Hi,

I was considering an issue not discussed in Pregel paper. One
interesting thing about MapReduce is that the memory limit for each job
in a cluster node is the number of task assigned to that node * the
memory allocated by each task (plus of course the framework overhead).
The input data is iteratively loaded (and kind of emitted too) from
storage and doesn't need to be kept in memory or loaded together in advance.

In Pregel, to me, it looks like the whole graph has to fit in memory
among the cluster nodes. As it is somehow stateful and doesn't have an
iterative job-job nature as MapReduce, at the beginning of the job all
the vertices and their data have to be loaded into the cluster (and kept
in memory).

So the question is: if i want to run Pagerank over my graph, do I need
to be able to store the whole graph in memory?


Thanks!

-- 
Claudio Martella
Digital Technologies
Unit Research & Development - Analyst

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