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https://issues.apache.org/jira/browse/SPARK-15378?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15288665#comment-15288665
]
Nick Pentreath edited comment on SPARK-15378 at 5/18/16 9:17 AM:
-----------------------------------------------------------------
If you are trying to run on a cluster, then either the library needs to be
installed on each worker node, or you can distribute libraries using the
{{--py-files}} option of {{spark-submit}}. Please see [submitting applications
guide|http://spark.apache.org/docs/latest/submitting-applications.html#advanced-dependency-management]
for details.
was (Author: mlnick):
If you are trying to run on a cluster, then either the library needs to be
installed on each worker node, or you can distribute libaries using the
{{--py-files}} option of {{spark-submit}}. Please see [submitting applications
guide|http://spark.apache.org/docs/latest/submitting-applications.html#advanced-dependency-management]
for details.
> Unable to load NLTK in spark RDD pipeline
> ------------------------------------------
>
> Key: SPARK-15378
> URL: https://issues.apache.org/jira/browse/SPARK-15378
> Project: Spark
> Issue Type: Bug
> Components: PySpark, Spark Core
> Environment: spark version 1.6.1
> Reporter: Krishna Prasad
> Labels: RDD, spark, spark-submit
>
> h1.Info:
> * spark version 1.6.1
> * python version 2.7.9
> * I have install NLTK and its working fine with the following code, I am
> running in *pyspark shell*
> {code}
> >>> from nltk.tokenize import word_tokenize
> >>> text = "Hello, this is testing of nltk in pyspark, mainly
> word_tokenize functions in nltk.tokenize, working fine with PySpark, please
> see the below example"
> >>> text
> //'Hello, this is testing of nltk in pyspark, mainly word_tokenize
> functions in nltk.tokenize, working fine with PySpark, please see the below
> example'
> >>> word_token = word_tokenize(text)
> >>> word_token
> //['Hello', ',', 'this', 'is', 'testing', 'of', 'nltk', 'in',
> 'pyspark', ',', 'mainly', 'word_tokenize', 'functions', 'in',
> 'nltk.tokenize', ',', 'working', 'fine', 'with', 'PySpark', ',', 'please',
> 'see', 'the', 'below', 'example']
> >>>
> {code}
> h1.Problem:
> When I try to run it using spark in-build method `map` its throwing an error
> *ImportError: No module named nltk.tokenize*
> {code}
> >>> from nltk.tokenize import word_tokenize
> >>> rdd = sc.parallelize(["This is first sentence for tokenization",
> "second line, we need to tokenize"])
> >> rdd_tokens = rdd.map(lambda sentence : word_tokenize(sentence))
> >> rdd_tokens
> // PythonRDD[2] at RDD at PythonRDD.scala:43
> >>> rdd_tokens.collect()
> {code}
> h2. Fullstack errors:
> {code}
> >>> from nltk.tokenize import word_tokenize
> >>> rdd = sc.parallelize(["This is first sentence for tokenization",
> "second line, we need to tokenize"])
> >> rdd_tokens = rdd.map(lambda sentence : word_tokenize(sentence))
> >> rdd_tokens
> // PythonRDD[2] at RDD at PythonRDD.scala:43
> >>> rdd_tokens.collect()
> 16/05/17 17:06:48 WARN
> org.apache.spark.scheduler.TaskSetManager: Lost task 0.0 in stage 2.0 (TID
> 16, spark-w-0.c.clean-feat-131014.internal):
> org.apache.spark.api.python.PythonException: Traceback (most recent call
> last):
> File "/usr/lib/spark/python/pyspark/worker.py", line 98, in
> main
> command = pickleSer._read_with_length(infile)
> File "/usr/lib/spark/python/pyspark/serializers.py", line
> 164, in _read_with_length
> return self.loads(obj)
> File "/usr/lib/spark/python/pyspark/serializers.py", line
> 422, in loads
> return pickle.loads(obj)
> ImportError: No module named nltk.tokenize
> at
> org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:166)
> at
> org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:207)
> at
> org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:125)
> at
> org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:70)
> at
> org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
> at
> org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
> at org.apache.spark.scheduler.Task.run(Task.scala:89)
> at
> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
> at java.lang.Thread.run(Thread.java:745)
> 16/05/17 17:06:49 ERROR
> org.apache.spark.scheduler.TaskSetManager: Task 0 in stage 2.0 failed 4
> times; aborting job
> 16/05/17 17:06:49 WARN
> org.apache.spark.scheduler.TaskSetManager: Lost task 1.3 in stage 2.0 (TID
> 23, spark-w-0.c.clean-feat-131014.internal):
> org.apache.spark.TaskKilledException
> at
> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:204)
> 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)
> Traceback (most recent call last):
> File "<stdin>", line 1, in <module>
> File "/usr/lib/spark/python/pyspark/rdd.py", line 771, in
> collect
> port =
> self.ctx._jvm.PythonRDD.collectAndServe(self._jrdd.rdd())
> File
> "/usr/lib/spark/python/lib/py4j-0.9-src.zip/py4j/java_gateway.py", line 813,
> in __call__
> File "/usr/lib/spark/python/pyspark/sql/utils.py", line 45,
> in deco
> return f(*a, **kw)
> File
> "/usr/lib/spark/python/lib/py4j-0.9-src.zip/py4j/protocol.py", line 308, in
> get_return_value
> py4j.protocol.Py4JJavaError: An error occurred while calling
> z:org.apache.spark.api.python.PythonRDD.collectAndServe.
