| # |
| # 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 streaming word-counting workflow. |
| """ |
| |
| from __future__ import absolute_import |
| |
| import argparse |
| import logging |
| |
| from past.builtins import unicode |
| |
| import apache_beam as beam |
| import apache_beam.transforms.window as window |
| from apache_beam.examples.wordcount import WordExtractingDoFn |
| from apache_beam.options.pipeline_options import PipelineOptions |
| from apache_beam.options.pipeline_options import SetupOptions |
| from apache_beam.options.pipeline_options import StandardOptions |
| |
| |
| def run(argv=None): |
| """Build and run the pipeline.""" |
| parser = argparse.ArgumentParser() |
| parser.add_argument( |
| '--output_topic', required=True, |
| help=('Output PubSub topic of the form ' |
| '"projects/<PROJECT>/topic/<TOPIC>".')) |
| group = parser.add_mutually_exclusive_group(required=True) |
| group.add_argument( |
| '--input_topic', |
| help=('Input PubSub topic of the form ' |
| '"projects/<PROJECT>/topics/<TOPIC>".')) |
| group.add_argument( |
| '--input_subscription', |
| help=('Input PubSub subscription of the form ' |
| '"projects/<PROJECT>/subscriptions/<SUBSCRIPTION>."')) |
| known_args, pipeline_args = parser.parse_known_args(argv) |
| |
| # We use the save_main_session option because one or more DoFn's in this |
| # workflow rely on global context (e.g., a module imported at module level). |
| pipeline_options = PipelineOptions(pipeline_args) |
| pipeline_options.view_as(SetupOptions).save_main_session = True |
| pipeline_options.view_as(StandardOptions).streaming = True |
| p = beam.Pipeline(options=pipeline_options) |
| |
| # Read from PubSub into a PCollection. |
| if known_args.input_subscription: |
| messages = (p |
| | beam.io.ReadFromPubSub( |
| subscription=known_args.input_subscription) |
| .with_output_types(bytes)) |
| else: |
| messages = (p |
| | beam.io.ReadFromPubSub(topic=known_args.input_topic) |
| .with_output_types(bytes)) |
| |
| lines = messages | 'decode' >> beam.Map(lambda x: x.decode('utf-8')) |
| |
| # Count the occurrences of each word. |
| def count_ones(word_ones): |
| (word, ones) = word_ones |
| return (word, sum(ones)) |
| |
| counts = (lines |
| | 'split' >> (beam.ParDo(WordExtractingDoFn()) |
| .with_output_types(unicode)) |
| | 'pair_with_one' >> beam.Map(lambda x: (x, 1)) |
| | beam.WindowInto(window.FixedWindows(15, 0)) |
| | 'group' >> beam.GroupByKey() |
| | 'count' >> beam.Map(count_ones)) |
| |
| # Format the counts into a PCollection of strings. |
| def format_result(word_count): |
| (word, count) = word_count |
| return '%s: %d' % (word, count) |
| |
| output = (counts |
| | 'format' >> beam.Map(format_result) |
| | 'encode' >> beam.Map(lambda x: x.encode('utf-8')) |
| .with_output_types(bytes)) |
| |
| # Write to PubSub. |
| # pylint: disable=expression-not-assigned |
| output | beam.io.WriteToPubSub(known_args.output_topic) |
| |
| result = p.run() |
| result.wait_until_finish() |
| |
| |
| if __name__ == '__main__': |
| logging.getLogger().setLevel(logging.INFO) |
| run() |