Experiences with Implementing Landmark Embedding in Neo4j
Experiences with Implementing Landmark Embedding in Neo4j
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DOI：
10.1145/3327964.3328496
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发表时间：
2019-06
期刊：
影响因子：
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通讯作者：
Manuel Hotz;Theodoros Chondrogiannis;Leonard Wörteler;Michael Grossniklaus
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文献类型：
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作者：
Manuel Hotz;Theodoros Chondrogiannis;Leonard Wörteler;Michael Grossniklaus
可达性、距离和最短路径查询是图数据管理领域的基本操作，在研究和工业中具有各种应用。然而，虽然已经提出了各种基于预处理的方法来优化这种查询的计算，但是将现有方法集成到图数据库管理系统和处理框架中受到限制。在本文中，我们提出了一种静态图索引的实现，该索引采用Neo4j的地标嵌入，以实现基于索引的可达性计算，距离和最短路径查询。我们探索不同的策略选择地标和不同的计划存储预先计算的地标距离。为了评估每个地标选择策略和每个存储方案的效率，我们使用四个真实世界的网络数据集进行了实验评估。我们测量的预处理成本，查询处理时间，和我们的索引结构的不同配置的距离估计的准确性。
Reachability, distance, and shortest path queries are fundamental operations in the field of graph data management with various applications in research and industry. However, while various preprocessing-based methods have been proposed to optimize the computation of such queries, the integration of existing methods into graph database management systems and processing frameworks has been limited. In this paper, we present an implementation of a static graph index that employs landmark embedding for Neo4j, to enable the index-based computation of reachability, distance, and shortest path queries on the database. We explore different strategies for selecting landmarks and different schemes for storing the precomputed landmark distances. To evaluate the efficiency of each landmark selection strategy and each storage scheme, we conduct an experimental evaluation using four real-world network datasets. We measure the preprocessing cost, the query processing time, and the accuracy of the distance estimation of different configurations of our index structure.