PathEnum：面向实时的跳跃约束的s-t路径枚举
PathEnum: Towards Real-Time Hop-Constrained s-t Path Enumeration
摘要：
研究了跳数约束的s-t路枚举问题，该问题以一个图$G$、两个不同的顶点$s,t$和一个跳数约束$k$为输入，输出从$s$到$t$的所有长度不超过$k$的路径.现有的算法在对具有大搜索空间的工作负载进行枚举时，由于代价高昂的剪枝操作而导致严重的性能问题。因此，这些算法很难满足许多在线应用的实时的【形】约束。在本文中，我们提出了PathEnum，一个有效的基于索引的实时的【形】HcPE算法。对于输入查询，PathEnum首先构建一个轻量级索引，旨在减少枚举中涉及的边的数量，并开发基于索引的高效枚举方法，一种基于深度优先搜索，另一种基于连接。我们进一步开发了一个查询优化器的基础上连接为基础的成本模型，以优化搜索顺序。我们用15个真实世界的图形进行实验。实验结果表明，PathEnum在查询时间、吞吐量和响应时间方面的性能优于现有的方法。
英文摘要：
We study the hop-constrained s-t path enumeration (HcPE) problem, which takes a graph $G$, two distinct vertices $s,t$ and a hop constraint $k$ as input, and outputs all paths from $s$ to $t$ whose length is at most $k$. The state-of-the-art algorithms suffer from severe performance issues caused by the costly pruning operations during enumeration for the workloads with the large search space. Consequently, these algorithms hardly meet the real-time constraints of many online applications. In this paper, we propose PathEnum, an efficient index-based algorithm towards real-time HcPE. For an input query, PathEnum first builds a light-weight index aiming to reduce the number of edges involved in the enumeration, and develops efficient index-based approaches for enumeration, one based on depth-first search and the other based on joins. We further develop a query optimizer based on a join-based cost model to optimize the search order. We conduct experiments with 15 real-world graphs. Our experiment results show that PathEnum outperforms the state-of-the-art approaches by orders of magnitude in terms of the query time, throughput and response time.
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