def _delete_pipeline_metadata(self, pipeline_name: Text):
"""Drops the database containing metadata produced by the pipeline.
Args:
pipeline_name: The name of the pipeline owning the database.
"""
pod_name = self._get_mysql_pod_name()
db_name = self._get_mlmd_db_name(pipeline_name)
command = [
'kubectl',
'-n',
'kubeflow',
'exec',
'-it',
pod_name,
'--',
'mysql',
'--user',
'root',
'--execute',
'drop database if exists {};'.format(db_name),
]
logging.info('Dropping MLMD DB with name: %s', db_name)
with test_utils.Timer('DeletingMLMDDatabase'):
subprocess.run(command, check=True)
def _run_workflow(self,
workflow_file: Text,
workflow_name: Text,
parameter: Dict[Text, Text] = None):
"""Runs the specified workflow with Argo.
Blocks until the workflow has run (successfully or not) to completion.
Args:
workflow_file: YAML file with Argo workflow spec for the pipeline.
workflow_name: Name to use for the workflow.
parameter: mapping from pipeline parameter name to its runtime value.
"""
# TODO(ajaygopinathan): Consider using KFP cli instead.
def _format_parameter(parameter: Dict[Text, Any]) -> List[Text]:
"""Format the pipeline parameter section of argo workflow."""
if parameter:
result = []
for k, v in parameter.items():
result.append('-p')
result.append('{}={}'.format(k, v))
return result
else:
return []
run_command = [
'argo',
'submit',
'--name',
workflow_name,
'--namespace',
'kubeflow',
'--serviceaccount',
'pipeline-runner',
workflow_file,
]
run_command += _format_parameter(parameter)
logging.info('Launching workflow %s with parameter %s', workflow_name,
_format_parameter(parameter))
with test_utils.Timer('RunningPipelineToCompletion'):
subprocess.run(run_command, check=True)
# Wait in the loop while pipeline is pending or running state.
status = 'Pending'
while status in ('Pending', 'Running'):
time.sleep(self._POLLING_INTERVAL_IN_SECONDS)
status = self._get_argo_pipeline_status(workflow_name)
