我对GCP很陌生，也不是Python专家，我试图在云函数中运行脚本(在有某种条件的数据库中读/写(，但在GCP中运行需要2分钟(即使是2gb(，而在本地环境中在Jupyter笔记本中运行则需要2分钟。有人能帮我优化这段时间吗？我已经尝试过以2Gb的速度部署云功能，但运行大约2分钟需要同样的时间(我也已经读过这篇文章：为什么谷歌云功能运行超过2分钟？以及云功能的最佳实践，但不那么容易理解！(
云函数中的脚本下方(主函数为：main_binary_aalert(((
import sqlalchemy
import pandas as pd
import pg8000
def load_data_from_db(sql_query):
db=sqlalchemy.create_engine(
"XX",
pool_size=5,
max_overflow=2,
pool_timeout=30,
pool_recycle=1800
)
try:
with db.connect() as conn:
df=pd.read_sql_query(sql_query,con=conn)
except Exception as e:
return 'Error: {}'.format(str(e))
return df
def insert_data_into_db(sql_query):
db=sqlalchemy.create_engine(
"XX",
pool_size=5,
max_overflow=2,
pool_timeout=30,
pool_recycle=1800
)
stmt=sqlalchemy.text(sql_query)
try:
with db.connect() as conn:
conn.execute(stmt)
except Exception as e:
return 'Error: {}'.format(str(e))
return 'ok'
def check_condition(logic_condition,_to_check,check_):
if logic_condition==None or check_==None:
return True
if _to_check==None:
return False
if logic_condition=='superieur':
if _to_check > check_:
return True
else:
return False
if logic_condition=='superieur_ou_egal':
if _to_check >= check_:
return True
else:
return False
if logic_condition=='inferieur':
if _to_check < check_:
return True
else:
return False
if logic_condition=='inferieur_ou_egal':
if _to_check <= check_:
return True
else:
return False
def main_binary_alert(request):
try:
X=0
alert_param=load_data_from_db("SELECT * FROM alert_param")
alert_criteria_binary=[1,4,8,9,16,10,11,12,13,14,15]
alert_param_filterA=alert_param.loc[(alert_param['alert_criteria_id'].isin(alert_criteria_binary)) & (alert_param['alert_mute']==False)]
for row in alert_param_filterA.itertuples():
alert_id=row.alert_id
alert_location_id=row.alert_location_id
value_type_id=row.value_type_id
logic_condition_1=row.logic_condition_1
_condition_1=row._condition_1
logic_condition_2=row.logic_condition_2
_condition_2=row._condition_2
last_same_alert_in_x_day=load_data_from_db("SELECT * FROM alert_reading
WHERE alert_id="+str(alert_id)+"
AND time IN (SELECT MAX(time) FROM alert_reading WHERE alert_id="+str(alert_id)+"AND time >= date_trunc('day',now()-interval '"+str(X)+"day'))
AND time >= date_trunc('day',now()-interval '"+str(X)+"day')")
last_check_button=load_data_from_db("SELECT * FROM binary_reading_client1_raw
WHERE time >= date_trunc('day',now()-interval '"+str(X)+"day')
AND time IN (SELECT MAX(time) FROM binary_reading_client1_raw
WHERE time >= date_trunc('day',now()-interval '"+str(X)+"day')
AND value_id IN (SELECT value_id FROM value WHERE value_type_id=10 AND location_id="+str(alert_location_id)+"))
AND value_id IN (SELECT value_id FROM value WHERE value_type_id=10 AND location_id="+str(alert_location_id)+")"
)
if last_same_alert_in_x_day.empty==True:
if last_check_button.empty==True:
sum_from_X_days=load_data_from_db(
"SELECT SUM() FROM binary_reading_client1_raw
WHERE time >= date_trunc('day',now()-interval '"+str(X)+"day')
AND value_id IN (SELECT value_id FROM value WHERE value_type_id="+str(value_type_id)+"
AND location_id="+str(alert_location_id)+")"
)
if check_condition(logic_condition_1,sum_from_X_days.iloc[0,0],_condition_1)==True & check_condition(logic_condition_2,sum_from_X_days.iloc[0,0],_condition_2)==True:
insert_data_into_db(
"INSERT INTO alert_reading (alert_id,time,location_id) S
("+str(alert_id)+",now(),"+str(alert_location_id)+")"
)
print('case: alert triggered based on counter from X days')
else:
print('case:no alert triggered: no past same alert, no past check, no condition met')
