Btw, all important jobs in ALS are map-only, so its the number of map slotes that counts.
On 06.03.2013 12:11, Sean Owen wrote: > OK, that's reasonable on 35 machines. (You can turn up to 70 reducers, > probably, as most machines can handle 2 reducers at once). > I think the recommendation step loads one whole matrix into memory. You're > not running out of memory but if you're turning up the heap size to > accommodate, you might be hitting swapping, yes. I think (?) the > conventional wisdom is to turn off swap for Hadoop. > > Sebastian yes that is probably a good optimization; I've had good results > reusing a mutable object in this context. > > > On Wed, Mar 6, 2013 at 10:54 AM, Josh Devins <[email protected]> wrote: > >> The factorization at 2-hours is kind of a non-issue (certainly fast >> enough). It was run with (if I recall correctly) 30 reducers across a 35 >> node cluster, with 10 iterations. >> >> I was a bit shocked at how long the recommendation step took and will throw >> some timing debug in to see where the problem lies exactly. There were no >> other jobs running on the cluster during these attempts, but it's certainly >> possible that something is swapping or the like. I'll be looking more >> closely today before I start to consider other options for calculating the >> recommendations. >> >> >
