sdks/python/apache_beam/runners/portability/flink_runner_test.py - beam - Git at Google

 #
 # 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.
 #
 from __future__ import absolute_import
 from __future__ import print_function

 import argparse
 import logging
 import sys
 import unittest
 from os import linesep
 from os import path
 from os.path import exists
 from shutil import rmtree
 from tempfile import mkdtemp

 import apache_beam as beam
 from apache_beam import Impulse
 from apache_beam import Map
 from apache_beam import Pipeline
 from apache_beam.io.external.generate_sequence import GenerateSequence
 from apache_beam.io.external.kafka import ReadFromKafka
 from apache_beam.io.external.kafka import WriteToKafka
 from apache_beam.metrics import Metrics
 from apache_beam.options.pipeline_options import DebugOptions
 from apache_beam.options.pipeline_options import PortableOptions
 from apache_beam.options.pipeline_options import StandardOptions
 from apache_beam.runners.portability import portable_runner
 from apache_beam.runners.portability import portable_runner_test
 from apache_beam.testing.util import assert_that
 from apache_beam.testing.util import equal_to

 if __name__ == '__main__':
   # Run as
   #
   # python -m apache_beam.runners.portability.flink_runner_test \
   #     --flink_job_server_jar=/path/to/job_server.jar \
   #     --environment_type=docker \
   #     --extra_experiments=beam_experiments \
   #     [FlinkRunnerTest.test_method, ...]

   parser = argparse.ArgumentParser(add_help=True)
   parser.add_argument('--flink_job_server_jar',
                       help='Job server jar to submit jobs.')
   parser.add_argument('--streaming', default=False, action='store_true',
                       help='Job type. batch or streaming')
   parser.add_argument('--environment_type', default='docker',
                       help='Environment type. docker or process')
   parser.add_argument('--environment_config', help='Environment config.')
   parser.add_argument('--extra_experiments', default=[], action='append',
                       help='Beam experiments config.')
   known_args, args = parser.parse_known_args(sys.argv)
   sys.argv = args

   flink_job_server_jar = known_args.flink_job_server_jar
   streaming = known_args.streaming
   environment_type = known_args.environment_type.lower()
   environment_config = (
       known_args.environment_config if known_args.environment_config else None)
   extra_experiments = known_args.extra_experiments

   # This is defined here to only be run when we invoke this file explicitly.
   class FlinkRunnerTest(portable_runner_test.PortableRunnerTest):
     _use_grpc = True
     _use_subprocesses = True

     conf_dir = None
     expansion_port = None

     @classmethod
     def tearDownClass(cls):
       if cls.conf_dir and exists(cls.conf_dir):
         logging.info("removing conf dir: %s" % cls.conf_dir)
         rmtree(cls.conf_dir)
       super(FlinkRunnerTest, cls).tearDownClass()

     @classmethod
     def _create_conf_dir(cls):
       """Create (and save a static reference to) a "conf dir", used to provide
        metrics configs and verify metrics output

        It gets cleaned up when the suite is done executing"""

       if hasattr(cls, 'conf_dir'):
         cls.conf_dir = mkdtemp(prefix='flinktest-conf')

         # path for a FileReporter to write metrics to
         cls.test_metrics_path = path.join(cls.conf_dir, 'test-metrics.txt')

         # path to write Flink configuration to
         conf_path = path.join(cls.conf_dir, 'flink-conf.yaml')
         file_reporter = 'org.apache.beam.runners.flink.metrics.FileReporter'
         with open(conf_path, 'w') as f:
           f.write(linesep.join([
               'metrics.reporters: file',
               'metrics.reporter.file.class: %s' % file_reporter,
               'metrics.reporter.file.path: %s' % cls.test_metrics_path
           ]))

