def test_parent_pointer(self):
class MyPTransform(beam.PTransform):
def expand(self, p):
self.p = p
return p | beam.Create([None])
p = beam.Pipeline()
p | MyPTransform() # pylint: disable=expression-not-assigned
p = Pipeline.from_runner_api(
Pipeline.to_runner_api(p, use_fake_coders=True), None, None)
self.assertIsNotNone(p.transforms_stack[0].parts[0].parent)
self.assertEqual(p.transforms_stack[0].parts[0].parent,
p.transforms_stack[0])
def test_parent_pointer(self):
class MyPTransform(beam.PTransform):
def expand(self, p):
self.p = p
return p | beam.Create([None])
p = beam.Pipeline()
p | MyPTransform() # pylint: disable=expression-not-assigned
p = Pipeline.from_runner_api(Pipeline.to_runner_api(p), None, None)
self.assertIsNotNone(p.transforms_stack[0].parts[0].parent)
self.assertEquals(p.transforms_stack[0].parts[0].parent,
p.transforms_stack[0])
def test_sdk_harness_container_images_get_set(self):
pipeline_options = PipelineOptions([
'--experiments=beam_fn_api', '--experiments=use_unified_worker',
'--temp_location', 'gs://any-location/temp'
])
pipeline = Pipeline(options=pipeline_options)
pipeline | Create([1, 2, 3]) | ParDo(DoFn()) # pylint:disable=expression-not-assigned
test_environment = DockerEnvironment(
container_image='test_default_image')
proto_pipeline, _ = pipeline.to_runner_api(
return_context=True, default_environment=test_environment)
# We have to manually add environments since Dataflow only sets
# 'sdkHarnessContainerImages' when there are at least two environments.
dummy_env = beam_runner_api_pb2.Environment(
urn=common_urns.environments.DOCKER.urn,
payload=(beam_runner_api_pb2.DockerPayload(
container_image='dummy_image')).SerializeToString())
proto_pipeline.components.environments['dummy_env_id'].CopyFrom(
dummy_env)
dummy_transform = beam_runner_api_pb2.PTransform(
environment_id='dummy_env_id')
proto_pipeline.components.transforms['dummy_transform_id'].CopyFrom(
dummy_transform)
env = apiclient.Environment(
[], # packages
pipeline_options,
'2.0.0', # any environment version
FAKE_PIPELINE_URL,
proto_pipeline,
_sdk_image_overrides={
'.*dummy.*': 'dummy_image',
'.*test.*': 'test_default_image'
})
worker_pool = env.proto.workerPools[0]
# For the test, a third environment get added since actual default
# container image for Dataflow is different from 'test_default_image'
# we've provided above.
self.assertEqual(3, len(worker_pool.sdkHarnessContainerImages))
# Container image should be overridden by a Dataflow specific URL.
self.assertTrue(
str.startswith(
(worker_pool.sdkHarnessContainerImages[0]).containerImage,
'gcr.io/cloud-dataflow/v1beta3/python'))
def test_java_sdk_harness_dedup(self):
pipeline_options = PipelineOptions([
'--experiments=beam_fn_api', '--experiments=use_unified_worker',
'--temp_location', 'gs://any-location/temp'
])
pipeline = Pipeline(options=pipeline_options)
pipeline | Create([1, 2, 3]) | ParDo(DoFn()) # pylint:disable=expression-not-assigned
proto_pipeline, _ = pipeline.to_runner_api(return_context=True)
dummy_env_1 = beam_runner_api_pb2.Environment(
urn=common_urns.environments.DOCKER.urn,
payload=(beam_runner_api_pb2.DockerPayload(
container_image='apache/beam_java:dummy_tag')
).SerializeToString())
proto_pipeline.components.environments['dummy_env_id_1'].CopyFrom(
dummy_env_1)
dummy_transform_1 = beam_runner_api_pb2.PTransform(
environment_id='dummy_env_id_1')
proto_pipeline.components.transforms['dummy_transform_id_1'].CopyFrom(
dummy_transform_1)
dummy_env_2 = beam_runner_api_pb2.Environment(
urn=common_urns.environments.DOCKER.urn,
payload=(beam_runner_api_pb2.DockerPayload(
container_image='apache/beam_java:dummy_tag')
).SerializeToString())
proto_pipeline.components.environments['dummy_env_id_2'].CopyFrom(
dummy_env_2)
dummy_transform_2 = beam_runner_api_pb2.PTransform(
environment_id='dummy_env_id_2')
proto_pipeline.components.transforms['dummy_transform_id_2'].CopyFrom(
dummy_transform_2)
