Apache Spark: pyspark crash for large dataset - apache-spark

Question

I am new to Spark. and I have input file with training data 4000x1800. When I try to train this data (written python) get following error:
14/11/15 22:39:13 ERROR PythonRDD: Python worker exited unexpectedly (crashed)
java.net.SocketException: Connection reset by peer: socket write error
org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 0.0 failed 1 times, most recent failure: Lost task 0.0 in stage 0.0 (TID 0, local
host): java.net.SocketException: Connection reset by peer: socket write error
Working with spark 1.1.0. Any suggestion will be of great help.
Code:
from pyspark.mllib.classification import SVMWithSGD
from pyspark.mllib.regression import LabeledPoint
from pyspark.mllib.linalg import Vectors
from pyspark import SparkContext
from pyspark import SparkConf, SparkContext
from numpy import array
#Train the model using feature matrix
# Load and parse the data
def parsePoint(line):
values = [float(x) for x in line.split(' ')]
return LabeledPoint(values[0], values[1:])
#create spark Context
conf = (SparkConf()
.setMaster("local")
.setAppName("My app")
.set("spark.executor.memory", "1g"))
sc = SparkContext(conf = conf)
data = sc.textFile("myfile.txt")
parsedData = data.map(parsePoint)
#Train SVM model
model = SVMWithSGD.train(parsedData,100)
I get the following error:
14/11/15 22:38:38 INFO MemoryStore: ensureFreeSpace(32768) called with curMem=0, maxMem=278302556
14/11/15 22:38:38 INFO MemoryStore: Block broadcast_0 stored as values in memory (estimated size 32.0 KB, free 265.4 MB)
>>> parsedData = data.map(parsePoint)
>>> model = SVMWithSGD.train(parsedData,100)
14/11/15 22:39:12 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
14/11/15 22:39:12 WARN LoadSnappy: Snappy native library not loaded
14/11/15 22:39:12 INFO FileInputFormat: Total input paths to process : 1
14/11/15 22:39:13 INFO SparkContext: Starting job: runJob at PythonRDD.scala:296
14/11/15 22:39:13 INFO DAGScheduler: Got job 0 (runJob at PythonRDD.scala:296) with 1 output partitions (allowLocal=true)
14/11/15 22:39:13 INFO DAGScheduler: Final stage: Stage 0(runJob at PythonRDD.scala:296)
14/11/15 22:39:13 INFO DAGScheduler: Parents of final stage: List()
14/11/15 22:39:13 INFO DAGScheduler: Missing parents: List()
14/11/15 22:39:13 INFO DAGScheduler: Submitting Stage 0 (PythonRDD[3] at RDD at PythonRDD.scala:43), which has no missing parents
14/11/15 22:39:13 INFO MemoryStore: ensureFreeSpace(5088) called with curMem=32768, maxMem=278302556
14/11/15 22:39:13 INFO MemoryStore: Block broadcast_1 stored as values in memory (estimated size 5.0 KB, free 265.4 MB)
14/11/15 22:39:13 INFO DAGScheduler: Submitting 1 missing tasks from Stage 0 (PythonRDD[3] at RDD at PythonRDD.scala:43)
14/11/15 22:39:13 INFO TaskSchedulerImpl: Adding task set 0.0 with 1 tasks
14/11/15 22:39:13 INFO TaskSetManager: Starting task 0.0 in stage 0.0 (TID 0, localhost, PROCESS_LOCAL, 1221 bytes)
14/11/15 22:39:13 INFO Executor: Running task 0.0 in stage 0.0 (TID 0)
14/11/15 22:39:13 INFO HadoopRDD: Input split: file:/G:/SparkTest/spark-1.1.0/spark-1.1.0/bin/FeatureMatrix.txt:0+8103732
14/11/15 22:39:13 INFO PythonRDD: Times: total = 264, boot = 233, init = 29, finish = 2
14/11/15 22:39:13 ERROR PythonRDD: Python worker exited unexpectedly (crashed)
java.net.SocketException: Connection reset by peer: socket write error
at java.net.SocketOutputStream.socketWrite0(Native Method)
at java.net.SocketOutputStream.socketWrite(SocketOutputStream.java:113)
at java.net.SocketOutputStream.write(SocketOutputStream.java:159)
at java.io.BufferedOutputStream.flushBuffer(BufferedOutputStream.java:82)
at java.io.BufferedOutputStream.write(BufferedOutputStream.java:126)
at java.io.DataOutputStream.write(DataOutputStream.java:107)
at java.io.FilterOutputStream.write(FilterOutputStream.java:97)
at org.apache.spark.api.python.PythonRDD$.writeUTF(PythonRDD.scala:533)
at org.apache.spark.api.python.PythonRDD$$anonfun$writeIteratorToStream$2.apply(PythonRDD.scala:341)
at org.apache.spark.api.python.PythonRDD$$anonfun$writeIteratorToStream$2.apply(PythonRDD.scala:340)
at scala.collection.Iterator$class.foreach(Iterator.scala:727)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
at org.apache.spark.api.python.PythonRDD$.writeIteratorToStream(PythonRDD.scala:340)
at org.apache.spark.api.python.PythonRDD$WriterThread$$anonfun$run$1.apply$mcV$sp(PythonRDD.scala:209)
at org.apache.spark.api.python.PythonRDD$WriterThread$$anonfun$run$1.apply(PythonRDD.scala:184)
at org.apache.spark.api.python.PythonRDD$WriterThread$$anonfun$run$1.apply(PythonRDD.scala:184)