     @classmethod
     def _subprocess_command(cls, job_port, expansion_port):
       # will be cleaned up at the end of this method, and recreated and used by
       # the job server
       tmp_dir = mkdtemp(prefix='flinktest')

       cls._create_conf_dir()
       cls.expansion_port = expansion_port

       try:
         return [
             'java',
             '-jar', flink_job_server_jar,
             '--flink-master-url', '[local]',
             '--flink-conf-dir', cls.conf_dir,
             '--artifacts-dir', tmp_dir,
             '--job-port', str(job_port),
             '--artifact-port', '0',
             '--expansion-port', str(expansion_port),
         ]
       finally:
         rmtree(tmp_dir)

     @classmethod
     def get_runner(cls):
       return portable_runner.PortableRunner()

     def create_options(self):
       options = super(FlinkRunnerTest, self).create_options()
       options.view_as(DebugOptions).experiments = [
           'beam_fn_api'] + extra_experiments
       options._all_options['parallelism'] = 2
       options._all_options['shutdown_sources_on_final_watermark'] = True
       options.view_as(PortableOptions).environment_type = (
           environment_type.upper())
       if environment_config:
         options.view_as(PortableOptions).environment_config = environment_config

       if streaming:
         options.view_as(StandardOptions).streaming = True
       return options

     # Can't read host files from within docker, read a "local" file there.
     def test_read(self):
       with self.create_pipeline() as p:
         lines = p | beam.io.ReadFromText('/etc/profile')
         assert_that(lines, lambda lines: len(lines) > 0)

     def test_no_subtransform_composite(self):
       raise unittest.SkipTest("BEAM-4781")

     def test_external_transforms(self):
       # TODO Move expansion address resides into PipelineOptions
       def get_expansion_service():
         return "localhost:" + str(self.expansion_port)

       with self.create_pipeline() as p:
         res = (
             p
             | GenerateSequence(start=1, stop=10,
                                expansion_service=get_expansion_service()))

         assert_that(res, equal_to([i for i in range(1, 10)]))

       # We expect to fail here because we do not have a Kafka cluster handy.
       # Nevertheless, we check that the transform is expanded by the
       # ExpansionService and that the pipeline fails during execution.
       with self.assertRaises(Exception) as ctx:
         with self.create_pipeline() as p:
           # pylint: disable=expression-not-assigned
           (p
            | ReadFromKafka(consumer_config={'bootstrap.servers':
                                             'notvalid1:7777, notvalid2:3531'},
                            topics=['topic1', 'topic2'],
                            key_deserializer='org.apache.kafka.'
                                             'common.serialization.'
                                             'ByteArrayDeserializer',
                            value_deserializer='org.apache.kafka.'
                                               'common.serialization.'
                                               'LongDeserializer',
                            expansion_service=get_expansion_service()))
       self.assertTrue('No resolvable bootstrap urls given in bootstrap.servers'
                       in str(ctx.exception),
                       'Expected to fail due to invalid bootstrap.servers, but '
                       'failed due to:\n%s' % str(ctx.exception))

       # We just test the expansion but do not execute.
       # pylint: disable=expression-not-assigned
       (self.create_pipeline()
        | Impulse()
        | Map(lambda input: (1, input))
        | WriteToKafka(producer_config={'bootstrap.servers':
                                        'localhost:9092, notvalid2:3531'},
                       topic='topic1',
                       key_serializer='org.apache.kafka.'
                                      'common.serialization.'
                                      'LongSerializer',
                       value_serializer='org.apache.kafka.'
                                        'common.serialization.'
                                        'ByteArraySerializer',
                       expansion_service=get_expansion_service()))

     def test_flattened_side_input(self):
       # Blocked on support for transcoding
       # https://jira.apache.org/jira/browse/BEAM-6523
       super(FlinkRunnerTest, self).test_flattened_side_input(
           with_transcoding=False)

     def test_metrics(self):
       """Run a simple DoFn that increments a counter, and verify that its
        expected value is written to a temporary file by the FileReporter"""

       counter_name = 'elem_counter'