# Accessing non-public method for testing.
apiclient.DataflowApplicationClient._apply_sdk_environment_overrides(
proto_pipeline, dict(), pipeline_options)
# Only one of 'dummy_env_id_1' or 'dummy_env_id_2' should be in the set of
# environment IDs used by the proto after Java environment de-duping.
env_ids_from_transforms = [
proto_pipeline.components.transforms[transform_id].environment_id
for transform_id in proto_pipeline.components.transforms
]
if 'dummy_env_id_1' in env_ids_from_transforms:
self.assertTrue('dummy_env_id_2' not in env_ids_from_transforms)
else:
self.assertTrue('dummy_env_id_2' in env_ids_from_transforms)
def test_visitor_not_sorted(self):
p = Pipeline()
# pylint: disable=expression-not-assigned
from apache_beam.testing.test_stream import TestStream
p | TestStream().add_elements(['']) | beam.Map(lambda _: _)
original_graph = p.to_runner_api(return_context=False)
out_of_order_graph = p.to_runner_api(return_context=False)
root_id = out_of_order_graph.root_transform_ids[0]
root = out_of_order_graph.components.transforms[root_id]
tmp = root.subtransforms[0]
root.subtransforms[0] = root.subtransforms[1]
root.subtransforms[1] = tmp
p = beam.Pipeline().from_runner_api(out_of_order_graph,
runner='BundleBasedDirectRunner',
options=None)
v_out_of_order = ConsumerTrackingPipelineVisitor()
p.visit(v_out_of_order)
p = beam.Pipeline().from_runner_api(original_graph,
runner='BundleBasedDirectRunner',
options=None)
v_original = ConsumerTrackingPipelineVisitor()
p.visit(v_original)
# Convert to string to assert they are equal.
out_of_order_labels = {
str(k): [str(t) for t in v_out_of_order.value_to_consumers[k]]
for k in v_out_of_order.value_to_consumers
}
original_labels = {
str(k): [str(t) for t in v_original.value_to_consumers[k]]
for k in v_original.value_to_consumers
}
self.assertDictEqual(out_of_order_labels, original_labels)
def test_bad_path(self):
dummy_sdk_file = tempfile.NamedTemporaryFile()
remote_runner = DataflowRunner()
pipeline = Pipeline(
remote_runner,
options=PipelineOptions([
'--dataflow_endpoint=ignored',
'--sdk_location=' + dummy_sdk_file.name, '--job_name=test-job',
'--project=test-project', '--staging_location=ignored',
'--temp_location=/dev/null', '--template_location=/bad/path',
'--no_auth'
]))
remote_runner.job = apiclient.Job(pipeline._options,
pipeline.to_runner_api())
with self.assertRaises(IOError):
pipeline.run().wait_until_finish()
def test_default_environment_get_set(self):
pipeline_options = PipelineOptions([
'--experiments=beam_fn_api',
'--experiments=use_unified_worker',
'--temp_location',
'gs://any-location/temp'
])
pipeline = Pipeline(options=pipeline_options)
pipeline | Create([1, 2, 3]) | ParDo(DoFn()) # pylint:disable=expression-not-assigned
test_environment = DockerEnvironment(container_image='test_default_image')
proto_pipeline, _ = pipeline.to_runner_api(
return_context=True, default_environment=test_environment)
dummy_env = beam_runner_api_pb2.Environment(
urn=common_urns.environments.DOCKER.urn,
payload=(
beam_runner_api_pb2.DockerPayload(
container_image='dummy_image')).SerializeToString())
proto_pipeline.components.environments['dummy_env_id'].CopyFrom(dummy_env)
dummy_transform = beam_runner_api_pb2.PTransform(
environment_id='dummy_env_id')
proto_pipeline.components.transforms['dummy_transform_id'].CopyFrom(
dummy_transform)
env = apiclient.Environment(
