Was trying out 1.5 rc2 and noticed some issues with the Tungsten shuffle manager. One problem was when using the com.databricks.spark.avro reader and the error(1) was received, see stack trace below. The problem does not occur with the "sort" shuffle manager.
Another problem was in a large complex job with lots of transformations occurring simultaneously, i.e. 50+ or more maps each shuffling data. Received error(2) about inability to acquire memory which seems to also have to do with Tungsten. Possibly some setting available to increase that memory, because there's lots of heap memory available. Am running on Yarn 2.2 with about 400 executors. Hoping this will give some hints for improving the upcoming release, or for me to get some hints to fix the problems. Thanks, Anders *Error(1) * 15/08/31 18:30:57 WARN TaskSetManager: Lost task 0.0 in stage 1.0 (TID 3387, lon4-hadoopslave-c245.lon4.spotify.net): java.io.EOFException at java.io.DataInputStream.readInt(DataInputStream.java:392) at org.apache.spark.sql.execution.UnsafeRowSerializerInstance$$anon$3$$anon$1.next(UnsafeRowSerializer.scala:121) at org.apache.spark.sql.execution.UnsafeRowSerializerInstance$$anon$3$$anon$1.next(UnsafeRowSerializer.scala:109) at scala.collection.Iterator$$anon$13.next(Iterator.scala:372) at scala.collection.Iterator$$anon$11.next(Iterator.scala:328) at org.apache.spark.util.CompletionIterator.next(CompletionIterator.scala:30) at org.apache.spark.InterruptibleIterator.next(InterruptibleIterator.scala:43) at scala.collection.Iterator$$anon$11.next(Iterator.scala:328) at org.apache.spark.sql.execution.aggregate.TungstenAggregationIterator.processInputs(TungstenAggregationIterator.scala:366) at org.apache.spark.sql.execution.aggregate.TungstenAggregationIterator.start(TungstenAggregationIterator.scala:622) at org.apache.spark.sql.execution.aggregate.TungstenAggregate$$anonfun$doExecute$ 1.org$apache$spark$sql$execution$aggregate$Tung stenAggregate$$anonfun$$executePartition$1(TungstenAggregate.scala:110) at org.apache.spark.sql.execution.aggregate.TungstenAggregate$$anonfun$doExecute$1$$anonfun$2.apply(TungstenAggregate.scala:119) at org.apache.spark.sql.execution.aggregate.TungstenAggregate$$anonfun$doExecute$1$$anonfun$2.apply(TungstenAggregate.scala:119) at org.apache.spark.rdd.MapPartitionsWithPreparationRDD.compute(MapPartitionsWithPreparationRDD.scala:47) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297) at org.apache.spark.rdd.RDD.iterator(RDD.scala:264) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297) at org.apache.spark.rdd.RDD.iterator(RDD.scala:264) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66) at org.apache.spark.scheduler.Task.run(Task.scala:88) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615) at java.lang.Thread.run(Thread.java:745) *Error(2) * 5/08/31 18:41:25 WARN TaskSetManager: Lost task 16.1 in stage 316.0 (TID 32686, lon4-hadoopslave-b925.lon4.spotify.net): java.io.IOException: Unable to acquire 67108864 bytes of memory at org.apache.spark.shuffle.unsafe.UnsafeShuffleExternalSorter.acquireNewPageIfNecessary(UnsafeShuffleExternalSorter.java:385) at org.apache.spark.shuffle.unsafe.UnsafeShuffleExternalSorter.insertRecord(UnsafeShuffleExternalSorter.java:435) at org.apache.spark.shuffle.unsafe.UnsafeShuffleWriter.insertRecordIntoSorter(UnsafeShuffleWriter.java:246) at org.apache.spark.shuffle.unsafe.UnsafeShuffleWriter.write(UnsafeShuffleWriter.java:174) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41) at org.apache.spark.scheduler.Task.run(Task.scala:88) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214) 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)