def test_reuse_default_cluster_if_not_configured(self):
clusters = self.current_env.clusters
runner = interactive_runner.InteractiveRunner(
underlying_runner=FlinkRunner())
options = PipelineOptions()
# Pipeline is not configured to run on Cloud.
p = beam.Pipeline(runner=runner, options=options)
meta = ClusterMetadata(project_id='test-project', region='test-region')
meta.master_url = 'test-url'
meta.dashboard = 'test-dashboard'
dcm = DataprocClusterManager(meta)
# Configure the clusters so that a default cluster is known.
clusters.dataproc_cluster_managers[meta] = dcm
clusters.set_default_cluster(meta)
runner.configure_for_flink(p, options)
# The default cluster is used.
tuned_meta = clusters.cluster_metadata(p)
self.assertIs(tuned_meta, clusters.default_cluster_metadata)
# The pipeline is known.
self.assertIn(p, clusters.pipelines)
registered_dcm = clusters.pipelines[p]
self.assertIn(p, registered_dcm.pipelines)
# The pipeline options is tuned for execution on the cluster.
flink_options = options.view_as(FlinkRunnerOptions)
self.assertEqual(flink_options.flink_master, tuned_meta.master_url)
self.assertEqual(flink_options.flink_version,
clusters.DATAPROC_FLINK_VERSION)
def test_describe_by_cluster_identifier(self):
known_meta = ClusterMetadata(project_id='test-project')
known_meta2 = ClusterMetadata(project_id='test-project',
region='some-other-region')
dcm = self.clusters.create(known_meta)
dcm2 = self.clusters.create(known_meta2)
p = beam.Pipeline()
p2 = beam.Pipeline()
self.clusters.pipelines[p] = dcm
dcm.pipelines.add(p)
self.clusters.pipelines[p2] = dcm2
dcm.pipelines.add(p2)
cid_pipeline = p
meta = self.clusters.describe(cid_pipeline)
self.assertIs(meta, known_meta)
cid_master_url = known_meta.master_url
meta = self.clusters.describe(cid_master_url)
self.assertIs(meta, known_meta)
cid_meta = ClusterMetadata(project_id=known_meta.project_id,
region=known_meta.region,
cluster_name=known_meta.cluster_name)
meta = self.clusters.describe(cid_meta)
self.assertIs(meta, known_meta)
def test_describe_everything(self):
meta = ClusterMetadata(project_id='test-project')
meta2 = ClusterMetadata(project_id='test-project',
region='some-other-region')
_ = self.clusters.create(meta)
_ = self.clusters.create(meta2)
meta_list = self.clusters.describe()
self.assertEqual([meta, meta2], meta_list)
def _worker_options_to_cluster_metadata(self, options: PipelineOptions,
cluster_metadata: ClusterMetadata):
worker_options = options.view_as(WorkerOptions)
if worker_options.subnetwork:
cluster_metadata.subnetwork = worker_options.subnetwork
if worker_options.num_workers:
cluster_metadata.num_workers = worker_options.num_workers
if worker_options.machine_type:
cluster_metadata.machine_type = worker_options.machine_type
def test_force_cleanup_everything(self):
meta = ClusterMetadata(project_id='test-project')
meta2 = ClusterMetadata(project_id='test-project-2')
_ = self.clusters.create(meta)
_ = self.clusters.create(meta2)
self.clusters.cleanup(force=True)
self.assertEqual(self.m_delete_cluster.call_count, 2)
self.assertNotIn(meta, self.clusters.dataproc_cluster_managers)
self.assertNotIn(meta2, self.clusters.dataproc_cluster_managers)
self.assertIsNone(self.clusters.default_cluster_metadata)
def test_cleanup_by_meta(self):
known_meta = ClusterMetadata(project_id='test-project',
region='test-region')
_ = self.clusters.create(known_meta)
meta = ClusterMetadata(project_id=known_meta.project_id,
region=known_meta.region,
cluster_name=known_meta.cluster_name)
self.clusters.cleanup(meta)
self.m_delete_cluster.assert_called_once()
self.assertNotIn(known_meta, self.clusters.dataproc_cluster_managers)
self.assertNotIn(known_meta.master_url, self.clusters.master_urls)
self.assertIsNone(self.clusters.default_cluster_metadata)
def test_get_master_url_and_dashboard(self, mock_parse_method):
"""
Tests that get_master_url_and_dashboard detect the line containing the
unique substring which identifies the location of the master_url and
application id of the Flink master.