[], # packages
pipeline_options,
'2.0.0', # any environment version
FAKE_PIPELINE_URL,
proto_pipeline,
_sdk_image_overrides={
'.*dummy.*': 'dummy_image', '.*test.*': 'test_default_image'
})
worker_pool = env.proto.workerPools[0]
self.assertEqual(2, len(worker_pool.sdkHarnessContainerImages))
images_from_proto = [
sdk_info.containerImage
for sdk_info in worker_pool.sdkHarnessContainerImages
]
self.assertIn('test_default_image', images_from_proto)
def test_bad_path(self):
dummy_sdk_file = tempfile.NamedTemporaryFile()
remote_runner = DataflowRunner()
pipeline = Pipeline(remote_runner,
options=PipelineOptions([
'--dataflow_endpoint=ignored',
'--sdk_location=' + dummy_sdk_file.name,
'--job_name=test-job',
'--project=test-project',
'--staging_location=ignored',
'--temp_location=/dev/null',
'--template_location=/bad/path',
'--no_auth=True']))
remote_runner.job = apiclient.Job(pipeline._options,
pipeline.to_runner_api())
with self.assertRaises(IOError):
pipeline.run().wait_until_finish()
def test_pipeline_sdk_not_overridden(self):
pipeline_options = PipelineOptions([
'--experiments=beam_fn_api',
'--experiments=use_unified_worker',
'--temp_location',
'gs://any-location/temp',
'--worker_harness_container_image=dummy_prefix/dummy_name:dummy_tag'
])
pipeline = Pipeline(options=pipeline_options)
pipeline | Create([1, 2, 3]) | ParDo(DoFn()) # pylint:disable=expression-not-assigned
proto_pipeline, _ = pipeline.to_runner_api(return_context=True)
dummy_env = beam_runner_api_pb2.Environment(
urn=common_urns.environments.DOCKER.urn,
payload=(
beam_runner_api_pb2.DockerPayload(
container_image='dummy_prefix/dummy_name:dummy_tag')
).SerializeToString())
proto_pipeline.components.environments['dummy_env_id'].CopyFrom(dummy_env)
dummy_transform = beam_runner_api_pb2.PTransform(
environment_id='dummy_env_id')
proto_pipeline.components.transforms['dummy_transform_id'].CopyFrom(
dummy_transform)
# Accessing non-public method for testing.
apiclient.DataflowApplicationClient._apply_sdk_environment_overrides(
proto_pipeline, dict(), pipeline_options)
self.assertIsNotNone(2, len(proto_pipeline.components.environments))
from apache_beam.utils import proto_utils
found_override = False
for env in proto_pipeline.components.environments.values():
docker_payload = proto_utils.parse_Bytes(
env.payload, beam_runner_api_pb2.DockerPayload)
if docker_payload.container_image.startswith(
names.DATAFLOW_CONTAINER_IMAGE_REPOSITORY):
found_override = True
self.assertFalse(found_override)
def test_sdk_harness_container_image_overrides(self):
if 'sdkHarnessContainerImages' not in dataflow.WorkerPool.__dict__:
_LOGGER.warning(
'Skipping test \'test_sdk_harness_container_image_overrides\' since '
'Dataflow API WorkerPool does not have attribute '
'\'sdkHarnessContainerImages\'')
return
pipeline_options = PipelineOptions([
'--experiments=beam_fn_api',
'--experiments=use_unified_worker',
'--temp_location',
'gs://any-location/temp',
'--project',
'dummy_project',
'--sdk_harness_container_image_overrides',
'.*dummy.*,new_dummy_container_image',
])
pipeline = Pipeline(options=pipeline_options)
test_environment = DockerEnvironment(
container_image='dummy_container_image')
proto_pipeline, _ = pipeline.to_runner_api(
return_context=True, default_environment=test_environment)
dataflow_client = apiclient.DataflowApplicationClient(pipeline_options)
