| # |
| # 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 word-counting workflow that uses the SQL transform. |
| |
| A Java version supported by Beam must be installed locally to run this pipeline. |
| Additionally, Docker must also be available to run this pipeline locally. |
| """ |
| |
| import argparse |
| import logging |
| import re |
| import typing |
| |
| import apache_beam as beam |
| from apache_beam import coders |
| from apache_beam.io import ReadFromText |
| from apache_beam.io import WriteToText |
| from apache_beam.options.pipeline_options import PipelineOptions |
| from apache_beam.options.pipeline_options import SetupOptions |
| from apache_beam.runners.portability import portable_runner |
| from apache_beam.transforms.sql import SqlTransform |
| |
| # The input to SqlTransform must be a PCollection(s) of known schema. |
| # One way to create such a PCollection is to produce a PCollection of |
| # NamedTuple registered with the RowCoder. |
| # |
| # Here we create and register a simple NamedTuple with a single str typed |
| # field named 'word' which we will use below. |
| MyRow = typing.NamedTuple('MyRow', [('word', str)]) |
| coders.registry.register_coder(MyRow, coders.RowCoder) |
| |
| |
| def run(p, input_file, output_file): |
| #pylint: disable=expression-not-assigned |
| ( |
| p |
| # Read the lines from a text file. |
| | 'Read' >> ReadFromText(input_file) |
| # Split the line into individual words. |
| | 'Split' >> beam.FlatMap(lambda line: re.split(r'\W+', line)) |
| # Map each word to an instance of MyRow. |
| | 'ToRow' >> beam.Map(MyRow).with_output_types(MyRow) |
| # SqlTransform yields a PCollection containing elements with attributes |
| # based on the output of the query. |
| | 'Sql!!' >> SqlTransform( |
| """ |
| SELECT |
| word as key, |
| COUNT(*) as `count` |
| FROM PCOLLECTION |
| GROUP BY word""") |
| | 'Format' >> beam.Map(lambda row: '{}: {}'.format(row.key, row.count)) |
| | 'Write' >> WriteToText(output_file)) |
| |
| |
| def main(): |
| logging.getLogger().setLevel(logging.INFO) |
| |
| parser = argparse.ArgumentParser() |
| parser.add_argument( |
| '--input', |
| dest='input', |
| default='gs://dataflow-samples/shakespeare/kinglear.txt', |
| help='Input file to process.') |
| parser.add_argument( |
| '--output', |
| dest='output', |
| required=True, |
| help='Output file to write results to.') |
| |
| known_args, pipeline_args = parser.parse_known_args() |
| |
| pipeline_options = PipelineOptions(pipeline_args) |
| |
| # 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.view_as(SetupOptions).save_main_session = True |
| |
| with beam.Pipeline(options=pipeline_options) as p: |
| if isinstance(p.runner, portable_runner.PortableRunner): |
| # Preemptively start due to BEAM-6666. |
| p.runner.create_job_service(pipeline_options) |
| |
| run(p, known_args.input, known_args.output) |
| |
| |
| # Some more fun queries: |
| # ------ |
| # SELECT |
| # word as key, |
| # COUNT(*) as `count` |
| # FROM PCOLLECTION |
| # GROUP BY word |
| # ORDER BY `count` DESC |
| # LIMIT 100 |
| # ------ |
| # SELECT |
| # len as key, |
| # COUNT(*) as `count` |
| # FROM ( |
| # SELECT |
| # LENGTH(word) AS len |
| # FROM PCOLLECTION |
| # ) |
| # GROUP BY len |
| |
| if __name__ == '__main__': |
| main() |