Performance Guarantees for Distributed Reachability Queries

TL;DR

This paper introduces distributed algorithms for reachability queries on fragmented graphs, providing performance guarantees and demonstrating scalability in real-world and synthetic datasets.

Contribution

It presents novel distributed evaluation algorithms for reachability, bounded reachability, and regular reachability, with proven performance guarantees and MapReduce implementation.

Findings

Algorithms visit each site only once

Network traffic depends on query size and fragmentation

Algorithms are scalable on large, distributed graphs

Abstract

In the real world a graph is often fragmented and distributed across different sites. This highlights the need for evaluating queries on distributed graphs. This paper proposes distributed evaluation algorithms for three classes of queries: reachability for determining whether one node can reach another, bounded reachability for deciding whether there exists a path of a bounded length between a pair of nodes, and regular reachability for checking whether there exists a path connecting two nodes such that the node labels on the path form a string in a given regular expression. We develop these algorithms based on partial evaluation, to explore parallel computation. When evaluating a query Q on a distributed graph G, we show that these algorithms possess the following performance guarantees, no matter how G is fragmented and distributed: (1) each site is visited only once; (2) the total network traffic is determined by the size of Q and the fragmentation of G, independent of the size of G; and (3) the response time is decided by the largest fragment of G rather than the entire G. In addition, we show that these algorithms can be readily implemented in the MapReduce framework. Using synthetic and real-life data, we experimentally verify that these algorithms are scalable on large graphs, regardless of how the graphs are distributed.