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Hello,
A problem confusing me a lot. I believe it is a code bug of Crail
When running spark-io with Hibench-pagerank with 3 iterations. The stage 0 is fine, as the stage 1 starts, the problem pops out: java.io.StreamCorruptedException: invalid type code: AC;
the debug info is as follows:
WARN scheduler.TaskSetManager: Lost task 0.0 in stage 1.0 (TID 40, 172.18.0.17): java.io.StreamCorruptedException: invalid type code: AC
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1381)
at java.io.ObjectInputStream.readObject(ObjectInputStream.java:373)
at org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:75)
at org.apache.spark.serializer.DeserializationStream.readKey(Serializer.scala:157)
at org.apache.spark.serializer.DeserializationStream$$anon$2.getNext(Serializer.scala:189)
at org.apache.spark.serializer.DeserializationStream$$anon$2.getNext(Serializer.scala:186)
at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:73)
at org.apache.spark.shuffle.crail.CrailInputCloser.hasNext(CrailInputCloser.scala:33)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
at scala.collection.Iterator$class.foreach(Iterator.scala:893)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
at org.apache.spark.shuffle.crail.CrailShuffleWriter.write(CrailShuffleWriter.scala:65)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:79)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:47)
at org.apache.spark.scheduler.Task.run(Task.scala:85)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
How to solve this? A little help will be appreciated
The text was updated successfully, but these errors were encountered:
Don't think this is a Crail bug, maybe a problem with the CrailSparkSerializer. If so, it can always be solved through an application specific serializer.
Hello,
A problem confusing me a lot. I believe it is a code bug of Crail
When running spark-io with Hibench-pagerank with 3 iterations. The stage 0 is fine, as the stage 1 starts, the problem pops out: java.io.StreamCorruptedException: invalid type code: AC;
the debug info is as follows:
WARN scheduler.TaskSetManager: Lost task 0.0 in stage 1.0 (TID 40, 172.18.0.17): java.io.StreamCorruptedException: invalid type code: AC
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1381)
at java.io.ObjectInputStream.readObject(ObjectInputStream.java:373)
at org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:75)
at org.apache.spark.serializer.DeserializationStream.readKey(Serializer.scala:157)
at org.apache.spark.serializer.DeserializationStream$$anon$2.getNext(Serializer.scala:189)
at org.apache.spark.serializer.DeserializationStream$$anon$2.getNext(Serializer.scala:186)
at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:73)
at org.apache.spark.shuffle.crail.CrailInputCloser.hasNext(CrailInputCloser.scala:33)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
at scala.collection.Iterator$class.foreach(Iterator.scala:893)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
at org.apache.spark.shuffle.crail.CrailShuffleWriter.write(CrailShuffleWriter.scala:65)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:79)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:47)
at org.apache.spark.scheduler.Task.run(Task.scala:85)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
How to solve this? A little help will be appreciated
The text was updated successfully, but these errors were encountered: