You should go read the manuals. Look for "multiget" or mget or get_multi or whatever functions. I don't know what the equivalent set routines would look like for pylibmemc offhand. It should be in the documentation.
If not, and someone knows, they should pipe up :) -Dormando On Thu, 18 Aug 2011, Neeraj Agarwal wrote: > I have pasted my code above. > > > I tried my program again by writing back the results in a file. > perhaps mongo just pushes the request and returns so it wasn't taking > much time while memcached is a blocking call. > > storing in db 1.26978802681 for 11437 tweets > storing in memcached 1.5911450386 > reading from db 41.3619318008 (was reading > one record at a time from db and writing it to the file) > reading from memcached 1.78016901016 (similarly with > memcached) > > mongodb still winning in terms of writing.. > > Does libmemcached groups multiple get/ set calls? Or are they even > blocking calls? > > Thanks for your time, > Neeraj > > > On Aug 18, 12:08 pm, dormando <[email protected]> wrote: > > > 85 seconds was because of the network latency (was using EC2 with my > > > computer. pinging time was 350 ms itself..) > > > > > Perhaps for x many number of items, it was taking x*350 ms time for > > > making calls.. while mongo, it was sending all data at one go. > > > > > So I ran the script on the server itself: > > > storing in db 0.108298063278 for 1487 items > > > storing in memcached 0.208426952362 > > > reading from db 0.0738799571991 > > > reading from memcached 0.145488023758 > > > > > what am I doing wrong here? > > > > Can you attach your benchmark program? > > > > You should be using multiget to fetch back items quicker. Try using > > pylibmc, which is based off of libmemcached. That may be able to do > > multisets and get you better speed. The other library is pure python, I > > think. Would be slower than a native DB driver. > > > > -Dormando >