at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1311)
at org.apache.spark.api.python.PythonRDD$WriterThread.run(PythonRDD.scala:183)
14/11/15 22:39:13 ERROR PythonRDD: This may have been caused by a prior exception:
java.net.SocketException: Connection reset by peer: socket write error
at java.net.SocketOutputStream.socketWrite0(Native Method)
at java.net.SocketOutputStream.socketWrite(SocketOutputStream.java:113)
at java.net.SocketOutputStream.write(SocketOutputStream.java:159)
at java.io.BufferedOutputStream.flushBuffer(BufferedOutputStream.java:82)
at java.io.BufferedOutputStream.write(BufferedOutputStream.java:126)
at java.io.DataOutputStream.write(DataOutputStream.java:107)
at java.io.FilterOutputStream.write(FilterOutputStream.java:97)
at org.apache.spark.api.python.PythonRDD$.writeUTF(PythonRDD.scala:533)
at org.apache.spark.api.python.PythonRDD$$anonfun$writeIteratorToStream$2.apply(PythonRDD.scala:341)
at org.apache.spark.api.python.PythonRDD$$anonfun$writeIteratorToStream$2.apply(PythonRDD.scala:340)
at scala.collection.Iterator$class.foreach(Iterator.scala:727)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
at org.apache.spark.api.python.PythonRDD$.writeIteratorToStream(PythonRDD.scala:340)
at org.apache.spark.api.python.PythonRDD$WriterThread$$anonfun$run$1.apply$mcV$sp(PythonRDD.scala:209)
at org.apache.spark.api.python.PythonRDD$WriterThread$$anonfun$run$1.apply(PythonRDD.scala:184)
at org.apache.spark.api.python.PythonRDD$WriterThread$$anonfun$run$1.apply(PythonRDD.scala:184)
at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1311)
at org.apache.spark.api.python.PythonRDD$WriterThread.run(PythonRDD.scala:183)
14/11/15 22:39:13 ERROR Executor: Exception in task 0.0 in stage 0.0 (TID 0)
java.net.SocketException: Connection reset by peer: socket write error
at java.net.SocketOutputStream.socketWrite0(Native Method)
at java.net.SocketOutputStream.socketWrite(SocketOutputStream.java:113)
at java.net.SocketOutputStream.write(SocketOutputStream.java:159)
at java.io.BufferedOutputStream.flushBuffer(BufferedOutputStream.java:82)
at java.io.BufferedOutputStream.write(BufferedOutputStream.java:126)
at java.io.DataOutputStream.write(DataOutputStream.java:107)
at java.io.FilterOutputStream.write(FilterOutputStream.java:97)
at org.apache.spark.api.python.PythonRDD$.writeUTF(PythonRDD.scala:533)
at org.apache.spark.api.python.PythonRDD$$anonfun$writeIteratorToStream$2.apply(PythonRDD.scala:341)
at org.apache.spark.api.python.PythonRDD$$anonfun$writeIteratorToStream$2.apply(PythonRDD.scala:340)
at scala.collection.Iterator$class.foreach(Iterator.scala:727)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
at org.apache.spark.api.python.PythonRDD$.writeIteratorToStream(PythonRDD.scala:340)
at org.apache.spark.api.python.PythonRDD$WriterThread$$anonfun$run$1.apply$mcV$sp(PythonRDD.scala:209)
at org.apache.spark.api.python.PythonRDD$WriterThread$$anonfun$run$1.apply(PythonRDD.scala:184)
at org.apache.spark.api.python.PythonRDD$WriterThread$$anonfun$run$1.apply(PythonRDD.scala:184)
at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1311)
at org.apache.spark.api.python.PythonRDD$WriterThread.run(PythonRDD.scala:183)
14/11/15 22:39:13 WARN TaskSetManager: Lost task 0.0 in stage 0.0 (TID 0, localhost): java.net.SocketException: Connection reset by peer: socket write error
java.net.SocketOutputStream.socketWrite0(Native Method)
java.net.SocketOutputStream.socketWrite(SocketOutputStream.java:113)
java.net.SocketOutputStream.write(SocketOutputStream.java:159)
java.io.BufferedOutputStream.flushBuffer(BufferedOutputStream.java:82)
java.io.BufferedOutputStream.write(BufferedOutputStream.java:126)
java.io.DataOutputStream.write(DataOutputStream.java:107)
java.io.FilterOutputStream.write(FilterOutputStream.java:97)
org.apache.spark.api.python.PythonRDD$.writeUTF(PythonRDD.scala:533)
org.apache.spark.api.python.PythonRDD$$anonfun$writeIteratorToStream$2.apply(PythonRDD.scala:341)
org.apache.spark.api.python.PythonRDD$$anonfun$writeIteratorToStream$2.apply(PythonRDD.scala:340)
scala.collection.Iterator$class.foreach(Iterator.scala:727)
scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
org.apache.spark.api.python.PythonRDD$.writeIteratorToStream(PythonRDD.scala:340)
org.apache.spark.api.python.PythonRDD$WriterThread$$anonfun$run$1.apply$mcV$sp(PythonRDD.scala:209)
org.apache.spark.api.python.PythonRDD$WriterThread$$anonfun$run$1.apply(PythonRDD.scala:184)
org.apache.spark.api.python.PythonRDD$WriterThread$$anonfun$run$1.apply(PythonRDD.scala:184)
org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1311)
