分布式可达性的性能保证
Performance Guarantees for Distributed Reachability Queries
摘要：
在现实世界中，一个图通常是碎片化的，分布在不同的站点上。这突出了在分布式图上评估查询的需要。本文提出了三种类型的查询的分布式评估算法：可达性，以确定一个节点是否可以到达另一个，有界可达性，以确定是否存在一个有界长度的路径之间的一对节点，并定期可达性检查是否存在一个路径连接两个节点，使路径上的节点标签形成一个字符串在一个给定的正则表达式。我们开发这些算法的基础上部分评估，探索并行计算。当在分布图G上计算查询Q时，我们证明了这些算法具有以下性能保证，无论G如何分割和分布：（1）每个站点只被访问一次;（2）网络总流量由Q的大小和G的分割决定，与G的大小无关;（3）响应时间由G的最大片段而不是整个G决定。此外，我们表明，这些算法可以很容易地在MapReduce框架中实现。使用合成和现实生活中的数据，我们实验验证，这些算法是可扩展的大型图形，无论图形是如何分布。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