       class DoFn(beam.DoFn):
         def __init__(self):
           self.counter = Metrics.counter(self.__class__, counter_name)
           logging.info('counter: %s' % self.counter.metric_name)

         def process(self, v):
           self.counter.inc()

       options = self.create_options()
       # Test only supports parallelism of 1
       options._all_options['parallelism'] = 1
       n = 100
       with Pipeline(self.get_runner(), options) as p:
         # pylint: disable=expression-not-assigned
         (p
          | beam.Create(list(range(n)))
          | beam.ParDo(DoFn()))

       with open(self.test_metrics_path, 'r') as f:
         lines = [line for line in f.readlines() if counter_name in line]
         self.assertEqual(
             len(lines), 1,
             msg='Expected 1 line matching "{}":\n{}'.format(
                 counter_name, '\n'.join(lines))
         )
         line = lines[0]
         self.assertTrue(
             '{}: {}'.format(counter_name in line, n),
             msg='Failed to find expected counter {} in line {}'.format(
                 counter_name, line)
         )

     def test_sdf_with_sdf_initiated_checkpointing(self):
       raise unittest.SkipTest("BEAM-2939")

     def test_sdf_synthetic_source(self):
       raise unittest.SkipTest("BEAM-2939")

     def test_callbacks_with_exception(self):
       raise unittest.SkipTest("BEAM-6868")

     def test_register_finalizations(self):
       raise unittest.SkipTest("BEAM-6868")

     # Inherits all other tests.

   class FlinkRunnerTestOptimized(FlinkRunnerTest):
     # TODO: Remove these tests after resolving BEAM-7248 and enabling
     #  PortableRunnerOptimized
     def create_options(self):
       options = super(FlinkRunnerTestOptimized, self).create_options()
       options.view_as(DebugOptions).experiments = [
           'pre_optimize=all'] + options.view_as(DebugOptions).experiments
       return options

     def test_external_transforms(self):
       raise unittest.SkipTest("BEAM-7252")

   # Run the tests.
   logging.getLogger().setLevel(logging.INFO)
   unittest.main()
	#
	# 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.
	#
	from __future__ import absolute_import
	from __future__ import print_function

	import argparse
	import logging
	import sys
	import unittest
	from os import linesep
	from os import path
	from os.path import exists
	from shutil import rmtree
	from tempfile import mkdtemp

	import apache_beam as beam
	from apache_beam import Impulse
	from apache_beam import Map
	from apache_beam import Pipeline
	from apache_beam.io.external.generate_sequence import GenerateSequence
	from apache_beam.io.external.kafka import ReadFromKafka
	from apache_beam.io.external.kafka import WriteToKafka
	from apache_beam.metrics import Metrics
	from apache_beam.options.pipeline_options import DebugOptions
	from apache_beam.options.pipeline_options import PortableOptions
	from apache_beam.options.pipeline_options import StandardOptions
	from apache_beam.runners.portability import portable_runner
	from apache_beam.runners.portability import portable_runner_test
	from apache_beam.testing.util import assert_that
	from apache_beam.testing.util import equal_to

	if __name__ == '__main__':
	# Run as
	#
	# python -m apache_beam.runners.portability.flink_runner_test \
	# --flink_job_server_jar=/path/to/job_server.jar \
	# --environment_type=docker \
	# --extra_experiments=beam_experiments \
	# [FlinkRunnerTest.test_method, ...]

	parser = argparse.ArgumentParser(add_help=True)
	parser.add_argument('--flink_job_server_jar',
	help='Job server jar to submit jobs.')
	parser.add_argument('--streaming', default=False, action='store_true',
	help='Job type. batch or streaming')
	parser.add_argument('--environment_type', default='docker',
	help='Environment type. docker or process')
	parser.add_argument('--environment_config', help='Environment config.')
	parser.add_argument('--extra_experiments', default=[], action='append',
	help='Beam experiments config.')
	known_args, args = parser.parse_known_args(sys.argv)
	sys.argv = args

	flink_job_server_jar = known_args.flink_job_server_jar
	streaming = known_args.streaming
	environment_type = known_args.environment_type.lower()
	environment_config = (
	known_args.environment_config if known_args.environment_config else None)
	extra_experiments = known_args.extra_experiments

