Hi All,
I am trying to run KMeans clustering on a large data set with 12,000 points
and 80,000 dimensions. I have a spark cluster in Ec2 stand alone mode with
8 workers running on 2 slaves with 160 GB Ram and 40 VCPU.
*My Code is as Follows:*
def convert_into_sparse_vector(A):
non_nan_indices=np.nonzero(~np.isnan(A) )
non_nan_values=A[non_nan_indices]
dictionary=dict(zip(non_nan_indices[0],non_nan_values))
return Vectors.sparse (len(A),dictionary)
X=[convert_into_sparse_vector(A) for A in complete_dataframe.values ]
sc=SparkContext(appName="parallel_kmeans")
data=sc.parallelize(X,10)
model = KMeans.train(data, 1000, initializationMode="k-means||")
where complete_dataframe is a pandas data frame that has my data.
I get the error: Py4JNetworkError: An error occurred while trying to connect
to the Java server.
/
The error trace is as follows:
> ---------------------------------------- Exception happened during
> processing of request from ('127.0.0.1', 41360) Traceback (most recent
> call last): File "/usr/lib64/python2.6/SocketServer.py", line 283,
> in _handle_request_noblock
> self.process_request(request, client_address) File
> "/usr/lib64/python2.6/SocketServer.py", line 309, in process_request
> self.finish_request(request, client_address) File
> "/usr/lib64/python2.6/SocketServer.py", line 322, in finish_request
> self.RequestHandlerClass(request, client_address, self) File
> "/usr/lib64/python2.6/SocketServer.py", line 617, in __init__
> self.handle() File "/root/spark/python/pyspark/accumulators.py",
> line 235, in handle
> num_updates = read_int(self.rfile) File
> "/root/spark/python/pyspark/serializers.py", line 544, in read_int
> raise EOFError EOFError
> ----------------------------------------
> ---------------------------------------------------------------------------
> Py4JNetworkError Traceback (most recent call
> last) <ipython-input-13-3dd00c2c5e93> in <module>()
> ----> 1 model = KMeans.train(data, 1000, initializationMode="k-means||")
>
> /root/spark/python/pyspark/mllib/clustering.pyc in train(cls, rdd, k,
> maxIterations, runs, initializationMode, seed, initializationSteps,
> epsilon)
> 134 """Train a k-means clustering model."""
> 135 model = callMLlibFunc("trainKMeansModel",
> rdd.map(_convert_to_vector), k, maxIterations,
> --> 136 runs, initializationMode, seed,
> initializationSteps, epsilon)
> 137 centers = callJavaFunc(rdd.context, model.clusterCenters)
> 138 return KMeansModel([c.toArray() for c in centers])
>
> /root/spark/python/pyspark/mllib/common.pyc in callMLlibFunc(name,
> *args)
> 126 sc = SparkContext._active_spark_context
> 127 api = getattr(sc._jvm.PythonMLLibAPI(), name)
> --> 128 return callJavaFunc(sc, api, *args)
> 129
> 130
>
> /root/spark/python/pyspark/mllib/common.pyc in callJavaFunc(sc, func,
> *args)
> 119 """ Call Java Function """
> 120 args = [_py2java(sc, a) for a in args]
> --> 121 return _java2py(sc, func(*args))
> 122
> 123
>
> /root/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/java_gateway.py in
> __call__(self, *args)
> 534 END_COMMAND_PART
> 535
> --> 536 answer = self.gateway_client.send_command(command)
> 537 return_value = get_return_value(answer,
> self.gateway_client,
> 538 self.target_id, self.name)
>
> /root/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/java_gateway.py in
> send_command(self, command, retry)
> 367 if retry:
> 368 #print_exc()
> --> 369 response = self.send_command(command)
> 370 else:
> 371 response = ERROR
>
> /root/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/java_gateway.py in
> send_command(self, command, retry)
> 360 the Py4J protocol.
> 361 """
> --> 362 connection = self._get_connection()
> 363 try:
> 364 response = connection.send_command(command)
>
> /root/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/java_gateway.py in
> _get_connection(self)
> 316 connection = self.deque.pop()
> 317 except Exception:
> --> 318 connection = self._create_connection()
> 319 return connection
> 320
>
> /root/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/java_gateway.py in
> _create_connection(self)
> 323 connection = GatewayConnection(self.address, self.port,
> 324 self.auto_close, self.gateway_property)
> --> 325 connection.start()
> 326 return connection
> 327
>
> /root/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/java_gateway.py in
> start(self)
> 430 'server'
> 431 logger.exception(msg)
> --> 432 raise Py4JNetworkError(msg)
> 433
> 434 def close(self):
>
> Py4JNetworkError: An error occurred while trying to connect to the
> Java server/
Please let me know if I am missing something.
Thanks and Regards,
Rogers Jeffrey L
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