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From "Sean Owen (JIRA)" <j...@apache.org>
Subject [jira] [Resolved] (SPARK-15378) Unable to load NLTK in spark RDD pipeline
Date Wed, 18 May 2016 09:01:12 GMT

     [ https://issues.apache.org/jira/browse/SPARK-15378?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Sean Owen resolved SPARK-15378.
-------------------------------
    Resolution: Not A Problem

You don't have nltk installed on your executors, it seems.

>  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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