Filed https://issues.apache.org/jira/browse/SPARK-3891
Thanks, Anand Mohan On Thu, Oct 9, 2014 at 7:13 PM, Michael Armbrust <mich...@databricks.com> wrote: > Please file a JIRA:https://issues.apache.org/jira/browse/SPARK/ > <https://www.google.com/url?q=https%3A%2F%2Fissues.apache.org%2Fjira%2Fbrowse%2FSPARK%2F&sa=D&sntz=1&usg=AFQjCNFS_GnMso2OCOITA0TSJ5U10b3JSQ> > > On Thu, Oct 9, 2014 at 6:48 PM, Anand Mohan <chinn...@gmail.com> wrote: > >> Hi, >> >> I just noticed the Percentile UDAF PR being merged into trunk and decided >> to test it. >> So pulled in today's trunk and tested the percentile queries. >> They work marvelously, Thanks a lot for bringing this into Spark SQL. >> >> However Hive percentile UDAF also supports an array mode where in you can >> give the list of percentiles that you want and it would return an array of >> double values one for each requested percentile. >> This query is failing with the below error. However a query with the >> individual percentiles like >> percentile(turnaroundtime,0.25),percentile(turnaroundtime,0.5),percentile(turnaroundtime,0.75) >> is working. (and so this issue is not of a high priority as there is this >> workaround for us) >> >> Thanks, >> Anand Mohan >> >> 0: jdbc:hive2://dev-uuppala.sfohi.philips.com> select name, >> percentile(turnaroundtime,array(0,0.25,0.5,0.75,1)) from exam group by name; >> >> Error: org.apache.spark.SparkException: Job aborted due to stage failure: >> Task 1 in stage 25.0 failed 4 times, most recent failure: Lost task 1.3 in >> stage 25.0 (TID 305, Dev-uuppala.sfohi.philips.com): >> java.lang.ClassCastException: scala.collection.mutable.ArrayBuffer cannot >> be cast to [Ljava.lang.Object; >> >> org.apache.hadoop.hive.serde2.objectinspector.StandardListObjectInspector.getListLength(StandardListObjectInspector.java:83) >> >> org.apache.hadoop.hive.serde2.objectinspector.ObjectInspectorConverters$ListConverter.convert(ObjectInspectorConverters.java:259) >> >> org.apache.hadoop.hive.ql.udf.generic.GenericUDFUtils$ConversionHelper.convertIfNecessary(GenericUDFUtils.java:349) >> >> org.apache.hadoop.hive.ql.udf.generic.GenericUDAFBridge$GenericUDAFBridgeEvaluator.iterate(GenericUDAFBridge.java:170) >> >> org.apache.spark.sql.hive.HiveUdafFunction.update(hiveUdfs.scala:342) >> >> org.apache.spark.sql.execution.Aggregate$$anonfun$execute$1$$anonfun$7.apply(Aggregate.scala:167) >> >> org.apache.spark.sql.execution.Aggregate$$anonfun$execute$1$$anonfun$7.apply(Aggregate.scala:151) >> org.apache.spark.rdd.RDD$$anonfun$13.apply(RDD.scala:599) >> org.apache.spark.rdd.RDD$$anonfun$13.apply(RDD.scala:599) >> >> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35) >> org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262) >> org.apache.spark.rdd.RDD.iterator(RDD.scala:229) >> org.apache.spark.rdd.MappedRDD.compute(MappedRDD.scala:31) >> org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262) >> org.apache.spark.rdd.RDD.iterator(RDD.scala:229) >> org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61) >> org.apache.spark.scheduler.Task.run(Task.scala:56) >> >> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:181) >> >> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145) >> >> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615) >> java.lang.Thread.run(Thread.java:745) >> Driver stacktrace: (state=,code=0) >> >> >> >> ------------------------------ >> View this message in context: Spark SQL Percentile UDAF >> <http://apache-spark-user-list.1001560.n3.nabble.com/Spark-SQL-Percentile-UDAF-tp16092.html> >> Sent from the Apache Spark User List mailing list archive >> <http://apache-spark-user-list.1001560.n3.nabble.com/> at Nabble.com. >> > >
