We have a server that gets cranky if it gets too many users logging in at the same time (meaning less than 7 seconds apart). Once the users are logged in, there is no problem (one or two logging in at the same time is also not a problem, but when 10-20 try the entire server goes into a death spiral sigh).
I'm attempting to write a page that will hold onto users (displaying an animated countdown etc.) and let them through 7 seconds apart. The algorithm is simple
t+7
is in the past start the login and store now()
as the new timestampt+7
is in the future, store it as the new timestamp, wait until t+7
, then start the login.A straight forward python/redis implementation would be:
import time, redis
SLOT_LENGTH = 7 # seconds
now = time.time()
r = redis.StrictRedis()
# lines below contain race condition..
last_start = float(r.get('FLOWCONTROL') or '0.0') # 0.0 == time-before-time
my_start = last_start + SLOT_LENGTH
r.set('FLOWCONTROL', max(my_start, now))
wait_period = max(0, my_start - now)
time.sleep(wait_period)
# .. login
The race condition here is obvious, many processes can be at the my_start =
line simultaneously. How can I solve this using redis?
I've tried the redis-py pipeline
functionality, but of course that doesn't get an actual value until in the r.get()
call...
I'll document the answer in case anyone else finds this...
r = redis.StrictRedis()
with r.pipeline() as p:
while 1:
try:
p.watch('FLOWCONTROL') # --> immediate mode
last_slot = float(p.get('FLOWCONTROL') or '0.0')
p.multi() # --> back to buffered mode
my_slot = last_slot + SLOT_LENGTH
p.set('FLOWCONTROL', max(my_slot, now))
p.execute() # raises WatchError if anyone changed TCTR-FLOWCONTROL
break # break out of while loop
except WatchError:
pass # someone else got there before us, retry.
a little more complex than the original three lines...