blob: bd277820ceb595fea8f41340501161022613c312 [file] [log] [blame]
# coding=utf-8
#
# 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
# pylint:disable=line-too-long
# beam-playground:
# name: CoGroupByKeyMerge
# description: Demonstration of CoGroupByKey transform usage.
# multifile: false
# default_example: false
# context_line: 43
# categories:
# - Core Transforms
# - Joins
# complexity: BASIC
# tags:
# - transforms
# - strings
# - integers
# - tuples
# - pairs
# - group
def cogroupbykey(test=None):
# [START cogroupbykey]
import apache_beam as beam
with beam.Pipeline() as pipeline:
icon_pairs = pipeline | 'Create icons' >> beam.Create([
('Apple', '🍎'),
('Apple', '🍏'),
('Eggplant', '🍆'),
('Tomato', '🍅'),
])
duration_pairs = pipeline | 'Create durations' >> beam.Create([
('Apple', 'perennial'),
('Carrot', 'biennial'),
('Tomato', 'perennial'),
('Tomato', 'annual'),
])
plants = (({
'icons': icon_pairs, 'durations': duration_pairs
})
| 'Merge' >> beam.CoGroupByKey()
| beam.Map(print))
# [END cogroupbykey]
if test:
test(plants)
if __name__ == '__main__':
cogroupbykey()