def startScheduleWorkflow(self, request, context):
try:
rq: WorkflowRequest = request
workflow_json = rq.workflow_json
workflow: Workflow = loads(workflow_json)
workflow_id = self.scheduler_manager.schedule_workflow(workflow=workflow)
return ScheduleResponse(return_code=0, return_msg='', data=str(workflow_id))
except Exception as err:
logging.error(err.args)
return ScheduleResponse(return_code=1, return_msg=str(err), data='0')
def load_workflow_config(config_path: Text) -> WorkFlowConfig:
if config_path.endswith('.json'):
with open(config_path, 'r') as f:
workflow_config_json = f.read()
workflow_config: WorkFlowConfig = loads(workflow_config_json)
return workflow_config
elif config_path.endswith('.yaml'):
workflow_data = yaml_utils.load_yaml_file(config_path)
workflow_config: WorkFlowConfig = WorkFlowConfig()
for k, v in workflow_data.items():
if k == GLOBAL_CONFIG_KEY:
continue
job_config_class = get_job_config_class(v['platform'], v['engine'])
job_config = job_config_class()
job_config_class.from_dict(v, job_config)
workflow_config.add_job_config(k, job_config)
return workflow_config
else:
return None
def submitWorkflow(self, request, context):
try:
rq: ScheduleWorkflowRequest = request
workflow: Workflow = json_utils.loads(rq.workflow_json)
workflow.workflow_name = rq.workflow_name
config = {}
config.update(workflow.project_desc.project_config['blob'])
# config['local_repository'] = self._scheduler_config.repository()
blob_manager = BlobManagerFactory.get_blob_manager(config)
project_path: Text = blob_manager\
.download_blob(workflow_id=workflow.workflow_id,
remote_path=workflow.project_desc.project_config.get('uploaded_project_path'),
local_path=self._scheduler_config.repository())
project_desc: ProjectDesc = get_project_description_from(
project_path)
project_name = project_desc.project_name
# update workflow
workflow.project_desc = project_desc
for n, j in workflow.jobs.items():
j.job_config.project_desc = project_desc
j.job_config.project_path = project_path
workflow_info = self._scheduler.submit_workflow(
workflow, project_desc)
if workflow_info is None:
return WorkflowInfoResponse(result=ResultProto(
status=StatusProto.ERROR,
error_message='{}, {} do not exist!'.format(
project_name, workflow.workflow_name)))
return WorkflowInfoResponse(
result=ResultProto(status=StatusProto.OK),
workflow=workflow_to_proto(workflow_info))
except Exception as err:
return WorkflowInfoResponse(
result=ResultProto(status=StatusProto.ERROR,
error_message=traceback.format_exc()))
def test_json(self):
channel = DataEdge("a", 0)
json_text = json_utils.dumps(channel)
c2: DataEdge = json_utils.loads(json_text)
self.assertEqual(channel.target_node_id, c2.target_node_id)
self.assertEqual(channel.port, c2.port)
def __init__(self, job_file, *args, **kwargs):
super(KubernetesFlinkOperator, self).__init__(*args, **kwargs)
with open(file=job_file, mode='rt') as f:
job = f.read()
self.job = json_utils.loads(job)
self.plugin = KubernetesFlinkJobPlugin()
def test_json(self):
node = BaseNode(name="a")
json_text = json_utils.dumps(node)
print(json_text)
n2: BaseNode = json_utils.loads(json_text)
self.assertEqual(node.name, n2.name)
def __init__(self, job, *args, **kwargs):
super(KubernetesCMDOperator, self).__init__(*args, **kwargs)
self.job = json_utils.loads(job)
self.plugin = KubernetesCMDJobPlugin()
def load_graph(json_text: str) -> Graph:
graph: Graph = loads(json_text)
return graph
