84 lines
3.2 KiB
Python
84 lines
3.2 KiB
Python
# Copyright 2018 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# Usage:
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# python transform.py \
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# --project bradley-playground \
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# --region us-central1 \
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# --cluster ten4 \
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# --output gs://bradley-playground/transform \
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# --train gs://bradley-playground/sfpd/train.csv \
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# --eval gs://bradley-playground/sfpd/eval.csv \
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# --analysis gs://bradley-playground/analysis \
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# --target resolution
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import argparse
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import os
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import subprocess
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from common import _utils
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def main(argv=None):
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parser = argparse.ArgumentParser(description='ML Transfomer')
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parser.add_argument('--project', type=str, help='Google Cloud project ID to use.')
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parser.add_argument('--region', type=str, help='Which zone to run the analyzer.')
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parser.add_argument('--cluster', type=str, help='The name of the cluster to run job.')
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parser.add_argument('--output', type=str, help='GCS path to use for output.')
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parser.add_argument('--train', type=str, help='GCS path of the training csv file.')
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parser.add_argument('--eval', type=str, help='GCS path of the eval csv file.')
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parser.add_argument('--analysis', type=str, help='GCS path of the analysis results.')
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parser.add_argument('--target', type=str, help='Target column name.')
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args = parser.parse_args()
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# Remove existing [output]/train and [output]/eval if they exist.
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# It should not be done in the run time code because run time code should be portable
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# to on-prem while we need gsutil here.
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_utils.delete_directory_from_gcs(os.path.join(args.output, 'train'))
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_utils.delete_directory_from_gcs(os.path.join(args.output, 'eval'))
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code_path = os.path.dirname(os.path.realpath(__file__))
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dirname = os.path.basename(__file__).split('.')[0]
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runfile_source = os.path.join(code_path, dirname, 'run.py')
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dest_files = _utils.copy_resources_to_gcs([runfile_source], args.output)
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try:
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api = _utils.get_client()
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print('Submitting job...')
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spark_args = ['--output', args.output, '--analysis', args.analysis,
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'--target', args.target]
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if args.train:
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spark_args.extend(['--train', args.train])
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if args.eval:
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spark_args.extend(['--eval', args.eval])
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job_id = _utils.submit_pyspark_job(
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api, args.project, args.region, args.cluster, dest_files[0], spark_args)
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print('Job request submitted. Waiting for completion...')
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_utils.wait_for_job(api, args.project, args.region, job_id)
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with open('/output_train.txt', 'w') as f:
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f.write(os.path.join(args.output, 'train', 'part-*'))
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with open('/output_eval.txt', 'w') as f:
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f.write(os.path.join(args.output, 'eval', 'part-*'))
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print('Job completed.')
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finally:
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_utils.remove_resources_from_gcs(dest_files)
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if __name__== "__main__":
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main()
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