Created
July 18, 2011 02:47
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eventlet is slower than sync pymongo queries?
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# > time python async_pymongo.py | |
# | |
# real 0m0.511s | |
# user 0m0.220s | |
# sys 0m0.170s | |
import pymongo | |
import eventlet | |
eventlet.monkey_patch() | |
POOL_SIZE = 10 | |
class SocketWrapper(object): | |
__slots__ = ('__pool','__sock') | |
def __init__(self,pool,sock): | |
self.__pool = pool | |
self.__sock = sock | |
def __getattr__(self,name): | |
return getattr(self.__sock,name) | |
def __del__(self): | |
self.__pool.sockets.put(self.__sock) | |
del self.__pool | |
del self.__sock | |
class Pool(object): | |
def __init__(self,socket_factory,max_pool_size=POOL_SIZE): | |
self.socket_factory = socket_factory | |
self.max_pool_size = min(max_pool_size,POOL_SIZE) | |
self.sockets = None | |
def socket(self): | |
if not self.sockets: | |
self.initialize() | |
return SocketWrapper(self,self.sockets.get()) | |
def initialize(self): | |
self.sockets = Queue(self.max_pool_size) | |
for i in range(self.max_pool_size): | |
sock = self.socket_factory() | |
self.sockets.put(sock) | |
def return_socket(self): | |
pass | |
pymongo.connection._Pool = Pool | |
db = pymongo.Connection().test | |
def do(*args, **kwargs): | |
db.test2.insert(*args) | |
pool = eventlet.GreenPool(size=1000) | |
pile = eventlet.GreenPile(pool) | |
[pool.spawn_n(do, {'num': i}) for i in xrange(1000)] | |
pool.waitall() |
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# > time python sync_pymongo.py | |
# | |
# real 0m0.356s | |
# user 0m0.120s | |
# sys 0m0.150s | |
import pymongo | |
c = pymongo.Connection() | |
db = c.test | |
for i in xrange(1000): | |
db.test2.insert({'num': i}) |
yep exactly. if the mongo server was on a big 32 core box I bet the results would be different. then it (mongo) would be able to do the work in parallel.
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Did you ever get anywhere with this?
My suspicion is that the overhead of eventlet is actually more than the cost of an individual insert when doing it against a local server without any other load hitting it and no indices to worry about.