github.com/apache/beam/sdks/v2@v2.48.2/python/apache_beam/examples/matrix_power.py (about) 1 # 2 # Licensed to the Apache Software Foundation (ASF) under one or more 3 # contributor license agreements. See the NOTICE file distributed with 4 # this work for additional information regarding copyright ownership. 5 # The ASF licenses this file to You under the Apache License, Version 2.0 6 # (the "License"); you may not use this file except in compliance with 7 # the License. You may obtain a copy of the License at 8 # 9 # http://www.apache.org/licenses/LICENSE-2.0 10 # 11 # Unless required by applicable law or agreed to in writing, software 12 # distributed under the License is distributed on an "AS IS" BASIS, 13 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 14 # See the License for the specific language governing permissions and 15 # limitations under the License. 16 # 17 18 """An example that computes the matrix power y = A^m * v. 19 20 A is square matrix and v is a given vector with appropriate dimension. 21 22 In this computation, each element of the matrix is represented by ((i,j), a) 23 where a is the element in the i-th row and j-th column. Each element of the 24 vector is computed as a PCollection (i, v) where v is the element of the i-th 25 row. For multiplication, the vector is converted into a dict side input. 26 """ 27 28 import argparse 29 import logging 30 31 import apache_beam as beam 32 from apache_beam.options.pipeline_options import PipelineOptions 33 from apache_beam.testing.test_pipeline import TestPipeline 34 35 36 def extract_matrix(line): 37 tokens = line.split(':') 38 row = int(tokens[0]) 39 numbers = tokens[1].strip().split() 40 for column, number in enumerate(numbers): 41 yield ((row, column), float(number)) 42 43 44 def extract_vector(line): 45 return enumerate(map(float, line.split())) 46 47 48 def multiply_elements(element, vector): 49 ((row, col), value) = element 50 return (row, value * vector[col]) 51 52 53 def run(argv=None): 54 parser = argparse.ArgumentParser() 55 parser.add_argument( 56 '--input_matrix', required=True, help='Input file containing the matrix.') 57 parser.add_argument( 58 '--input_vector', 59 required=True, 60 help='Input file containing initial vector.') 61 parser.add_argument( 62 '--output', required=True, help='Output file to write results to.') 63 parser.add_argument( 64 '--exponent', 65 required=True, 66 type=int, 67 help='Exponent of input square matrix.') 68 known_args, pipeline_args = parser.parse_known_args(argv) 69 70 p = TestPipeline(options=PipelineOptions(pipeline_args)) 71 72 # Read the matrix from the input file and extract into the ((i,j), a) format. 73 matrix = ( 74 p | 'read matrix' >> beam.io.ReadFromText(known_args.input_matrix) 75 | 'extract matrix' >> beam.FlatMap(extract_matrix)) 76 77 # Read and extract the vector from its input file. 78 vector = ( 79 p | 'read vector' >> beam.io.ReadFromText(known_args.input_vector) 80 | 'extract vector' >> beam.FlatMap(extract_vector)) 81 82 for i in range(known_args.exponent): 83 # Multiply the matrix by the current vector once, 84 # and keep the resulting vector for the next iteration. 85 vector = ( 86 matrix 87 # Convert vector into side-input dictionary, compute the product. 88 | 'multiply elements %d' % i >> beam.Map( 89 multiply_elements, beam.pvalue.AsDict(vector)) 90 | 'sum element products %d' % i >> beam.CombinePerKey(sum)) 91 92 # Format and output final vector. 93 _ = ( 94 vector # pylint: disable=expression-not-assigned 95 | 'format' >> beam.Map(repr) 96 | 'write' >> beam.io.WriteToText(known_args.output)) 97 98 p.run() 99 100 101 if __name__ == '__main__': 102 logging.getLogger().setLevel(logging.INFO) 103 run()