# Accessing non-public method for testing.
dataflow_client._apply_sdk_environment_overrides(proto_pipeline)
self.assertIsNotNone(1, len(proto_pipeline.components.environments))
env = list(proto_pipeline.components.environments.values())[0]
from apache_beam.utils import proto_utils
docker_payload = proto_utils.parse_Bytes(
env.payload, beam_runner_api_pb2.DockerPayload)
# Container image should be overridden by a the given override.
self.assertEqual(docker_payload.container_image,
'new_dummy_container_image')
def test_display_data(self):
class MyParentTransform(beam.PTransform):
def expand(self, p):
self.p = p
return p | beam.Create([None])
def display_data(self): # type: () -> dict
parent_dd = super(MyParentTransform, self).display_data()
parent_dd['p_dd_string'] = DisplayDataItem(
'p_dd_string_value', label='p_dd_string_label')
parent_dd['p_dd_bool'] = DisplayDataItem(True, label='p_dd_bool_label')
parent_dd['p_dd_int'] = DisplayDataItem(1, label='p_dd_int_label')
return parent_dd
class MyPTransform(MyParentTransform):
def expand(self, p):
self.p = p
return p | beam.Create([None])
def display_data(self): # type: () -> dict
parent_dd = super(MyPTransform, self).display_data()
parent_dd['dd_string'] = DisplayDataItem(
'dd_string_value', label='dd_string_label')
parent_dd['dd_bool'] = DisplayDataItem(False, label='dd_bool_label')
parent_dd['dd_int'] = DisplayDataItem(1.1, label='dd_int_label')
return parent_dd
p = beam.Pipeline()
p | MyPTransform() # pylint: disable=expression-not-assigned
from apache_beam.portability.api import beam_runner_api_pb2
proto_pipeline = Pipeline.to_runner_api(p, use_fake_coders=True)
my_transform, = [
transform
for transform in proto_pipeline.components.transforms.values()
if transform.unique_name == 'MyPTransform'
]
self.assertIsNotNone(my_transform)
self.assertListEqual(
list(my_transform.display_data),
[
beam_runner_api_pb2.DisplayData(
urn=common_urns.StandardDisplayData.DisplayData.LABELLED.urn,
payload=beam_runner_api_pb2.LabelledPayload(
label='p_dd_string_label',
string_value='p_dd_string_value').SerializeToString()),
beam_runner_api_pb2.DisplayData(
urn=common_urns.StandardDisplayData.DisplayData.LABELLED.urn,
payload=beam_runner_api_pb2.LabelledPayload(
label='p_dd_bool_label',
bool_value=True).SerializeToString()),
beam_runner_api_pb2.DisplayData(
urn=common_urns.StandardDisplayData.DisplayData.LABELLED.urn,
payload=beam_runner_api_pb2.LabelledPayload(
label='p_dd_int_label',
double_value=1).SerializeToString()),
beam_runner_api_pb2.DisplayData(
urn=common_urns.StandardDisplayData.DisplayData.LABELLED.urn,
payload=beam_runner_api_pb2.LabelledPayload(
label='dd_string_label',
string_value='dd_string_value').SerializeToString()),
beam_runner_api_pb2.DisplayData(
urn=common_urns.StandardDisplayData.DisplayData.LABELLED.urn,
payload=beam_runner_api_pb2.LabelledPayload(
label='dd_bool_label',
bool_value=False).SerializeToString()),
beam_runner_api_pb2.DisplayData(
urn=common_urns.StandardDisplayData.DisplayData.LABELLED.urn,
payload=beam_runner_api_pb2.LabelledPayload(
label='dd_int_label',
double_value=1.1).SerializeToString()),
])
