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GRAIL: a scalable index for reachability queries in very large graphs

机译:GRAIL:可伸缩性索引,用于在非常大的图形中进行可达性查询

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Given a large directed graph, rapidly answering reachability queries between source and target nodes is an important problem. Existing methods for reachability tradeoff indexing time and space versus query time performance. However, the biggest limitation of existing methods is that they do not scale to very large real-world graphs. We present a simple yet scalable reachability index, called GRAIL, that is based on the idea of randomized interval labeling and that can effectively handle very large graphs. Based on an extensive set of experiments, we show that while more sophisticated methods work better on small graphs, GRAIL is the only index that can scale to millions of nodes and edges. GRAIL has linear indexing time and space, and the query time ranges from constant time to being linear in the graph order and size. Our reference C++ implementations are open source and available for download at .
机译:给定一个大的有向图,快速回答源节点和目标节点之间的可达性查询是一个重要的问题。可达性折衷索引时间和空间与查询时间性能的现有方法。但是,现有方法的最大局限性在于它们无法缩放到非常大的实际图形。我们提出了一个简单而可扩展的可达性索引,称为GRAIL,它基于随机间隔标签的思想,可以有效处理非常大的图形。基于大量的实验,我们表明,虽然更复杂的方法在小型图上更有效,但GRAIL是唯一可以缩放到数百万个节点和边的索引。 GRAIL具有线性索引时间和空间,查询时间的范围从恒定时间到图形顺序和大小都是线性的。我们的参考C ++实现是开源的,可以从下载。

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