blob: 4c262746e362fe1fde41f47c9c6cc697067c177d [file] [log] [blame]
#
# 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.examples import wordcount_fnapi
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.
DEFAULT_CHECKSUM = '33535a832b7db6d78389759577d4ff495980b9c0'
@attr('IT')
def test_wordcount_it(self):
test_pipeline = TestPipeline(is_integration_test=True)
# Set extra options to the pipeline for test purpose
output = '/'.join([test_pipeline.get_option('output'),
str(int(time.time())),
'results'])
arg_sleep_secs = test_pipeline.get_option('sleep_secs')
sleep_secs = int(arg_sleep_secs) if arg_sleep_secs is not None else None
pipeline_verifiers = [PipelineStateMatcher(),
FileChecksumMatcher(output + '*-of-*',
self.DEFAULT_CHECKSUM,
sleep_secs)]
extra_opts = {'output': output,
'on_success_matcher': all_of(*pipeline_verifiers)}
# Register clean up before pipeline execution
self.addCleanup(delete_files, [output + '*'])
# Get pipeline options from command argument: --test-pipeline-options,
# and start pipeline job by calling pipeline main function.
wordcount.run(test_pipeline.get_full_options_as_args(**extra_opts))
@attr('IT', 'ValidatesContainer')
def test_wordcount_fnapi_it(self):
test_pipeline = TestPipeline(is_integration_test=True)
# Get pipeline options from command argument: --test-pipeline-options,
# and start pipeline job by calling pipeline main function.
wordcount_fnapi.run(
test_pipeline.get_full_options_as_args(
experiment='beam_fn_api',
on_success_matcher=PipelineStateMatcher()))
if __name__ == '__main__':
logging.getLogger().setLevel(logging.DEBUG)
unittest.main()