org.apache.spark.api.python.PythonRDD$WriterThread.run(PythonRDD.scala:183)
14/11/15 22:39:13 ERROR TaskSetManager: Task 0 in stage 0.0 failed 1 times; aborting job
14/11/15 22:39:13 INFO TaskSchedulerImpl: Removed TaskSet 0.0, whose tasks have all completed, from pool
14/11/15 22:39:13 INFO TaskSchedulerImpl: Cancelling stage 0
14/11/15 22:39:13 INFO DAGScheduler: Failed to run runJob at PythonRDD.scala:296
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "G:\SparkTest\spark-1.1.0\spark-1.1.0\python\pyspark\mllib\classification.py", line 178, in train
return _regression_train_wrapper(sc, train_func, SVMModel, data, initialWeights)
File "G:\SparkTest\spark-1.1.0\spark-1.1.0\python\pyspark\mllib\_common.py", line 430, in _regression_train_wrapper
initial_weights = _get_initial_weights(initial_weights, data)
File "G:\SparkTest\spark-1.1.0\spark-1.1.0\python\pyspark\mllib\_common.py", line 415, in _get_initial_weights
initial_weights = _convert_vector(data.first().features)
File "G:\SparkTest\spark-1.1.0\spark-1.1.0\python\pyspark\rdd.py", line 1167, in first
return self.take(1)[0]
File "G:\SparkTest\spark-1.1.0\spark-1.1.0\python\pyspark\rdd.py", line 1153, in take
res = self.context.runJob(self, takeUpToNumLeft, p, True)
File "G:\SparkTest\spark-1.1.0\spark-1.1.0\python\pyspark\context.py", line 770, in runJob
it = self._jvm.PythonRDD.runJob(self._jsc.sc(), mappedRDD._jrdd, javaPartitions, allowLocal)
File "G:\SparkTest\spark-1.1.0\spark-1.1.0\python\lib\py4j-0.8.2.1-src.zip\py4j\java_gateway.py", line 538, in __call__
File "G:\SparkTest\spark-1.1.0\spark-1.1.0\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 z:org.apache.spark.api.python.PythonRDD.runJob.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 0.0 failed 1 times, most recent failure: Lost task 0.0 in stage 0.0 (TID 0, lo
host): java.net.SocketException: Connection reset by peer: socket write error
java.net.SocketOutputStream.socketWrite0(Native Method)
java.net.SocketOutputStream.socketWrite(SocketOutputStream.java:113)
java.net.SocketOutputStream.write(SocketOutputStream.java:159)
java.io.BufferedOutputStream.flushBuffer(BufferedOutputStream.java:82)
java.io.BufferedOutputStream.write(BufferedOutputStream.java:126)
java.io.DataOutputStream.write(DataOutputStream.java:107)
java.io.FilterOutputStream.write(FilterOutputStream.java:97)
org.apache.spark.api.python.PythonRDD$.writeUTF(PythonRDD.scala:533)
org.apache.spark.api.python.PythonRDD$$anonfun$writeIteratorToStream$2.apply(PythonRDD.scala:341)
org.apache.spark.api.python.PythonRDD$$anonfun$writeIteratorToStream$2.apply(PythonRDD.scala:340)
scala.collection.Iterator$class.foreach(Iterator.scala:727)
scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
org.apache.spark.api.python.PythonRDD$.writeIteratorToStream(PythonRDD.scala:340)
org.apache.spark.api.python.PythonRDD$WriterThread$$anonfun$run$1.apply$mcV$sp(PythonRDD.scala:209)
org.apache.spark.api.python.PythonRDD$WriterThread$$anonfun$run$1.apply(PythonRDD.scala:184)
org.apache.spark.api.python.PythonRDD$WriterThread$$anonfun$run$1.apply(PythonRDD.scala:184)
org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1311)
org.apache.spark.api.python.PythonRDD$WriterThread.run(PythonRDD.scala:183)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1185)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1174)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1173)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1173)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:688)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:688)
at scala.Option.foreach(Option.scala:236)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:688)
at org.apache.spark.scheduler.DAGSchedulerEventProcessActor$$anonfun$receive$2.applyOrElse(DAGScheduler.scala:1391)
at akka.actor.ActorCell.receiveMessage(ActorCell.scala:498)
at akka.actor.ActorCell.invoke(ActorCell.scala:456)
at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:237)
at akka.dispatch.Mailbox.run(Mailbox.scala:219)
at akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:386)
at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
at scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
at scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
at scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
>>> 14/11/15 23:22:52 INFO BlockManager: Removing broadcast 1
14/11/15 23:22:52 INFO BlockManager: Removing block broadcast_1
14/11/15 23:22:52 INFO MemoryStore: Block broadcast_1 of size 5088 dropped from memory (free 278269788)
14/11/15 23:22:52 INFO ContextCleaner: Cleaned broadcast 1
Regards,
Mrutyunjay