> : org.apache.spark.SparkException: Job aborted due to stage
> failure: Task 0 in stage 2.0 failed 4 times, most recent failure: Lost task
> 0.3 in stage 2.0 (TID 22, spark-w-0.c.clean-feat-131014.internal):
> org.apache.spark.api.python.PythonException: Traceback (most recent call
> last):
> File "/usr/lib/spark/python/pyspark/worker.py", line 98, in
> main
> command = pickleSer._read_with_length(infile)
> File "/usr/lib/spark/python/pyspark/serializers.py", line
> 164, in _read_with_length
> return self.loads(obj)
> File "/usr/lib/spark/python/pyspark/serializers.py", line
> 422, in loads
> return pickle.loads(obj)
> ImportError: No module named nltk.tokenize
> at
> org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:166)
> at
> org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:207)
> at
> org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:125)
> at
> org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:70)
> at
> org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
> at
> org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
> at org.apache.spark.scheduler.Task.run(Task.scala:89)
> at
> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
> at java.lang.Thread.run(Thread.java:745)
> Driver stacktrace:
> at
> org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1431)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1419)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1418)
> at
> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> at
> scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
> at
> org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1418)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:799)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:799)
> at scala.Option.foreach(Option.scala:236)
> at
> org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:799)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1640)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1599)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1588)
> at
> org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
> at
> org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:620)
> at
> org.apache.spark.SparkContext.runJob(SparkContext.scala:1832)
> at
> org.apache.spark.SparkContext.runJob(SparkContext.scala:1845)
> at
> org.apache.spark.SparkContext.runJob(SparkContext.scala:1858)
> at
> org.apache.spark.SparkContext.runJob(SparkContext.scala:1929)
> at
> org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:927)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:111)
> at org.apache.spark.rdd.RDD.withScope(RDD.scala:316)
> at org.apache.spark.rdd.RDD.collect(RDD.scala:926)
> at
> org.apache.spark.api.python.PythonRDD$.collectAndServe(PythonRDD.scala:405)
> at
> org.apache.spark.api.python.PythonRDD.collectAndServe(PythonRDD.scala)
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native
> Method)
> at
> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
> at
> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:498)
> at
> py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:231)
> at
> py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:381)
> at py4j.Gateway.invoke(Gateway.java:259)
> at
> py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:133)
> at
> py4j.commands.CallCommand.execute(CallCommand.java:79)
> at
> py4j.GatewayConnection.run(GatewayConnection.java:209)
> at java.lang.Thread.run(Thread.java:745)
> Caused by: org.apache.spark.api.python.PythonException:
> Traceback (most recent call last):
> File "/usr/lib/spark/python/pyspark/worker.py", line 98, in
> main
> command = pickleSer._read_with_length(infile)
> File "/usr/lib/spark/python/pyspark/serializers.py", line
> 164, in _read_with_length
> return self.loads(obj)
> File "/usr/lib/spark/python/pyspark/serializers.py", line
> 422, in loads
> return pickle.loads(obj)
> ImportError: No module named nltk.tokenize
> at
> org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:166)
> at
> org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:207)
> at
> org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:125)
> at
> org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:70)
> at
> org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
> at
> org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
> at org.apache.spark.scheduler.Task.run(Task.scala:89)
> at
> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
> ... 1 more
> >>>
> {code}
> h1.Main issue at:
> {code}
> File "/usr/lib/spark/python/pyspark/serializers.py", line 422, in loads
> return pickle.loads(obj)
> ImportError: No module named nltk.tokenize
> {code}
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