JF 2013 29th IEEE International Conference on Data Engineering (ICDE 2013)

YR 2013

VO 00

IS

SP 62

TI Enumerating subgraph instances using map-reduce

A1 F. N. Afrati,

A1 D. Fotakis,

A1 J. D. Ullman, K1 Partitioning algorithms

K1 Approximation algorithms

K1 Complexity theory

K1 Silicon

K1 Educational institutions

K1 Abstracts

K1 Probabilistic logic

AB The theme of this paper is how to find all instances of a given “sample” graph in a larger “data graph,” using a single round of map-reduce. For the simplest sample graph, the triangle, we improve upon the best known such algorithm. We then examine the general case, considering both the communication cost between mappers and reducers and the total computation cost at the reducers. To minimize communication cost, we exploit the techniques of [1] for computing multiway joins (evaluating conjunctive queries) in a single map-reduce round. Several methods are shown for translating sample graphs into a union of conjunctive queries with as few queries as possible. We also address the matter of optimizing computation cost. Many serial algorithms are shown to be “convertible,” in the sense that it is possible to partition the data graph, explore each partition in a separate reducer, and have the total computation cost at the reducers be of the same order as the computation cost of the serial algorithm.

PB IEEE Computer Society, [URL:http://www.computer.org]

SN 1063-6382

LA English

DO 10.1109/ICDE.2013.6544814

LK http://doi.ieeecomputersociety.org/10.1109/ICDE.2013.6544814