"""
cluster_metadata = ClusterMetadata(
project_id='test-project', region='test-region')
cluster_manager = DataprocClusterManager(cluster_metadata)
cluster_manager._fs = MockFileSystem()
cluster_metadata._staging_directory = 'test-staging-bucket'
master_url, dashboard = cluster_manager.get_master_url_and_dashboard()
self.assertEqual(master_url, 'test-master-url')
self.assertEqual(dashboard, 'test-dashboard-link')
def test_cleanup_by_a_pipeline(self):
meta = ClusterMetadata(project_id='test-project')
dcm = self.clusters.create(meta)
# Set up the association between a pipeline and a cluster.
# In real code, it's set by the runner the 1st time a pipeline is executed.
options = PipelineOptions()
options.view_as(FlinkRunnerOptions).flink_master = meta.master_url
p = beam.Pipeline(options=options)
self.clusters.pipelines[p] = dcm
dcm.pipelines.add(p)
self.clusters.cleanup(p)
# Delete the cluster.
self.m_delete_cluster.assert_called_once()
# Pipeline association is cleaned up.
self.assertNotIn(p, self.clusters.pipelines)
self.assertNotIn(p, dcm.pipelines)
self.assertEqual(
options.view_as(FlinkRunnerOptions).flink_master, '[auto]')
# The cluster is unknown now.
self.assertNotIn(meta, self.clusters.dataproc_cluster_managers)
self.assertNotIn(meta.master_url, self.clusters.master_urls)
# The cleaned up cluster is also the default cluster. Clean the default.
self.assertIsNone(self.clusters.default_cluster_metadata)
def test_not_cleanup_if_multiple_pipelines_share_a_manager(self):
meta = ClusterMetadata(project_id='test-project')
dcm = self.clusters.create(meta)
options = PipelineOptions()
options.view_as(FlinkRunnerOptions).flink_master = meta.master_url
options2 = PipelineOptions()
options2.view_as(FlinkRunnerOptions).flink_master = meta.master_url
p = beam.Pipeline(options=options)
p2 = beam.Pipeline(options=options2)
self.clusters.pipelines[p] = dcm
self.clusters.pipelines[p2] = dcm
dcm.pipelines.add(p)
dcm.pipelines.add(p2)
self.clusters.cleanup(p)
# No cluster deleted.
self.m_delete_cluster.assert_not_called()
# Pipeline association of p is cleaned up.
self.assertNotIn(p, self.clusters.pipelines)
self.assertNotIn(p, dcm.pipelines)
self.assertEqual(
options.view_as(FlinkRunnerOptions).flink_master, '[auto]')
# Pipeline association of p2 still presents.
self.assertIn(p2, self.clusters.pipelines)
self.assertIn(p2, dcm.pipelines)
self.assertEqual(
options2.view_as(FlinkRunnerOptions).flink_master, meta.master_url)
# The cluster is still known.
self.assertIn(meta, self.clusters.dataproc_cluster_managers)
self.assertIn(meta.master_url, self.clusters.master_urls)
# The default cluster still presents.
self.assertIs(meta, self.clusters.default_cluster_metadata)
def configure_for_flink(self, user_pipeline: beam.Pipeline,
options: PipelineOptions) -> None:
"""Configures the pipeline options for running a job with Flink.
When running with a FlinkRunner, a job server started from an uber jar
(locally built or remotely downloaded) hosting the beam_job_api will
communicate with the Flink cluster located at the given flink_master in the
pipeline options.
"""
clusters = ie.current_env().clusters
if clusters.pipelines.get(user_pipeline, None):
# Noop for a known pipeline using a known Dataproc cluster.
return
flink_master = options.view_as(FlinkRunnerOptions).flink_master
cluster_metadata = clusters.default_cluster_metadata
if flink_master == '[auto]':
# Try to create/reuse a cluster when no flink_master is given.
project_id = options.view_as(GoogleCloudOptions).project
region = options.view_as(GoogleCloudOptions).region
if project_id:
if clusters.default_cluster_metadata:
# Reuse the cluster name from default in case of a known cluster.
cluster_metadata = ClusterMetadata(
project_id=project_id,
region=region,
cluster_name=clusters.default_cluster_metadata.
cluster_name)
else:
# Generate the metadata with a new unique cluster name.
cluster_metadata = ClusterMetadata(project_id=project_id,
region=region)
# Add additional configurations.
self._worker_options_to_cluster_metadata(
options, cluster_metadata)
# else use the default cluster metadata.
elif flink_master in clusters.master_urls:
cluster_metadata = clusters.cluster_metadata(flink_master)
else: # Noop if a self-hosted Flink is in use.
return
if not cluster_metadata:
return # Not even a default cluster to create/reuse, run Flink locally.
