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examples/src/main/python/mllib/kmeans.py
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HyukjinKwon
[SPARK-32138] Drop Python 2.7, 3.4 and 3.5
14 июл 2020, 05:22
14 июл 2020, 05:22
4ad9bfd
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# # Licensed to the Apache Software Foundation (ASF) under one or more # contributor license agreements. See the NOTICE file distributed with # this work for additional information regarding copyright ownership. # The ASF licenses this file to You under the Apache License, Version 2.0 # (the "License"); you may not use this file except in compliance with # the License. You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # """ A K-means clustering program using MLlib. This example requires NumPy (http://www.numpy.org/). """ import sys import numpy as np from pyspark import SparkContext from pyspark.mllib.clustering import KMeans def parseVector(line): return np.array([float(x) for x in line.split(' ')]) if __name__ == "__main__": if len(sys.argv) != 3: print("Usage: kmeans <file> <k>", file=sys.stderr) sys.exit(-1) sc = SparkContext(appName="KMeans") lines = sc.textFile(sys.argv[1]) data = lines.map(parseVector) k = int(sys.argv[2]) model = KMeans.train(data, k) print("Final centers: " + str(model.clusterCenters)) print("Total Cost: " + str(model.computeCost(data))) sc.stop()