I think the job had 5000 - 6000 clusters. The input (sparse) vectors had a dimension of 6838856.
-- james On Fri, Feb 4, 2011 at 1:55 AM, Ted Dunning <[email protected]> wrote: > How many clusters? > > How large is the dimension of your input data? > > On Thu, Feb 3, 2011 at 9:05 PM, james q <[email protected]> > wrote: > > > Hello, > > > > New user to mahout and hadoop here. Isabel Drost suggested to a colleague > I > > should post to the mahout user list, as I am having some general > > difficulties with memory consumption and KMeans clustering. > > > > So a general question first and foremost: what determines how much memory > > does a map task consume during a KMeans clustering job? Increasing the > > number of map tasks by adjusting dfs.block.size and mapred.max.split.size > > doesn't seem to make the map task consume less memory. Or at least not a > > very noticeable amount. I figured if there are more map tasks, each > > individual map task evaluates less input keys and hence there would be > less > > memory consumption. Is there any way to predict memory usage of map tasks > > in > > KMeans? > > > > The cluster I am running consists of 10 machines, each with 8 cores and > 68G > > of ram. I've configured the cluster to have each machine, at maximum, run > 7 > > map or reduce tasks. I set the map and reduce tasks to have virtually no > > limit on memory consumption ... so with 7 processes each, at around 9 - > 10G > > per process, the machines will crap out. I can reduce the number of map > > tasks per machine, but something tells me that that level of memory > > consumption is wrong. > > > > If any more information is needed to help debug this, please let me know! > > Thanks! > > > > -- james > > >
