pipelines/samples/core/parallel_join/parallel_join.py

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1.8 KiB
Python
Executable File

#!/usr/bin/env python3
# Copyright 2019-2023 The Kubeflow Authors
#
# Licensed 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.
from kfp import dsl, compiler
def gcs_download_op(url):
return dsl.ContainerOp(
name='GCS - Download',
image='google/cloud-sdk:279.0.0',
command=['sh', '-c'],
arguments=['gsutil cat $0 | tee $1', url, '/tmp/results.txt'],
file_outputs={
'data': '/tmp/results.txt',
}
)
def echo2_op(text1, text2):
return dsl.ContainerOp(
name='echo',
image='library/bash:4.4.23',
command=['sh', '-c'],
arguments=['echo "Text 1: $0"; echo "Text 2: $1"', text1, text2]
)
@dsl.pipeline(
name='parallel-pipeline',
description='Download two messages in parallel and prints the concatenated result.'
)
def download_and_join(
url1='gs://ml-pipeline/sample-data/shakespeare/shakespeare1.txt',
url2='gs://ml-pipeline/sample-data/shakespeare/shakespeare2.txt'
):
"""A three-step pipeline with first two running in parallel."""
download1_task = gcs_download_op(url1)
download2_task = gcs_download_op(url2)
echo_task = echo2_op(download1_task.output, download2_task.output)
if __name__ == '__main__':
compiler.Compiler().compile(download_and_join, __file__ + '.yaml')