1. Graph Algorithms
and
MapReduce
Paolo Castagna
The words and opinions expressed here are my own, and do not, in any way, represent the views of my employer.
12. “ ... almost no descriptions of graph
algorithms appear in the literature,
with the exception of a simplified
PageRank calculation and a naive
implementation of finding distances
from a specified node. ”
Graph Twiddling in a MapReduce World, Jonathan Cohen
13. RDF processing
Inference1
(?x p ?y) (?y q r) -> (?x rdf:type t)
(?x p ?y) (?y p ?z) -> (?x p ?z)
1 using a rule engine with forward rules only and a total materialization strategy
26. #3
to communicate with all the
vertex use configuration
parameters of a subsequent
MapReduce job
27. “ Pregel computes over large graphs
much faster than alternatives, and the
application programming interface is
easy to use. Implementing PageRank,
for example, takes only about 15 lines of
code... ”
Official Google Research Blog, Grzegorz Czajkowski
28. “ Pregel computes over large graphs
much faster than alternatives, and the
application programming interface is
easy to use. Implementing PageRank,
for example, takes only about 15 lines of
code... ”
Official Google Research Blog, Grzegorz Czajkowski