Hi,
I've been struggling with a similar problem and that's why i've
started working on the outofcore message management, when the memory
shrinks. Your particular problem can get to an upper bound of
exponential space complexity, which you experience with the OOM. the
possible paths you can extract for each source vertex are about
O(d^l), where d is the average degree of the graph and l is the max
length of the extracted path (if you do shortest paths, then it's the
diameter).
Giraph is all good and fast but it's all inmemory and for this reason
it currently lacks a solution to your problem. I suggest you wait
until GIRAPH45 is ready (I should write an email tonight about that
patch).
Hope it makes sense to you,
Claudio
On Mon, Jan 23, 2012 at 10:56 AM, André Kelpe
<efeshundertelf@googlemail.com> wrote:
> Hi list,
>
> I have been investigating giraph for a week now and I have a huge stability
> problem. I am running the trunk against a CDH3u2 hadoop cluster. The problem
> I am trying to solve goes as follows:
>
> In a graph there are 3 kinds of vertices:
>
> 1: end of the world vertices, which have only 1 connected edge
> 2: bivalent vertices, which have exactly 2 connected edges
> 3: multivalent vertices that have nedges connected (n>2)
>
> The goal is now to calculate for each vertex that is not in category 2 all
> the paths to the other reachable non bivalent vertices. One could say all
> pathes between all nonbivalent vertices.
>
> To give an example:
>
> [9]
> 
> 
> <12>
> 
> 
> [5]<13>[6]<11>[7]<10>[8]
>
> In this path I want to know that [5] forms a path to [7] via the edges <13>
> and <11>. [7] forms a path via <12> with [9], via <10> with [8] and
via
> <11><13> with [5]. You get the idea... Directionality is not important.
>
> The algorithm I have is pretty straight forward, in superstep 0 all vertices
> that are nonbivalent send a message to their neighbours via which edge they
> are reachable. In all following supersteps the bivalent vertices are simply
> forwarding this information and the nonbivalent ones are terminating the
> algorithm. The messages that they sent are made using Textwritable instances
> encoding the path.
>
> If I run this algorithm on input with 1 million edges it never finishes, the
> master process and then the others always go out of memory, even with a 10GB
> heap. I know that java programs can be memory hungry, but 10GB heap for
> processing a 40MB input file is a bit to much in book. I have tried all sorts
> of settings, like disabling checkpoints, but nothing makes it finish. I also
> see a slowdown in processing, the first 20ish supersteps are done in no time,
> but then the processing slows down until it crashes in superstep 47.
>
> My questions are: What am I doing wrong? Do you guys have any pointers for
> things to look after? How can I get this thing to finish? Why is it so memory
> hungry?
>
> Thanks a lot for your help!
>
> André

Claudio Martella
claudio.martella@gmail.com
