我在气流中进行了以下DAG,我正在执行一组EMRSteps来运行我的管道。
default_args = {
'owner': 'airflow',
'depends_on_past': False,
'start_date': datetime(2017, 07, 20, 10, 00),
'email': ['airflow@airflow.com'],
'email_on_failure': False,
'email_on_retry': False,
'retries': 5,
'retry_delay': timedelta(minutes=2),
}
dag = DAG('dag_import_match_hourly',
default_args=default_args,
description='Fancy Description',
schedule_interval=timedelta(hours=1),
dagrun_timeout=timedelta(hours=2))
try:
merge_s3_match_step = EmrAddStepsOperator(
task_id='merge_s3_match_step',
job_flow_id=cluster_id,
aws_conn_id='aws_default',
steps=create_step('Merge S3 Match'),
dag=dag
)
mapreduce_step = EmrAddStepsOperator(
task_id='mapreduce_match_step',
job_flow_id=cluster_id,
aws_conn_id='aws_default',
steps=create_step('MapReduce Match Hourly'),
dag=dag
)
merge_hdfs_step = EmrAddStepsOperator(
task_id='merge_hdfs_step',
job_flow_id=cluster_id,
aws_conn_id='aws_default',
steps=create_step('Merge HDFS Match Hourly'),
dag=dag
)
## Sensors
check_merge_s3 = EmrStepSensor(
task_id='watch_merge_s3',
job_flow_id=cluster_id,
step_id="{{ task_instance.xcom_pull('merge_s3_match_step', key='return_value')[0] }}",
aws_conn_id='aws_default',
dag=dag
)
check_mapreduce = EmrStepSensor(
task_id='watch_mapreduce',
job_flow_id=cluster_id,
step_id="{{ task_instance.xcom_pull('mapreduce_match_step', key='return_value')[0] }}",
aws_conn_id='aws_default',
dag=dag
)
check_merge_hdfs = EmrStepSensor(
task_id='watch_merge_hdfs',
job_flow_id=cluster_id,
step_id="{{ task_instance.xcom_pull('merge_hdfs_step', key='return_value')[0] }}",
aws_conn_id='aws_default',
dag=dag
)
mapreduce_step.set_upstream(merge_s3_match_step)
merge_s3_match_step.set_downstream(check_merge_s3)
mapreduce_step.set_downstream(check_mapreduce)
merge_hdfs_step.set_upstream(mapreduce_step)
merge_hdfs_step.set_downstream(check_merge_hdfs)
except AirflowException as ae:
print ae.message
DAG工作正常,但
我想使用传感器来确保在且仅当EMR作业已正确完成时,我将执行下一步
.我尝试了几件事,但都不管用。上面的代码不能正确完成这项工作。有人知道如何使用EMRSensorStep来实现我的目标吗?