Doh :) Thanks.. seems like brain freeze.
On Fri, Feb 6, 2015 at 3:22 PM, Michael Armbrust <mich...@databricks.com> wrote: > You can't use columns (timestamp) that aren't in the GROUP BY clause. > Spark 1.2+ give you a better error message for this case. > > On Fri, Feb 6, 2015 at 3:12 PM, Mohnish Kodnani <mohnish.kodn...@gmail.com > > wrote: > >> Hi, >> i am trying to issue a sql query against a parquet file and am getting >> errors and would like some help to figure out what is going on. >> >> The sql : >> select timestamp, count(rid), qi.clientname from records where timestamp >> > 0 group by qi.clientname >> >> I am getting the following error: >> *org.apache.spark.sql.catalyst.errors.package$TreeNodeException: Binding >> attribute, tree: timestamp#0L* >> at >> org.apache.spark.sql.catalyst.errors.package$.attachTree(package.scala:47) >> at >> org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1.applyOrElse(BoundAttribute.scala:43) >> at >> org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1.applyOrElse(BoundAttribute.scala:42) >> at >> org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:165) >> at >> org.apache.spark.sql.catalyst.trees.TreeNode.transform(TreeNode.scala:156) >> at >> org.apache.spark.sql.catalyst.expressions.BindReferences$.bindReference(BoundAttribute.scala:42) >> at >> org.apache.spark.sql.catalyst.expressions.InterpretedMutableProjection$$anonfun$$init$$2.apply(Projection.scala:52) >> at >> org.apache.spark.sql.catalyst.expressions.InterpretedMutableProjection$$anonfun$$init$$2.apply(Projection.scala:52) >> at >> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244) >> at >> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244) >> at scala.collection.immutable.List.foreach(List.scala:318) >> at scala.collection.TraversableLike$class.map(TraversableLike.scala:244) >> at scala.collection.AbstractTraversable.map(Traversable.scala:105) >> at >> org.apache.spark.sql.catalyst.expressions.InterpretedMutableProjection.<init>(Projection.scala:52) >> at >> org.apache.spark.sql.execution.Aggregate$$anonfun$execute$1$$anonfun$7$$anon$1.<init>(Aggregate.scala:176) >> at >> org.apache.spark.sql.execution.Aggregate$$anonfun$execute$1$$anonfun$7.apply(Aggregate.scala:172) >> at >> org.apache.spark.sql.execution.Aggregate$$anonfun$execute$1$$anonfun$7.apply(Aggregate.scala:151) >> at org.apache.spark.rdd.RDD$$anonfun$13.apply(RDD.scala:596) >> at org.apache.spark.rdd.RDD$$anonfun$13.apply(RDD.scala:596) >> at >> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35) >> at org.apache.spark.sql.SchemaRDD.compute(SchemaRDD.scala:115) >> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262) >> at org.apache.spark.rdd.RDD.iterator(RDD.scala:229) >> at >> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35) >> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262) >> at org.apache.spark.rdd.RDD.iterator(RDD.scala:229) >> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:62) >> at org.apache.spark.scheduler.Task.run(Task.scala:54) >> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:178) >> at >> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145) >> at >> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615) >> at java.lang.Thread.run(Thread.java:745) >> *Caused by: java.lang.RuntimeException: Couldn't find timestamp#0L in >> [aggResult:SUM(PartialCount#14L)#17L,clientName#11]* >> at scala.sys.package$.error(package.scala:27) >> at >> org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1$$anonfun$applyOrElse$1.apply(BoundAttribute.scala:46) >> at >> org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1$$anonfun$applyOrElse$1.apply(BoundAttribute.scala:43) >> at >> org.apache.spark.sql.catalyst.errors.package$.attachTree(package.scala:46) >> >> >
