Hey Mike, I would look to Hive to fix this - it should be able to handle either a 0 or 0.0 in the response equally well. I suppose I wouldn't consider it to be a bug in Druid.
On Mon, Dec 17, 2018 at 10:15 AM mike <m...@shujike.com> wrote: > Hello, Could anybody give me a hand? > > Recently, I upgraded my druid server version from 0.9.2 to lastest > 0.12.3, I encountered into a trouble when I ran my previous application > over new druid. It worked fine on 0.9.2. after check up the logs, I found > that for double fields in my schema, it returned 0 instead of 0.0 in the > query result, which caused my json parser unhappy and throwed an exception > something like that: > > 18/12/11 19:36:37 ERROR thriftserver.SparkExecuteStatementOperation: Error > running hive query: > org.apache.hive.service.cli.HiveSQLException: > org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 > in stage 11.0 failed 1 times, most recent failure: Lost task 0.0 in stage > 11.0 (TID 11, localhost): java.lang.ClassCastException: scala.math.BigInt > cannot be cast to java.lang.Double > at scala.runtime.BoxesRunTime.unboxToDouble(BoxesRunTime.java:114) > at > org.apache.spark.sql.catalyst.expressions.BaseGenericInternalRow$class.getDouble(rows.scala:44) > at > org.apache.spark.sql.catalyst.expressions.GenericInternalRow.getDouble(rows.scala:221) > at > org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown > Source) > at > org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) > at > org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:370) > at > org.apache.spark.sql.execution.SparkPlan$$anonfun$4.apply(SparkPlan.scala:246) > at > org.apache.spark.sql.execution.SparkPlan$$anonfun$4.apply(SparkPlan.scala:240) > at > org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:803) > at > org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:803) > at > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:283) > at > org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70) > at org.apache.spark.scheduler.Task.run(Task.scala:86) > at > org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274) > at > java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) > at > java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) > at java.lang.Thread.run(Thread.java:748) > > > > Could anybody respond to me or fix this bug or help me get out of this > disgusting trouble, thanks million! > > Michael
