damccorm commented on code in PR #33297: URL: https://github.com/apache/beam/pull/33297#discussion_r1873922597
########## sdks/python/apache_beam/testing/benchmarks/wordcount/wordcount.py: ########## @@ -0,0 +1,39 @@ +# +# 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. +# +# pytype: skip-file + +import logging + +from apache_beam.examples import wordcount_with_return +from apache_beam.testing.load_tests.dataflow_cost_benchmark import DataflowCostBenchmark + + +class WordcountCostBenchmark(DataflowCostBenchmark): + def __init__(self): + super().__init__() + + def test(self): + extra_opts = {} + extra_opts['output'] = self.pipeline.get_option('output_file') + self.result = wordcount_with_return.run( + self.pipeline.get_full_options_as_args(**extra_opts), + save_main_session=False) Review Comment: Love how easy this is. ########## sdks/python/apache_beam/examples/wordcount_with_return.py: ########## @@ -0,0 +1,98 @@ +# +# 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.""" + +# pytype: skip-file + +import argparse +import logging +import re + +import apache_beam as beam +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.runner import PipelineResult + + +class WordExtractingDoFn(beam.DoFn): + """Parse each line of input text into words.""" + def process(self, element): + """Returns an iterator over the words of this element. + + The element is a line of text. If the line is blank, note that, too. + + Args: + element: the element being processed + + Returns: + The processed element. + """ + return re.findall(r'[\w\']+', element, re.UNICODE) + + +def run(argv=None, save_main_session=True) -> PipelineResult: + """Main entry point; defines and runs the wordcount pipeline.""" + 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(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 = save_main_session + + pipeline = beam.Pipeline(options=pipeline_options) + + # Read the text file[pattern] into a PCollection. + lines = pipeline | 'Read' >> ReadFromText(known_args.input) + + counts = ( + lines + | 'Split' >> (beam.ParDo(WordExtractingDoFn()).with_output_types(str)) + | 'PairWithOne' >> beam.Map(lambda x: (x, 1)) + | 'GroupAndSum' >> beam.CombinePerKey(sum)) + + # Format the counts into a PCollection of strings. + def format_result(word, count): + return '%s: %d' % (word, count) + + output = counts | 'Format' >> beam.MapTuple(format_result) + + # Write the output using a "Write" transform that has side effects. + # pylint: disable=expression-not-assigned + output | 'Write' >> WriteToText(known_args.output) + + result = pipeline.run() + result.wait_until_finish() + return result Review Comment: I think this is equivalent to https://github.com/apache/beam/blob/master/sdks/python/apache_beam/examples/wordcount.py right? If so, can we just update that to return like this instead? I think this pattern is fine for an example anyways (and we could leave a comment on why we're doing it) -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
