Run Multiple Athena Queries in Airflow 2.0(在AirFlow 2.0中运行多个雅典娜查询)
本文介绍了在AirFlow 2.0中运行多个雅典娜查询的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!
问题描述
我正在尝试创建一个DAG,其中一个任务使用boto3
执行athena
查询。它对一个查询有效,但是当我尝试运行多个雅典娜查询时遇到问题。
此问题可以按如下方式解决:-
- 翻阅thisblog可以看到,
athena
使用start_query_execution
触发查询,get_query_execution
获取status
、queryExecutionId
等查询数据(athena的文档)
遵循上述模式后,我有以下代码:-
import json
import time
import asyncio
import boto3
import logging
from airflow import DAG
from airflow.operators.python import PythonOperator
def execute_query(client, query, database, output_location):
response = client.start_query_execution(
QueryString=query,
QueryExecutionContext={
'Database': database
},
ResultConfiguration={
'OutputLocation': output_location
}
)
return response['QueryExecutionId']
async def get_ids(client_athena, query, database, output_location):
query_responses = []
for i in range(5):
query_responses.append(execute_query(client_athena, query, database, output_location))
res = await asyncio.gather(*query_responses, return_exceptions=True)
return res
def run_athena_query(query, database, output_location, region_name, **context):
BOTO_SESSION = boto3.Session(
aws_access_key_id = 'YOUR_KEY',
aws_secret_access_key = 'YOUR_ACCESS_KEY')
client_athena = BOTO_SESSION.client('athena', region_name=region_name)
loop = asyncio.get_event_loop()
query_execution_ids = loop.run_until_complete(get_ids(client_athena, query, database, output_location))
loop.close()
repetitions = 900
error_messages = []
s3_uris = []
while repetitions > 0 and len(query_execution_ids) > 0:
repetitions = repetitions - 1
query_response_list = client_athena.batch_get_query_execution(
QueryExecutionIds=query_execution_ids)['QueryExecutions']
for query_response in query_response_list:
if 'QueryExecution' in query_response and
'Status' in query_response['QueryExecution'] and
'State' in query_response['QueryExecution']['Status']:
state = query_response['QueryExecution']['Status']['State']
if state in ['FAILED', 'CANCELLED']:
error_reason = query_response['QueryExecution']['Status']['StateChangeReason']
error_message = 'Final state of Athena job is {}, query_execution_id is {}. Error: {}'.format(
state, query_execution_id, error_message
)
error_messages.append(error_message)
query_execution_ids.remove(query_response['QueryExecutionId'])
elif state == 'SUCCEEDED':
result_location = query_response['QueryExecution']['ResultConfiguration']['OutputLocation']
s3_uris.append(result_location)
query_execution_ids.remove(query_response['QueryExecutionId'])
time.sleep(2)
logging.exception(error_messages)
return s3_uris
DEFAULT_ARGS = {
'owner': 'ubuntu',
'depends_on_past': True,
'start_date': datetime(2021, 6, 8),
'retries': 0,
'concurrency': 2
}
with DAG('resync_job_dag', default_args=DEFAULT_ARGS, schedule_interval=None) as dag:
ATHENA_QUERY = PythonOperator(
task_id='athena_query',
python_callable=run_athena_query,
provide_context=True,
op_kwargs={
'query': 'SELECT request_timestamp FROM "sampledb"."elb_logs" limit 10;', # query provide in athena tutorial
'database':'sampledb',
'output_location':'YOUR_BUCKET',
'region_name':'YOUR_REGION'
}
)
ATHENA_QUERY
运行上述代码时,我收到以下错误:-
[2021-06-16 20:34:52,981] {taskinstance.py:1455} ERROR - An asyncio.Future, a coroutine or an awaitable is required
Traceback (most recent call last):
File "/home/ubuntu/venv/lib/python3.6/site-packages/airflow/models/taskinstance.py", line 1112, in _run_raw_task
self._prepare_and_execute_task_with_callbacks(context, task)
File "/home/ubuntu/venv/lib/python3.6/site-packages/airflow/models/taskinstance.py", line 1285, in _prepare_and_execute_task_with_callbacks
result = self._execute_task(context, task_copy)
File "/home/ubuntu/venv/lib/python3.6/site-packages/airflow/models/taskinstance.py", line 1315, in _execute_task
result = task_copy.execute(context=context)
File "/home/ubuntu/venv/lib/python3.6/site-packages/airflow/operators/python.py", line 117, in execute
return_value = self.execute_callable()
File "/home/ubuntu/venv/lib/python3.6/site-packages/airflow/operators/python.py", line 128, in execute_callable
return self.python_callable(*self.op_args, **self.op_kwargs)
File "/home/ubuntu/iac-airflow/dags/helper/tasks.py", line 93, in run_athena_query
query_execution_ids = loop.run_until_complete(get_ids(client_athena, query, database, output_location))
File "/usr/lib/python3.6/asyncio/base_events.py", line 484, in run_until_complete
return future.result()
File "/home/ubuntu/iac-airflow/dags/helper/tasks.py", line 79, in get_ids
res = await asyncio.gather(*query_responses, return_exceptions=True)
File "/usr/lib/python3.6/asyncio/tasks.py", line 602, in gather
fut = ensure_future(arg, loop=loop)
File "/usr/lib/python3.6/asyncio/tasks.py", line 526, in ensure_future
raise TypeError('An asyncio.Future, a coroutine or an awaitable is '
TypeError: An asyncio.Future, a coroutine or an awaitable is required
我不能到达我错的地方。如能就此问题给予一些提示
,我将不胜感激。推荐答案
我认为您在这里做的事情并不是真的需要。 您的问题是:
- 并行执行多个查询。
- 能够恢复每个查询
queryExecutionId
。
这两个问题只需使用AWSAthenaOperator
即可解决。操作员已经为您处理了您提到的所有事情。
示例:
from airflow.models import DAG
from airflow.utils.dates import days_ago
from airflow.operators.dummy import DummyOperator
from airflow.providers.amazon.aws.operators.athena import AWSAthenaOperator
with DAG(
dag_id="athena",
schedule_interval='@daily',
start_date=days_ago(1),
catchup=False,
) as dag:
start_op = DummyOperator(task_id="start_task")
query_list = ["SELECT 1;", "SELECT 2;" "SELECT 3;"]
for i, sql in enumerate(query_list):
run_query = AWSAthenaOperator(
task_id=f'run_query_{i}',
query=sql,
output_location='s3://my-bucket/my-path/',
database='my_database'
)
start_op >> query_op
只需向query_list
添加更多查询即可动态创建雅典娜任务:
请注意,QueryExecutionId
是pushed to xcom,因此您可以根据需要访问下游任务中的。
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