def execute(self, context):
emr = EmrHook(aws_conn_id=self.aws_conn_id).get_conn()
self.log.info('Adding steps to %s', self.job_flow_id)
response = emr.add_job_flow_steps(JobFlowId=self.job_flow_id, Steps=self.steps)
if response['ResponseMetadata']['HTTPStatusCode'] != 200:
raise AirflowException('Adding steps failed: %s' % response)
self.log.info('Steps %s added to JobFlow', response['StepIds'])
return response['StepIds']
def execute(self, context):
emr = EmrHook(aws_conn_id=self.aws_conn_id).get_conn()
logging.info("Adding steps to %s", self.job_flow_id)
response = emr.add_job_flow_steps(JobFlowId=self.job_flow_id, Steps=self.steps)
if not response["ResponseMetadata"]["HTTPStatusCode"] == 200:
raise AirflowException("Adding steps failed: %s" % response)
else:
logging.info("Steps %s added to JobFlow", response["StepIds"])
return response["StepIds"]
def execute(self, context):
emr = EmrHook(aws_conn_id=self.aws_conn_id).get_conn()
self.log.info('Adding steps to %s', self.job_flow_id)
response = emr.add_job_flow_steps(JobFlowId=self.job_flow_id, Steps=self.steps)
if not response['ResponseMetadata']['HTTPStatusCode'] == 200:
raise AirflowException('Adding steps failed: %s' % response)
else:
self.log.info('Steps %s added to JobFlow', response['StepIds'])
return response['StepIds']
def execute(self, context):
attempt = context['ti'].try_number
logging.info('attempt: {}'.format(attempt))
emr = EmrHook(aws_conn_id=self.aws_conn_id).get_conn()
job_flow_id = self.job_flow_id
if not job_flow_id:
job_flow_id = emr.get_cluster_id_by_name(self.job_flow_name,
self.cluster_states)
if self.do_xcom_push:
context['ti'].xcom_push(key='job_flow_id', value=job_flow_id)
step_name = self.step_name if attempt == 1 else "{} (attempt {})".format(
self.step_name, attempt)
action_on_failure = self.action_on_failure
if attempt % 3 == 0:
action_on_failure = 'TERMINATE_JOB_FLOW'
spark_conf = self.get_spark_params_config(self.spark_params,
self.spark_conf)
steps = self.generate_spark_step(step_name, self.main_class,
self.app_name, spark_conf,
self.application_args, self.jar_path,
action_on_failure)
logging.info("spark_params: " + str(steps))
self.log.info('Adding steps to %s', job_flow_id)
response = emr.add_job_flow_steps(JobFlowId=job_flow_id, Steps=steps)
logging.info('Running Spark Job {} with JobFlow ID {}'.format(
self.task_id, self.job_flow_id))
while True:
step_id = response['StepIds'][0]
logging.info('step id - {}'.format(step_id))
result = self.describe_step(emr, response)
step_status = result['Step']['Status']['State']
logging.info('step status - {}'.format(step_status))
# step state can be 'PENDING'|'CANCEL_PENDING'|'RUNNING'|'COMPLETED'|'CANCELLED'|'FAILED'|'INTERRUPTED'
if step_status == 'COMPLETED':
break
elif step_status != 'COMPLETED' and step_status != 'PENDING' and step_status != 'RUNNING':
raise AirflowException('Spark job {} has failed'.format(
self.task_id))
logging.info("Spark Job '{}' status is {}".format(
self.task_id, step_status))
def execute(self, context):
emr = EmrHook(aws_conn_id=self.aws_conn_id).get_conn()
job_flow_id = self.job_flow_id
if not job_flow_id:
job_flow_id = emr.get_cluster_id_by_name(self.job_flow_name, self.cluster_states)
if self.do_xcom_push:
context['ti'].xcom_push(key='job_flow_id', value=job_flow_id)
self.log.info('Adding steps to %s', job_flow_id)
response = emr.add_job_flow_steps(JobFlowId=job_flow_id, Steps=self.steps)
if not response['ResponseMetadata']['HTTPStatusCode'] == 200:
raise AirflowException('Adding steps failed: %s' % response)
else:
self.log.info('Steps %s added to JobFlow', response['StepIds'])
return response['StepIds']
