xyz#183.whenrequestreceived > AS whenrequestreceived#187L, DoubleType) / 1000.0) - CAST(25200, > DoubleType))),yyyy/MM/dd) AS pst_date#179, tree: > > Aggregate > [HiveSimpleUdf#org.apache.hadoop.hive.ql.udf.UDFFromUnixTime(HiveGenericUdf#org.apache.hadoop.hive.ql.udf.generic.GenericUDFFloor(((CAST(xyz#183.whenrequestreceived, > DoubleType) / 1000.0) - CAST(25200, DoubleType))),yyyy/MM/dd)], > [HiveSimpleUdf#org.apache.hadoop.hive.ql.udf.UDFFromUnixTime(HiveGenericUdf#org.apache.hadoop.hive.ql.udf.generic.GenericUDFFloor(((CAST(xyz#183.whenrequestreceived > AS whenrequestreceived#187L, DoubleType) / 1000.0) - CAST(25200, > DoubleType))),yyyy/MM/dd) AS pst_date#179,COUNT(1) AS num_xyzs#180L] > > MetastoreRelation default, all_matched_abc, None > at > org.apache.spark.sql.catalyst.analysis.Analyzer$CheckAggregation$$anonfun$apply$3$$anonfun$applyOrElse$6.apply(Analyzer.scala:127) > at > org.apache.spark.sql.catalyst.analysis.Analyzer$CheckAggregation$$anonfun$apply$3$$anonfun$applyOrElse$6.apply(Analyzer.scala:125) > at > scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) > at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47) > at > org.apache.spark.sql.catalyst.analysis.Analyzer$CheckAggregation$$anonfun$apply$3.applyOrElse(Analyzer.scala:125) > at > org.apache.spark.sql.catalyst.analysis.Analyzer$CheckAggregation$$anonfun$apply$3.applyOrElse(Analyzer.scala:115) > at > org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:144) > at > org.apache.spark.sql.catalyst.trees.TreeNode.transform(TreeNode.scala:135) > at > org.apache.spark.sql.catalyst.analysis.Analyzer$CheckAggregation$.apply(Analyzer.scala:115) > at > org.apache.spark.sql.catalyst.analysis.Analyzer$CheckAggregation$.apply(Analyzer.scala:113) > at > org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$apply$1$$anonfun$apply$2.apply(RuleExecutor.scala:61) > at > org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$apply$1$$anonfun$apply$2.apply(RuleExecutor.scala:59) > at > scala.collection.IndexedSeqOptimized$class.foldl(IndexedSeqOptimized.scala:51) > at > scala.collection.IndexedSeqOptimized$class.foldLeft(IndexedSeqOptimized.scala:60) > at > scala.collection.mutable.WrappedArray.foldLeft(WrappedArray.scala:34) > at > org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$apply$1.apply(RuleExecutor.scala:59) > at > org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$apply$1.apply(RuleExecutor.scala:51) > at scala.collection.immutable.List.foreach(List.scala:318) > at > org.apache.spark.sql.catalyst.rules.RuleExecutor.apply(RuleExecutor.scala:51) > at > org.apache.spark.sql.SQLContext$QueryExecution.analyzed$lzycompute(SQLContext.scala:411) > at > org.apache.spark.sql.SQLContext$QueryExecution.analyzed(SQLContext.scala:411) > at > org.apache.spark.sql.SQLContext$QueryExecution.withCachedData$lzycompute(SQLContext.scala:412) > at > org.apache.spark.sql.SQLContext$QueryExecution.withCachedData(SQLContext.scala:412) > at > org.apache.spark.sql.SQLContext$QueryExecution.optimizedPlan$lzycompute(SQLContext.scala:413) > at > org.apache.spark.sql.SQLContext$QueryExecution.optimizedPlan(SQLContext.scala:413) > at > org.apache.spark.sql.SQLContext$QueryExecution.sparkPlan$lzycompute(SQLContext.scala:418) > at > org.apache.spark.sql.SQLContext$QueryExecution.sparkPlan(SQLContext.scala:416) > at > org.apache.spark.sql.SQLContext$QueryExecution.executedPlan$lzycompute(SQLContext.scala:422) > at > org.apache.spark.sql.SQLContext$QueryExecution.executedPlan(SQLContext.scala:422) > at > org.apache.spark.sql.hive.HiveContext$QueryExecution.stringResult(HiveContext.scala:425) > at > org.apache.spark.sql.hive.thriftserver.AbstractSparkSQLDriver.run(AbstractSparkSQLDriver.scala:59) > at > org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver.processCmd(SparkSQLCLIDriver.scala:276) > at > org.apache.hadoop.hive.cli.CliDriver.processLine(CliDriver.java:423) > at > org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver$.main(SparkSQLCLIDriver.scala:211) > at > org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver.main(SparkSQLCLIDriver.scala) > at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) > at > sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) > at > sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) > at java.lang.reflect.Method.invoke(Method.java:483) > at org.apache.spark.deploy.SparkSubmit$.launch(SparkSubmit.scala:353) > at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:75) > at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala) > >