else:
last_check_time=last_check_button.iloc[0,1]
sum_from_last_check=load_data_from_db(
"SELECT SUM() FROM binary_reading_client1_raw
WHERE time >= "+"'"+str(last_check_time)+"'"+"
AND value_id IN (SELECT value_id FROM value WHERE value_type_id="+str(value_type_id)+"
AND location_id="+str(alert_location_id)+")"
)
if check_condition(logic_condition_1,sum_from_last_check.iloc[0,0],_condition_1)==True & check_condition(logic_condition_2,sum_from_last_check.iloc[0,0],_condition_2)==True:
insert_data_into_db(
"INSERT INTO alert_reading (alert_id,time,location_id) S
("+str(alert_id)+",now(),"+str(alert_location_id)+")"
)
print('case: alert triggered based on counter from past time check')
else:
print('case:no alert triggered: no past same alert, past check, no condition met')
else:
last_alert_time=last_same_alert_in_x_day.iloc[0,2]
if last_check_button.empty==True:
sum_from_last_alert=load_data_from_db(
"SELECT SUM() FROM binary_reading_client1_raw
WHERE time >= "+"'"+str(last_alert_time)+"'"+"
AND value_id IN (SELECT value_id FROM value WHERE value_type_id="+str(value_type_id)+"
AND location_id="+str(alert_location_id)+")"
)
if check_condition(logic_condition_1,sum_from_last_alert.iloc[0,0],_condition_1)==True & check_condition(logic_condition_2,sum_from_last_alert.iloc[0,0],_condition_2)==True:
#write an alert in alert_reading
insert_data_into_db(
"INSERT INTO alert_reading (alert_id,time,location_id) S
("+str(alert_id)+",now(),"+str(alert_location_id)+")"
)
print('case: alert triggered based on counter from past time alert')
else:
print('case:no alert triggered: past same alert, no past check, no condition met')
else:
last_check_time=last_check_button.iloc[0,1]
max_time_alert_check=max(last_alert_time,last_check_time)
sum_from_max_time_alert_check=load_data_from_db(
"SELECT SUM() FROM binary_reading_client1_raw
WHERE time >= "+"'"+str(max_time_alert_check)+"'"+"
AND value_id IN (SELECT value_id FROM value WHERE value_type_id="+str(value_type_id)+"
AND location_id="+str(alert_location_id)+")"
)
if check_condition(logic_condition_1,sum_from_max_time_alert_check.iloc[0,0],_condition_1)==True & check_condition(logic_condition_2,sum_from_max_time_alert_check.iloc[0,0],_condition_2)==True:
insert_data_into_db(
"INSERT INTO alert_reading (alert_id,time,location_id) S
("+str(alert_id)+",now(),"+str(alert_location_id)+")"
)
print('case: alert triggered based on counter from max time alert and check')
else:
print('case:no alert triggered: past same alert, past check, no condition met')
return ("ok", 200)
except Exception as e:
return 'Error: {}'.format(str(e))
函数是无状态的，执行环境通常是从头开始初始化的，这被称为冷启动，这意味着只要云函数在一段时间内不运行，它就会很慢。增加的延迟是由于云功能每次都会启动运行环境。
那么，你该如何缩短响应时间呢。您所要做的就是使cloud函数每隔一段时间运行一次。Cronjobs就是为这类任务而设计的。由于您已经在谷歌云平台上运行，请查看他们的调度程序。您可以尝试使用此参考执行
我每分钟创建一个云调度程序作业来执行云功能。
Frequency is * * * * * (means every minute).
Time Zone is US Newyork, the same region in which the cloud function was created(us-central1)
URL would be the cloud function’s endpoint and trigger URL.
Auth Header has to be specified as an Add OIDC token and create a service account and give the role Cloud functions Invoker permissions to this service account.
Audience is again cloud functions endpoint trigger URL.
Maximum retry attempts is 2 or anything as per your request
Max retry duration is 0s which means unlimited.
通过每分钟调度一个cron作业，我正在运行云功能，这样它就不必面临冷启动。如果一个函数在10分钟左右的时间内执行，那么每次都会从头开始，并且需要更长的部署时间。
使用这种方法，云函数将缓存此运行环境。因此，周期性地(每1分钟(运行，同时高速缓存是"0"；热的"；不会产生启动惩罚。
注意：这可能会给你带来不必要的成本，因为每分钟安排一次活动可能会耗尽你的免费配额。
如需更多参考，请查看云功能及其最佳实践的链接。