	# This is defined here to only be run when we invoke this file explicitly.
	class FlinkRunnerTest(portable_runner_test.PortableRunnerTest):
	_use_grpc = True
	_use_subprocesses = True

	conf_dir = None
	expansion_port = None

	@classmethod
	def tearDownClass(cls):
	if cls.conf_dir and exists(cls.conf_dir):
	logging.info("removing conf dir: %s" % cls.conf_dir)
	rmtree(cls.conf_dir)
	super(FlinkRunnerTest, cls).tearDownClass()

	@classmethod
	def _create_conf_dir(cls):
	"""Create (and save a static reference to) a "conf dir", used to provide
	metrics configs and verify metrics output

	It gets cleaned up when the suite is done executing"""

	if hasattr(cls, 'conf_dir'):
	cls.conf_dir = mkdtemp(prefix='flinktest-conf')

	# path for a FileReporter to write metrics to
	cls.test_metrics_path = path.join(cls.conf_dir, 'test-metrics.txt')

	# path to write Flink configuration to
	conf_path = path.join(cls.conf_dir, 'flink-conf.yaml')
	file_reporter = 'org.apache.beam.runners.flink.metrics.FileReporter'
	with open(conf_path, 'w') as f:
	f.write(linesep.join([
	'metrics.reporters: file',
	'metrics.reporter.file.class: %s' % file_reporter,
	'metrics.reporter.file.path: %s' % cls.test_metrics_path
	]))

	@classmethod
	def _subprocess_command(cls, job_port, expansion_port):
	# will be cleaned up at the end of this method, and recreated and used by
	# the job server
	tmp_dir = mkdtemp(prefix='flinktest')

	cls._create_conf_dir()
	cls.expansion_port = expansion_port

	try:
	return [
	'java',
	'-jar', flink_job_server_jar,
	'--flink-master-url', '[local]',
	'--flink-conf-dir', cls.conf_dir,
	'--artifacts-dir', tmp_dir,
	'--job-port', str(job_port),
	'--artifact-port', '0',
	'--expansion-port', str(expansion_port),
	]
	finally:
	rmtree(tmp_dir)

	@classmethod
	def get_runner(cls):
	return portable_runner.PortableRunner()

	def create_options(self):
	options = super(FlinkRunnerTest, self).create_options()
	options.view_as(DebugOptions).experiments = [
	'beam_fn_api'] + extra_experiments
	options._all_options['parallelism'] = 2
	options._all_options['shutdown_sources_on_final_watermark'] = True
	options.view_as(PortableOptions).environment_type = (
	environment_type.upper())
	if environment_config:
	options.view_as(PortableOptions).environment_config = environment_config

	if streaming:
	options.view_as(StandardOptions).streaming = True
	return options

	# Can't read host files from within docker, read a "local" file there.
	def test_read(self):
	with self.create_pipeline() as p:
	lines = p \| beam.io.ReadFromText('/etc/profile')
	assert_that(lines, lambda lines: len(lines) > 0)

	def test_no_subtransform_composite(self):
	raise unittest.SkipTest("BEAM-4781")

	def test_external_transforms(self):
	# TODO Move expansion address resides into PipelineOptions
	def get_expansion_service():
	return "localhost:" + str(self.expansion_port)

	with self.create_pipeline() as p:
	res = (
	p
	\| GenerateSequence(start=1, stop=10,
	expansion_service=get_expansion_service()))

	assert_that(res, equal_to([i for i in range(1, 10)]))

