I already committed a fix in that direction. I modified our FixedSizePriorityQueue to allow inspection of its head for direct comparison. This obviates the need to instantiate a Comparable and offer it to the queue.
/s On 06.03.2013 17:01, Ted Dunning wrote: > I would recommend against a mutable object on maintenance grounds. > > Better is to keep the threshold that a new score must meet and only > construct the object on need. That cuts the allocation down to negligible > levels. > > On Wed, Mar 6, 2013 at 6:11 AM, Sean Owen <sro...@gmail.com> 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 <h...@joshdevins.com> 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. >>> >>> >> >
