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Posted to issues@spark.apache.org by "Alexandru Rosianu (JIRA)" <ji...@apache.org> on 2016/01/07 10:55:39 UTC
[jira] [Issue Comment Deleted] (SPARK-12675) Executor dies because
of ClassCastException and causes timeout
[ https://issues.apache.org/jira/browse/SPARK-12675?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Alexandru Rosianu updated SPARK-12675:
--------------------------------------
Comment: was deleted
(was: The input dataset had 16368 partitions. I decreased the number of partitions to `sc.defaultParallelism` (8 in my case) now. It not only works, but it's also faster. Thank you!)
> Executor dies because of ClassCastException and causes timeout
> --------------------------------------------------------------
>
> Key: SPARK-12675
> URL: https://issues.apache.org/jira/browse/SPARK-12675
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 1.6.0, 2.0.0
> Environment: 64-bit Linux Ubuntu 15.10, 16GB RAM, 8 cores 3ghz
> Reporter: Alexandru Rosianu
> Priority: Minor
>
> I'm trying to fit a Spark ML pipeline but my executor dies. Here's the script which doesn't work (a bit simplified):
> {code:title=Script.scala}
> // Prepare data sets
> logInfo("Getting datasets")
> val emoTrainingData = sqlc.read.parquet("/tw/sentiment/emo/parsed/data.parquet")
> val trainingData = emoTrainingData
> // Configure the pipeline
> val pipeline = new Pipeline().setStages(Array(
> new FeatureReducer().setInputCol("raw_text").setOutputCol("reduced_text"),
> new StringSanitizer().setInputCol("reduced_text").setOutputCol("text"),
> new Tokenizer().setInputCol("text").setOutputCol("raw_words"),
> new StopWordsRemover().setInputCol("raw_words").setOutputCol("words"),
> new HashingTF().setInputCol("words").setOutputCol("features"),
> new NaiveBayes().setSmoothing(0.5).setFeaturesCol("features"),
> new ColumnDropper().setDropColumns("raw_text", "reduced_text", "text", "raw_words", "words", "features")
> ))
> // Fit the pipeline
> logInfo(s"Training model on ${trainingData.count()} rows")
> val model = pipeline.fit(trainingData)
> {code}
> It executes up to the last line. It prints "Training model on xx rows", then it starts fitting, the executor dies, the drivers doesn't receive heartbeats from the executor and it times out, then the script exits. It doesn't get past that line.
> This is the exception that kills the executor:
> {code}
> java.io.IOException: java.lang.ClassCastException: cannot assign instance of scala.collection.immutable.HashMap$SerializationProxy to field org.apache.spark.executor.TaskMetrics._accumulatorUpdates of type scala.collection.immutable.Map in instance of org.apache.spark.executor.TaskMetrics
> at org.apache.spark.util.Utils$.tryOrIOException(Utils.scala:1207)
> at org.apache.spark.executor.TaskMetrics.readObject(TaskMetrics.scala:219)
> at sun.reflect.GeneratedMethodAccessor15.invoke(Unknown Source)
> at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:497)
> at java.io.ObjectStreamClass.invokeReadObject(ObjectStreamClass.java:1058)
> at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1900)
> at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
> at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
> at java.io.ObjectInputStream.readObject(ObjectInputStream.java:371)
> at org.apache.spark.util.Utils$.deserialize(Utils.scala:92)
> at org.apache.spark.executor.Executor$$anonfun$org$apache$spark$executor$Executor$$reportHeartBeat$1$$anonfun$apply$6.apply(Executor.scala:436)
> at org.apache.spark.executor.Executor$$anonfun$org$apache$spark$executor$Executor$$reportHeartBeat$1$$anonfun$apply$6.apply(Executor.scala:426)
