def modify_job_state(self, job_id, new_state):
"""Modify the run state of the job.
Args:
job_id: The id of the job.
new_state: A string representing the new desired state. It could be set to
either 'JOB_STATE_DONE', 'JOB_STATE_CANCELLED' or 'JOB_STATE_DRAINING'.
Returns:
True if the job was modified successfully.
"""
if new_state == 'JOB_STATE_DONE':
new_state = dataflow.Job.RequestedStateValueValuesEnum.JOB_STATE_DONE
elif new_state == 'JOB_STATE_CANCELLED':
new_state = dataflow.Job.RequestedStateValueValuesEnum.JOB_STATE_CANCELLED
elif new_state == 'JOB_STATE_DRAINING':
new_state = dataflow.Job.RequestedStateValueValuesEnum.JOB_STATE_DRAINING
else:
# Other states could only be set by the service.
return False
request = dataflow.DataflowProjectsLocationsJobsUpdateRequest()
request.jobId = job_id
request.projectId = self.google_cloud_options.project
request.location = self.google_cloud_options.region
request.job = dataflow.Job(requestedState=new_state)
self._client.projects_locations_jobs.Update(request)
return True
def __init__(self, options, proto_pipeline):
self.options = options
self.proto_pipeline = proto_pipeline
self.google_cloud_options = options.view_as(GoogleCloudOptions)
if not self.google_cloud_options.job_name:
self.google_cloud_options.job_name = self.default_job_name(
self.google_cloud_options.job_name)
required_google_cloud_options = [
'project', 'job_name', 'temp_location'
]
missing = [
option for option in required_google_cloud_options
if not getattr(self.google_cloud_options, option)
]
if missing:
raise ValueError('Missing required configuration parameters: %s' %
missing)
if not self.google_cloud_options.staging_location:
logging.info(
'Defaulting to the temp_location as staging_location: %s',
self.google_cloud_options.temp_location)
(self.google_cloud_options.staging_location
) = self.google_cloud_options.temp_location
# Make the staging and temp locations job name and time specific. This is
# needed to avoid clashes between job submissions using the same staging
# area or team members using same job names. This method is not entirely
# foolproof since two job submissions with same name can happen at exactly
# the same time. However the window is extremely small given that
# time.time() has at least microseconds granularity. We add the suffix only
# for GCS staging locations where the potential for such clashes is high.
if self.google_cloud_options.staging_location.startswith('gs://'):
path_suffix = '%s.%f' % (self.google_cloud_options.job_name,
time.time())
self.google_cloud_options.staging_location = FileSystems.join(
self.google_cloud_options.staging_location, path_suffix)
self.google_cloud_options.temp_location = FileSystems.join(
self.google_cloud_options.temp_location, path_suffix)
self.proto = dataflow.Job(name=self.google_cloud_options.job_name)
if self.options.view_as(StandardOptions).streaming:
self.proto.type = dataflow.Job.TypeValueValuesEnum.JOB_TYPE_STREAMING
else:
self.proto.type = dataflow.Job.TypeValueValuesEnum.JOB_TYPE_BATCH
# Labels.
if self.google_cloud_options.labels:
self.proto.labels = dataflow.Job.LabelsValue()
for label in self.google_cloud_options.labels:
parts = label.split('=', 1)
key = parts[0]
value = parts[1] if len(parts) > 1 else ''
self.proto.labels.additionalProperties.append(
dataflow.Job.LabelsValue.AdditionalProperty(key=key,
value=value))
self.base64_str_re = re.compile(r'^[A-Za-z0-9+/]*=*$')
self.coder_str_re = re.compile(r'^([A-Za-z]+\$)([A-Za-z0-9+/]*=*)$')
def test_create_job_returns_existing_job(self):
pipeline_options = PipelineOptions([
'--project',
'test_project',
'--job_name',
'test_job_name',
'--temp_location',
'gs://test-location/temp',
])
job = apiclient.Job(pipeline_options, FAKE_PIPELINE_URL)
self.assertTrue(job.proto.clientRequestId) # asserts non-empty string
pipeline_options.view_as(GoogleCloudOptions).no_auth = True
client = apiclient.DataflowApplicationClient(pipeline_options)
response = dataflow.Job()
# different clientRequestId from `job`
response.clientRequestId = "20210821081910123456-1234"
response.name = 'test_job_name'
response.id = '2021-08-19_21_18_43-9756917246311111021'
with mock.patch.object(client._client.projects_locations_jobs,
'Create',
side_effect=[response]):
with mock.patch.object(client, 'create_job_description',
side_effect=None):
with self.assertRaises(
apiclient.DataflowJobAlreadyExistsError) as context:
client.create_job(job)
self.assertEqual(
str(context.exception),
'There is already active job named %s with id: %s. If you want to '
'submit a second job, try again by setting a different name using '
'--job_name.' % ('test_job_name', response.id))
def test_update_job_returns_existing_job(self):
pipeline_options = PipelineOptions([
'--project',
'test_project',
'--job_name',
'test_job_name',
'--temp_location',
'gs://test-location/temp',
'--region',
'us-central1',
'--update',
])
replace_job_id = '2021-08-21_00_00_01-6081497447916622336'
with mock.patch('apache_beam.runners.dataflow.internal.apiclient.Job.'
'job_id_for_name',
return_value=replace_job_id) as job_id_for_name_mock:
job = apiclient.Job(pipeline_options, FAKE_PIPELINE_URL)
job_id_for_name_mock.assert_called_once()
self.assertTrue(job.proto.clientRequestId) # asserts non-empty string
pipeline_options.view_as(GoogleCloudOptions).no_auth = True
client = apiclient.DataflowApplicationClient(pipeline_options)
response = dataflow.Job()
# different clientRequestId from `job`
response.clientRequestId = "20210821083254123456-1234"
response.name = 'test_job_name'
response.id = '2021-08-19_21_29_07-5725551945600207770'
with mock.patch.object(client, 'create_job_description', side_effect=None):
with mock.patch.object(client._client.projects_locations_jobs,
'Create',
side_effect=[response]):
with self.assertRaises(
apiclient.DataflowJobAlreadyExistsError) as context:
client.create_job(job)
self.assertEqual(
str(context.exception),
'The job named %s with id: %s has already been updated into job '
'id: %s and cannot be updated again.' %
('test_job_name', replace_job_id, response.id))
