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examples/src/main/python/mllib/stratified_sampling_example.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. # from pyspark import SparkContext if __name__ == "__main__": sc = SparkContext(appName="StratifiedSamplingExample") # SparkContext # $example on$ # an RDD of any key value pairs data = sc.parallelize([(1, 'a'), (1, 'b'), (2, 'c'), (2, 'd'), (2, 'e'), (3, 'f')]) # specify the exact fraction desired from each key as a dictionary fractions = {1: 0.1, 2: 0.6, 3: 0.3} approxSample = data.sampleByKey(False, fractions) # $example off$ for each in approxSample.collect(): print(each) sc.stop()