Answer 1

It's so simple.
conf = SparkConf().setMaster("local").setAppName("RatingsHistogram")
sc = SparkContext(conf = conf)
lines = sc.textFile("file:///SparkCourse/filter_1.csv",2000)
print lines.first()
while using sc.textfile add one more parameters for the number of divisions to a large value.
The bigger the data the larger the value.

Answer 2

Mrutynjay,
Though I do not have definitive answer. The issue looks like something related to the memory. I also encountered the same issue when trying to read a file of 5 MB. I deleted a portion of the file and and reduced to less than 1 MB and the code worked.
I also found something on the same issue here in the below site as well.
http://apache-spark-user-list.1001560.n3.nabble.com/pyspark-Failed-to-run-first-td7691.html

Answer 3

I had a similar problem, I tried something like:
numPartitions = a number for example 10 or 100
data = sc.textFile("myfile.txt",numPartitions)
Inspired by: How to repartition evenly in Spark? or here: https://databricks.gitbooks.io/databricks-spark-knowledge-base/content/performance_optimization/how_many_partitions_does_an_rdd_have.html

Answer 4

I got the same error,then i got an releated answer from pyspark process big datasets problems
the solution is add some code python/pyspark/worker.py
Add the following 2 lines to the end of the process function defined inside the main function
for obj in iterator:
pass
so the process function now looks like this (in spark 1.5.2 at least):
def process():
iterator = deserializer.load_stream(infile)
serializer.dump_stream(func(split_index, iterator), outfile)
for obj in iterator:
pass
and this works for me.

Answer 5

One possibility is that there is an exception in parsePoint, wrap
the code in a try except block and print out the exception.
Check your --driver-memory parameter, make it greater.