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#
# 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.
#
"""End-to-end test for the wordcount example."""
from __future__ import absolute_import
import logging
import time
import unittest
from hamcrest.core.core.allof import all_of
from nose.plugins.attrib import attr
from apache_beam.examples import wordcount
from apache_beam.testing.pipeline_verifiers import FileChecksumMatcher
from apache_beam.testing.pipeline_verifiers import PipelineStateMatcher
from apache_beam.testing.test_pipeline import TestPipeline
from apache_beam.testing.test_utils import delete_files
class WordCountIT(unittest.TestCase):
# Enable nose tests running in parallel
_multiprocess_can_split_ = True
# The default checksum is a SHA-1 hash generated from a sorted list of
# lines read from expected output. This value corresponds to the default
# input of WordCount example.
DEFAULT_CHECKSUM = '33535a832b7db6d78389759577d4ff495980b9c0'
@attr('IT')
def test_wordcount_it(self):
self._run_wordcount_it(wordcount.run)
@attr('IT', 'ValidatesContainer')
def test_wordcount_fnapi_it(self):
self._run_wordcount_it(wordcount.run, experiment='beam_fn_api')
def _run_wordcount_it(self, run_wordcount, **opts):
test_pipeline = TestPipeline(is_integration_test=True)
extra_opts = {}
# Set extra options to the pipeline for test purpose
test_output = '/'.join([test_pipeline.get_option('output'),
str(int(time.time() * 1000)),
'results'])
extra_opts['output'] = test_output
test_input = test_pipeline.get_option('input')
if test_input:
extra_opts['input'] = test_input
arg_sleep_secs = test_pipeline.get_option('sleep_secs')
sleep_secs = int(arg_sleep_secs) if arg_sleep_secs is not None else None
expect_checksum = (test_pipeline.get_option('expect_checksum') or
self.DEFAULT_CHECKSUM)
pipeline_verifiers = [PipelineStateMatcher(),
FileChecksumMatcher(test_output + '*-of-*',
expect_checksum,
sleep_secs)]
extra_opts['on_success_matcher'] = all_of(*pipeline_verifiers)
extra_opts.update(opts)
# Register clean up before pipeline execution
self.addCleanup(delete_files, [test_output + '*'])
# Get pipeline options from command argument: --test-pipeline-options,
# and start pipeline job by calling pipeline main function.
run_wordcount(test_pipeline.get_full_options_as_args(**extra_opts),
save_main_session=False)
if __name__ == '__main__':
logging.getLogger().setLevel(logging.DEBUG)
unittest.main()