See my stack overflow questions for better formatted info:
http://stackoverflow.com/questions/32621267/spark-1-5-0-hangs-running-randomforest
<http://stackoverflow.com/questions/32621267/spark-1-5-0-hangs-running-randomforest>
I am trying to run a basic decision tree from MLLIB. My spark version is
1.4.0. My configuration is:
EC2 r3.4xlarge (1 master, 2 workers)
146.6 GB Total
spark.executor.memory 100000m
spark.driver.memory 90000m
spark.driver.maxResultSize 0
spark.storage.memoryFraction 0.6
spark.default.parallelism 64
I have loaded a test dataset of LabeledPoint values, with each LabeledPoint
containing a SparseVector features. My LabeledPoint object looks like this:
LabeledPoint(0.0, (1080963,[44673,64508,65588,122081,306819,306820,382530
...], [1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0 ...]))
Additional information on each *RDD item*:
>>> d = data.first()
>>> d.label
0.0
>>> d.features.size
1080963
>>> len(d.features.values)
2286
My *model training* is very standard:
(trainingData, testData) = data.randomSplit([0.7, 0.3])
model = RandomForest.trainClassifier(trainingData, numClasses=2,
categoricalFeaturesInfo={},
numTrees=3,
featureSubsetStrategy="auto",
impurity='gini', maxDepth=4,
maxBins=32)
My *Error trace* is as follows:
15/09/17 19:36:13 INFO storage.BlockManagerInfo: Removed broadcast_4_piece0
on 10.0.28.233:38432 in memory (size: 4.4 KB, free: 45.5 GB)
15/09/17 19:36:13 INFO storage.BlockManagerInfo: Removed broadcast_4_piece0
on 10.0.28.28:58416 in memory (size: 4.4 KB, free: 50.5 GB)
15/09/17 19:36:13 INFO storage.BlockManager: Removing RDD 10
15/09/17 19:36:13 INFO spark.ContextCleaner: Cleaned RDD 10
15/09/17 19:36:13 INFO storage.BlockManagerInfo: Removed broadcast_3_piece0
on 10.0.28.233:38432 in memory (size: 4.2 KB, free: 45.5 GB)
15/09/17 19:36:13 INFO storage.BlockManagerInfo: Removed broadcast_3_piece0
on 10.0.28.28:58416 in memory (size: 4.2 KB, free: 50.5 GB)
15/09/17 19:36:13 INFO storage.BlockManagerInfo: Removed broadcast_2_piece0
on 10.0.28.233:38432 in memory (size: 3.7 KB, free: 45.5 GB)
15/09/17 19:36:13 INFO storage.BlockManagerInfo: Removed broadcast_2_piece0
on 10.0.28.28:58416 in memory (size: 3.7 KB, free: 50.5 GB)
15/09/17 19:36:13 INFO storage.BlockManagerInfo: Removed broadcast_2_piece0
on 10.0.28.31:56554 in memory (size: 3.7 KB, free: 50.5 GB)
15/09/17 20:33:43 INFO rdd.MapPartitionsRDD: Removing RDD 28 from
persistence list
15/09/17 20:33:43 INFO storage.BlockManager: Removing RDD 28
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "random_forest_spark.py", line 144, in trainModel
impurity='gini', maxDepth=4, maxBins=32)
File "/root/spark/python/pyspark/mllib/tree.py", line 352, in
trainClassifier
maxDepth, maxBins, seed)
File "/root/spark/python/pyspark/mllib/tree.py", line 270, in _train
maxDepth, maxBins, seed)
File "/root/spark/python/pyspark/mllib/common.py", line 128, in
callMLlibFunc
return callJavaFunc(sc, api, *args)
File "/root/spark/python/pyspark/mllib/common.py", line 121, in
callJavaFunc
return _java2py(sc, func(*args))
File "/root/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/java_gateway.py",
line 538, in __call__
File "/root/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/protocol.py", line
300, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling
o104.trainRandomForestModel.
: java.lang.OutOfMemoryError
at
java.io.ByteArrayOutputStream.hugeCapacity(ByteArrayOutputStream.java:123)
at
java.io.ByteArrayOutputStream.grow(ByteArrayOutputStream.java:117)
at
java.io.ByteArrayOutputStream.ensureCapacity(ByteArrayOutputStream.java:93)
at
java.io.ByteArrayOutputStream.write(ByteArrayOutputStream.java:153)
at
java.io.ObjectOutputStream$BlockDataOutputStream.drain(ObjectOutputStream.java:1876)
at
java.io.ObjectOutputStream$BlockDataOutputStream.setBlockDataMode(ObjectOutputStream.java:1785)
at
java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1188)
at
java.io.ObjectOutputStream.writeObject(ObjectOutputStream.java:347)
at
org.apache.spark.serializer.JavaSerializationStream.writeObject(JavaSerializer.scala:44)
at
org.apache.spark.serializer.JavaSerializerInstance.serialize(JavaSerializer.scala:81)
at
org.apache.spark.util.ClosureCleaner$.ensureSerializable(ClosureCleaner.scala:312)
at
org.apache.spark.util.ClosureCleaner$.org$apache$spark$util$ClosureCleaner$$clean(ClosureCleaner.scala:305)
at
org.apache.spark.util.ClosureCleaner$.clean(ClosureCleaner.scala:132)
at org.apache.spark.SparkContext.clean(SparkContext.scala:1891)
at org.apache.spark.rdd.RDD$$anonfun$map$1.apply(RDD.scala:294)
at org.apache.spark.rdd.RDD$$anonfun$map$1.apply(RDD.scala:293)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:148)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:109)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:286)
at org.apache.spark.rdd.RDD.map(RDD.scala:293)
at
org.apache.spark.mllib.tree.impl.TreePoint$.convertToTreeRDD(TreePoint.scala:65)
at
org.apache.spark.mllib.tree.RandomForest.run(RandomForest.scala:160)
at
org.apache.spark.mllib.tree.RandomForest$.trainClassifier(RandomForest.scala:289)
at
org.apache.spark.mllib.api.python.PythonMLLibAPI.trainRandomForestModel(PythonMLLibAPI.scala:666)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at
sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
at
sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:606)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:231)
at
py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:379)
at py4j.Gateway.invoke(Gateway.java:259)
at
py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:133)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:207)
at java.lang.Thread.run(Thread.java:745)
As you can see, I am having to wait an hour to see any type of action.
15/09/17 19:36:13 INFO storage.BlockManagerInfo: Removed broadcast_2_piece0
on 10.0.28.31:56554 in memory (size: 3.7 KB, free: 50.5 GB)
15/09/17 20:33:43 INFO rdd.MapPartitionsRDD: Removing RDD 28 from
persistence list
Does anyone know where I could start to debug this issue?
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