> at scala.Option.foreach(Option.scala:257)
> at org.apache.spark.executor.Executor$$anonfun$org$apache$spark$executor$Executor$$reportHeartBeat$1.apply(Executor.scala:426)
> at org.apache.spark.executor.Executor$$anonfun$org$apache$spark$executor$Executor$$reportHeartBeat$1.apply(Executor.scala:424)
> at scala.collection.Iterator$class.foreach(Iterator.scala:742)
> at scala.collection.AbstractIterator.foreach(Iterator.scala:1194)
> at scala.collection.IterableLike$class.foreach(IterableLike.scala:72)
> at scala.collection.AbstractIterable.foreach(Iterable.scala:54)
> at org.apache.spark.executor.Executor.org$apache$spark$executor$Executor$$reportHeartBeat(Executor.scala:424)
> at org.apache.spark.executor.Executor$$anon$1$$anonfun$run$1.apply$mcV$sp(Executor.scala:468)
> at org.apache.spark.executor.Executor$$anon$1$$anonfun$run$1.apply(Executor.scala:468)
> at org.apache.spark.executor.Executor$$anon$1$$anonfun$run$1.apply(Executor.scala:468)
> at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1741)
> at org.apache.spark.executor.Executor$$anon$1.run(Executor.scala:468)
> at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
> at java.util.concurrent.FutureTask.runAndReset(FutureTask.java:308)
> at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$301(ScheduledThreadPoolExecutor.java:180)
> at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:294)
> at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
> at java.lang.Thread.run(Thread.java:745)
> Caused by: java.lang.ClassCastException: cannot assign instance of scala.collection.immutable.HashMap$SerializationProxy to field org.apache.spark.executor.TaskMetrics._accumulatorUpdates of type scala.collection.immutable.Map in instance of org.apache.spark.executor.TaskMetrics
> at java.io.ObjectStreamClass$FieldReflector.setObjFieldValues(ObjectStreamClass.java:2133)
> at java.io.ObjectStreamClass.setObjFieldValues(ObjectStreamClass.java:1305)
> at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2006)
> at java.io.ObjectInputStream.defaultReadObject(ObjectInputStream.java:501)
> at org.apache.spark.executor.TaskMetrics$$anonfun$readObject$1.apply$mcV$sp(TaskMetrics.scala:220)
> at org.apache.spark.util.Utils$.tryOrIOException(Utils.scala:1204)
> ... 32 more
> {code}
> Which, later on, causes a timeout:
> {code}
> ERROR TaskSchedulerImpl: Lost executor driver on localhost: Executor heartbeat timed out after 142918 ms
> {code}
> I uploaded the INFO-level log file [here|https://infinit.io/_/DMii66J]. The DEBUG log is ~500MB.
> The build file and dependencies seem to be all right:
> {code:title=build.sbt}
> name := "tweeather"
> version := "1.0.0"
> scalaVersion := "2.11.7"
> libraryDependencies ++= Seq(
> "org.apache.spark" %% "spark-core" % "1.6.0",
> "org.apache.spark" %% "spark-mllib" % "1.6.0",
> "org.apache.spark" %% "spark-streaming" % "1.6.0",
> "org.apache.hadoop" % "hadoop-client" % "2.7.1",
> "com.github.fommil.netlib" % "all" % "1.1.2" pomOnly(),
> "org.twitter4j" % "twitter4j-stream" % "4.0.4",
> "org.scalaj" %% "scalaj-http" % "2.0.0",
> "com.jsuereth" %% "scala-arm" % "1.4",
> "edu.ucar" % "grib" % "4.6.3"
> )
> dependencyOverrides ++= Set(
> "com.fasterxml.jackson.core" % "jackson-databind" % "2.4.4",
> "org.scala-lang" % "scala-compiler" % scalaVersion.value,
> "org.scala-lang.modules" %% "scala-parser-combinators" % "1.0.4",
> "org.scala-lang.modules" %% "scala-xml" % "1.0.4",
> "jline" % "jline" % "2.12.1"
> )
> resolvers ++= Seq(
> "Unidata Releases" at "http://artifacts.unidata.ucar.edu/content/repositories/unidata-releases/"
> )
> {code}
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