python/mllib/elementwise_product_example.py

0001 #
0002 # Licensed to the Apache Software Foundation (ASF) under one or more
0003 # contributor license agreements.  See the NOTICE file distributed with
0004 # this work for additional information regarding copyright ownership.
0005 # The ASF licenses this file to You under the Apache License, Version 2.0
0006 # (the "License"); you may not use this file except in compliance with
0007 # the License.  You may obtain a copy of the License at
0008 #
0009 #    http://www.apache.org/licenses/LICENSE-2.0
0010 #
0011 # Unless required by applicable law or agreed to in writing, software
0012 # distributed under the License is distributed on an "AS IS" BASIS,
0013 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
0014 # See the License for the specific language governing permissions and
0015 # limitations under the License.
0016 #
0017
0018 from __future__ import print_function
0019
0020 from pyspark import SparkContext
0021 # $example on$
0022 from pyspark.mllib.feature import ElementwiseProduct
0023 from pyspark.mllib.linalg import Vectors
0024 # $example off$
0025
0026 if __name__ == "__main__":
0027     sc = SparkContext(appName="ElementwiseProductExample")  # SparkContext
0028
0029     # $example on$
0030     data = sc.textFile("data/mllib/kmeans_data.txt")
0031     parsedData = data.map(lambda x: [float(t) for t in x.split(" ")])
0032
0033     # Create weight vector.
0034     transformingVector = Vectors.dense([0.0, 1.0, 2.0])
0035     transformer = ElementwiseProduct(transformingVector)
0036
0037     # Batch transform
0038     transformedData = transformer.transform(parsedData)
0039     # Single-row transform
0040     transformedData2 = transformer.transform(parsedData.first())
0041     # $example off$
0042
0043     print("transformedData:")
0044     for each in transformedData.collect():
0045         print(each)
0046
0047     print("transformedData2:")
0048     for each in transformedData2:
0049         print(each)
0050
0051     sc.stop()