dcm = clusters.create(cluster_metadata)
# Side effects associated with the user_pipeline.
clusters.pipelines[user_pipeline] = dcm
dcm.pipelines.add(user_pipeline)
self._configure_flink_options(options, clusters.DATAPROC_FLINK_VERSION,
dcm.cluster_metadata.master_url)
def test_cluster_metadata_identifies_master_url(self):
cid = 'test-url'
known_meta = ClusterMetadata(project_id='test-project')
_ = DataprocClusterManager(known_meta)
self.clusters.master_urls[cid] = known_meta
meta = self.clusters.cluster_metadata(cid)
self.assertIs(meta, known_meta)
def test_cluster_metadata_identifies_pipeline(self):
cid = beam.Pipeline()
known_meta = ClusterMetadata(project_id='test-project')
dcm = DataprocClusterManager(known_meta)
self.clusters.pipelines[cid] = dcm
meta = self.clusters.cluster_metadata(cid)
self.assertIs(meta, known_meta)
def test_cleanup_by_a_master_url(self):
meta = ClusterMetadata(project_id='test-project')
_ = self.clusters.create(meta)
self.clusters.cleanup(meta.master_url)
self.m_delete_cluster.assert_called_once()
self.assertNotIn(meta, self.clusters.dataproc_cluster_managers)
self.assertNotIn(meta.master_url, self.clusters.master_urls)
self.assertIsNone(self.clusters.default_cluster_metadata)
def test_get_staging_location_exception(self, mock_cluster_client):
"""
Test to catch when an error is raised inside get_staging_location.
"""
cluster_metadata = ClusterMetadata(
project_id='test-project',
region='test-region',
cluster_name='test-cluster')
cluster_manager = DataprocClusterManager(cluster_metadata)
with self.assertRaises(MockException):
cluster_manager.get_staging_location()
def test_create_but_reuse_a_known_cluster(self):
known_meta = ClusterMetadata(project_id='test-project',
region='test-region')
known_dcm = DataprocClusterManager(known_meta)
known_meta.master_url = 'test-url'
self.clusters.set_default_cluster(known_meta)
self.clusters.dataproc_cluster_managers[known_meta] = known_dcm
self.clusters.master_urls[known_meta.master_url] = known_meta
# Use an equivalent meta as the identifier to create a cluster.
cid_meta = ClusterMetadata(project_id=known_meta.project_id,
region=known_meta.region,
cluster_name=known_meta.cluster_name)
dcm = self.clusters.create(cid_meta)
# The known cluster manager is returned.
self.assertIs(dcm, known_dcm)
# Then use an equivalent master_url as the identifier.
cid_master_url = known_meta.master_url
dcm = self.clusters.create(cid_master_url)
self.assertIs(dcm, known_dcm)
def test_create_a_new_cluster(self):
meta = ClusterMetadata(project_id='test-project')
_ = self.clusters.create(meta)
# Derived fields are populated.
self.assertTrue(meta.master_url.startswith('test-url'))
self.assertEqual(meta.dashboard, 'test-dashboard')
# The cluster is known.
self.assertIn(meta, self.clusters.dataproc_cluster_managers)
self.assertIn(meta.master_url, self.clusters.master_urls)
# The default cluster is updated to the created cluster.
self.assertIs(meta, self.clusters.default_cluster_metadata)
def test_create_cluster_region_does_not_exist(self, mock_cluster_client):
"""
Tests that an exception is thrown when a user specifies a region
that does not exist.
"""
cluster_metadata = ClusterMetadata(
project_id='test-project', region='test-region')
cluster_manager = DataprocClusterManager(cluster_metadata)
from apache_beam.runners.interactive.dataproc.dataproc_cluster_manager import _LOGGER
with self.assertLogs(_LOGGER, level='ERROR') as context_manager:
self.assertRaises(ValueError, cluster_manager.create_cluster, {})
self.assertTrue('Invalid region provided' in context_manager.output[0])
def test_create_cluster_default_already_exists(self, mock_cluster_client):
"""
Tests that no exception is thrown when a cluster already exists,
but is using ie.current_env().clusters.default_cluster_name.
"""
cluster_metadata = ClusterMetadata(
project_id='test-project', region='test-region')
cluster_manager = DataprocClusterManager(cluster_metadata)
from apache_beam.runners.interactive.dataproc.dataproc_cluster_manager import _LOGGER
with self.assertLogs(_LOGGER, level='INFO') as context_manager:
cluster_manager.create_cluster({})
self.assertTrue('already exists' in context_manager.output[0])
def test_cleanup_does_not_exist(self, mock_cluster_client, mock_cleanup):
"""
Tests that an exception is thrown when cleanup attempts to delete
a cluster that does not exist.