	# We expect to fail here because we do not have a Kafka cluster handy.
	# Nevertheless, we check that the transform is expanded by the
	# ExpansionService and that the pipeline fails during execution.
	with self.assertRaises(Exception) as ctx:
	with self.create_pipeline() as p:
	# pylint: disable=expression-not-assigned
	(p
	\| ReadFromKafka(consumer_config={'bootstrap.servers':
	'notvalid1:7777, notvalid2:3531'},
	topics=['topic1', 'topic2'],
	key_deserializer='org.apache.kafka.'
	'common.serialization.'
	'ByteArrayDeserializer',
	value_deserializer='org.apache.kafka.'
	'common.serialization.'
	'LongDeserializer',
	expansion_service=get_expansion_service()))
	self.assertTrue('No resolvable bootstrap urls given in bootstrap.servers'
	in str(ctx.exception),
	'Expected to fail due to invalid bootstrap.servers, but '
	'failed due to:\n%s' % str(ctx.exception))

	# We just test the expansion but do not execute.
	# pylint: disable=expression-not-assigned
	(self.create_pipeline()
	\| Impulse()
	\| Map(lambda input: (1, input))
	\| WriteToKafka(producer_config={'bootstrap.servers':
	'localhost:9092, notvalid2:3531'},
	topic='topic1',
	key_serializer='org.apache.kafka.'
	'common.serialization.'
	'LongSerializer',
	value_serializer='org.apache.kafka.'
	'common.serialization.'
	'ByteArraySerializer',
	expansion_service=get_expansion_service()))

	def test_flattened_side_input(self):
	# Blocked on support for transcoding
	# https://jira.apache.org/jira/browse/BEAM-6523
	super(FlinkRunnerTest, self).test_flattened_side_input(
	with_transcoding=False)

	def test_metrics(self):
	"""Run a simple DoFn that increments a counter, and verify that its
	expected value is written to a temporary file by the FileReporter"""

	counter_name = 'elem_counter'

	class DoFn(beam.DoFn):
	def __init__(self):
	self.counter = Metrics.counter(self.__class__, counter_name)
	logging.info('counter: %s' % self.counter.metric_name)

	def process(self, v):
	self.counter.inc()

	options = self.create_options()
	# Test only supports parallelism of 1
	options._all_options['parallelism'] = 1
	n = 100
	with Pipeline(self.get_runner(), options) as p:
	# pylint: disable=expression-not-assigned
	(p
	\| beam.Create(list(range(n)))
	\| beam.ParDo(DoFn()))

	with open(self.test_metrics_path, 'r') as f:
	lines = [line for line in f.readlines() if counter_name in line]
	self.assertEqual(
	len(lines), 1,
	msg='Expected 1 line matching "{}":\n{}'.format(
	counter_name, '\n'.join(lines))
	)
	line = lines[0]
	self.assertTrue(
	'{}: {}'.format(counter_name in line, n),
	msg='Failed to find expected counter {} in line {}'.format(
	counter_name, line)
	)

	def test_sdf_with_sdf_initiated_checkpointing(self):
	raise unittest.SkipTest("BEAM-2939")

	def test_sdf_synthetic_source(self):
	raise unittest.SkipTest("BEAM-2939")

	def test_callbacks_with_exception(self):
	raise unittest.SkipTest("BEAM-6868")

	def test_register_finalizations(self):
	raise unittest.SkipTest("BEAM-6868")

	# Inherits all other tests.

	class FlinkRunnerTestOptimized(FlinkRunnerTest):
	# TODO: Remove these tests after resolving BEAM-7248 and enabling
	# PortableRunnerOptimized
	def create_options(self):
	options = super(FlinkRunnerTestOptimized, self).create_options()
	options.view_as(DebugOptions).experiments = [
	'pre_optimize=all'] + options.view_as(DebugOptions).experiments
	return options

	def test_external_transforms(self):
	raise unittest.SkipTest("BEAM-7252")

	# Run the tests.
	logging.getLogger().setLevel(logging.INFO)
	unittest.main()