"""
cluster_metadata = ClusterMetadata(
project_id='test-project', region='test-region')
cluster_manager = DataprocClusterManager(cluster_metadata)
from apache_beam.runners.interactive.dataproc.dataproc_cluster_manager import _LOGGER
with self.assertLogs(_LOGGER, level='ERROR') as context_manager:
self.assertRaises(ValueError, cluster_manager.cleanup)
self.assertTrue('Cluster does not exist' in context_manager.output[0])
def test_cleanup_other_exception(self, mock_cluster_client, mock_cleanup):
"""
Tests that an exception is thrown when the exception is not handled by
any other case under cleanup.
"""
cluster_metadata = ClusterMetadata(
project_id='test-project', region='test-region')
cluster_manager = DataprocClusterManager(cluster_metadata)
from apache_beam.runners.interactive.dataproc.dataproc_cluster_manager import _LOGGER
with self.assertLogs(_LOGGER, level='ERROR') as context_manager:
self.assertRaises(MockException, cluster_manager.cleanup)
self.assertTrue('Failed to delete cluster' in context_manager.output[0])
def test_cluster_metadata_default_value(self):
cid_none = None
cid_unknown_p = beam.Pipeline()
cid_unknown_master_url = 'test-url'
default_meta = ClusterMetadata(project_id='test-project')
self.clusters.set_default_cluster(default_meta)
self.assertIs(default_meta, self.clusters.cluster_metadata(cid_none))
self.assertIs(default_meta,
self.clusters.cluster_metadata(cid_unknown_p))
self.assertIs(default_meta,
self.clusters.cluster_metadata(cid_unknown_master_url))
def configure_for_flink(self, user_pipeline: beam.Pipeline,
options: PipelineOptions) -> None:
"""Tunes the pipeline options for the setup of running a job with Flink.
"""
clusters = ie.current_env().clusters
if clusters.pipelines.get(user_pipeline, None):
# Noop for a known pipeline using a known Dataproc cluster.
return
flink_master = options.view_as(FlinkRunnerOptions).flink_master
cluster_metadata = clusters.default_cluster_metadata
if flink_master == '[auto]':
# Try to create/reuse a cluster when no flink_master is given.
project_id = options.view_as(GoogleCloudOptions).project
region = options.view_as(GoogleCloudOptions).region
if project_id:
if clusters.default_cluster_metadata:
# Reuse the cluster name from default in case of a known cluster.
cluster_metadata = ClusterMetadata(
project_id=project_id,
region=region,
cluster_name=clusters.default_cluster_metadata.
cluster_name)
else:
# Generate the metadata with a new unique cluster name.
cluster_metadata = ClusterMetadata(project_id=project_id,
region=region)
# else use the default cluster metadata.
elif flink_master in clusters.master_urls:
cluster_metadata = clusters.cluster_metadata(flink_master)
else: # Noop if a self-hosted Flink is in use.
return
if not cluster_metadata:
return # Not even a default cluster to create/reuse, run Flink locally.
dcm = clusters.create(cluster_metadata)
# Side effects associated with the user_pipeline.
clusters.pipelines[user_pipeline] = dcm
dcm.pipelines.add(user_pipeline)
flink_options = options.view_as(FlinkRunnerOptions)
flink_options.flink_master = dcm.cluster_metadata.master_url
flink_options.flink_version = clusters.DATAPROC_FLINK_VERSION
def test_get_staging_location(self, mock_cluster_client, mock_list):
"""
Test to receive a mock staging location successfully under
get_staging_location.
"""
cluster_metadata = ClusterMetadata(
project_id='test-project',
region='test-region',
cluster_name='test-cluster')
cluster_manager = DataprocClusterManager(cluster_metadata)
self.assertEqual(
cluster_manager.get_staging_location(),
'gs://test-bucket/google-cloud-dataproc-metainfo/')
def test_cleanup_permission_denied(self, mock_cluster_client, mock_cleanup):
"""
Tests that an exception is thrown when a user is trying to delete
a project that they have insufficient permissions for.
"""
cluster_metadata = ClusterMetadata(
project_id='test-project', region='test-region')
cluster_manager = DataprocClusterManager(cluster_metadata)
from apache_beam.runners.interactive.dataproc.dataproc_cluster_manager import _LOGGER
with self.assertLogs(_LOGGER, level='ERROR') as context_manager:
self.assertRaises(ValueError, cluster_manager.cleanup)
self.assertTrue(
'Due to insufficient project permissions' in
context_manager.output[0])
def test_reuse_a_cluster_for_a_known_pipeline(self):
clusters = self.current_env.clusters
runner = interactive_runner.InteractiveRunner(
underlying_runner=FlinkRunner())
options = PipelineOptions(project='test-project', region='test-region')
p = beam.Pipeline(runner=runner, options=options)
meta = ClusterMetadata(project_id='test-project', region='test-region')
dcm = DataprocClusterManager(meta)
# Configure the clusters so that the pipeline is known.
clusters.pipelines[p] = dcm
runner.configure_for_flink(p, options)
# A known cluster is reused.
tuned_meta = clusters.cluster_metadata(p)
self.assertIs(tuned_meta, meta)
def test_describe_everything_when_cluster_identifer_unknown(self):
known_meta = ClusterMetadata(project_id='test-project')
known_meta2 = ClusterMetadata(project_id='test-project',
region='some-other-region')
dcm = self.clusters.create(known_meta)
dcm2 = self.clusters.create(known_meta2)
p = beam.Pipeline()
p2 = beam.Pipeline()
self.clusters.pipelines[p] = dcm
dcm.pipelines.add(p)
self.clusters.pipelines[p2] = dcm2
dcm.pipelines.add(p2)
cid_pipeline = beam.Pipeline()
meta_list = self.clusters.describe(cid_pipeline)
self.assertEqual([known_meta, known_meta2], meta_list)
cid_master_url = 'some-random-url'
meta_list = self.clusters.describe(cid_master_url)
self.assertEqual([known_meta, known_meta2], meta_list)
cid_meta = ClusterMetadata(project_id='some-random-project')
meta_list = self.clusters.describe(cid_meta)
self.assertEqual([known_meta, known_meta2], meta_list)
def test_parse_master_url_and_dashboard(self, mock_cluster_details):
"""
Tests that parse_master_url_and_dashboard properly parses the input
string and produces a mock master_url and mock dashboard link.
"""
cluster_metadata = ClusterMetadata(
project_id='test-project', region='test-region')
cluster_manager = DataprocClusterManager(cluster_metadata)
line = 'test-line Found Web Interface test-master-url' \
' of application \'test-app-id\'.\n'
master_url, dashboard = cluster_manager.parse_master_url_and_dashboard(line)
self.assertEqual('test-master-url', master_url)
self.assertEqual(
'test-resource-manager/gateway/default/yarn/proxy/test-app-id/',
dashboard)
def test_cleanup_noop_unknown_cluster(self):
meta = ClusterMetadata(project_id='test-project')
dcm = self.clusters.create(meta)
p = beam.Pipeline()
self.clusters.pipelines[p] = dcm
dcm.pipelines.add(p)
cid_pipeline = beam.Pipeline()
self.clusters.cleanup(cid_pipeline)
self.m_delete_cluster.assert_not_called()
cid_master_url = 'some-random-url'
self.clusters.cleanup(cid_master_url)
self.m_delete_cluster.assert_not_called()
cid_meta = ClusterMetadata(project_id='random-project')
self.clusters.cleanup(cid_meta)
self.m_delete_cluster.assert_not_called()
self.assertIn(meta, self.clusters.dataproc_cluster_managers)
self.assertIn(meta.master_url, self.clusters.master_urls)
self.assertIs(meta, self.clusters.default_cluster_metadata)
self.assertIn(p, self.clusters.pipelines)
self.assertIn(p, dcm.pipelines)
def test_get_cluster_details_permission_denied(self, mock_cluster_client):
"""
Tests that an exception is thrown when a user is trying to get information
for a project without sufficient permissions to do so.
"""
cluster_metadata = ClusterMetadata(
project_id='test-project', region='test-region')
cluster_manager = DataprocClusterManager(cluster_metadata)
from apache_beam.runners.interactive.dataproc.dataproc_cluster_manager import _LOGGER
with self.assertLogs(
_LOGGER,
level='ERROR') as context_manager, self.assertRaises(ValueError):
cluster_manager.get_cluster_details()
self.assertTrue(
'Due to insufficient project permissions' in
context_manager.output[0])
def test_list_clusters(self):
meta = ClusterMetadata(project_id='project')
dcm = self.current_env.clusters.create(meta)
p = beam.Pipeline()
dcm.pipelines.add(p)
self.current_env.clusters.pipelines[p] = dcm
cluster_id = obfuscate(meta)
self.assertEqual(
{
cluster_id: {
'cluster_name': meta.cluster_name,
'project': meta.project_id,
'region': meta.region,
'master_url': meta.master_url,
'dashboard': meta.dashboard,
'pipelines': [str(id(p)) for p in dcm.pipelines]
}
}, json.loads(self.current_env.inspector.list_clusters()))
