Graphs are widely used to model data in many application domains. Thanks to the wide spread use of GPS-enabled devices, many applications assign spatial attributes to graph vertexes (e.g., geographic knowledge bases, geo-tagged social media). Graph database systems such as Neo4j and Titan are commonly used to manage and query graph data. Even though an off-the-shelf graph database system allows users to define spatial location semantics on vertexes and edges, existing graph query processors are not natively optimized for spatial predicates. The paper proposes GeoExpand—a query operator that adds spatial data awareness to a graph database management system. GeoExpand allows efficient execution of graph queries that involve spatial predicates. The proposed operator makes use of spatial bitmap entries stored as properties in the graph. GeoExpand leverages such bitmap entries to possibly terminate the graph traversal process early and hence reduces the query latency. Since the spatial bitmap entries are represented using a light-weight data structure, they do not add a lot of storage or maintenance overhead. That makes GeoExpand a practical solution. Experiments based on implementation inside the core kernel of Neo4j prove that the GeoExpand operator exhibits up to two orders of magnitude better query response time than the classic Expand operator used in Neo4j.

中文翻译：

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Neo4j图形数据库系统中的空间修剪顶点扩展算子

图被广泛用于在许多应用程序域中对数据建模。由于启用GPS的设备的广泛使用，许多应用程序将空间属性分配给图形顶点（例如，地理知识库，带有地理标签的社交媒体）。诸如Neo4j和Titan的图形数据库系统通常用于管理和查询图形数据。即使现成的图数据库系统允许用户在顶点和边上定义空间位置语义，但现有的图查询处理器并未针对空间谓词进行本地优化。本文提出了GeoExpand，这是一种查询运算符，可将空间数据感知功能添加到图形数据库管理系统中。GeoExpand允许有效执行涉及空间谓词的图查询。建议的运算符利用空间位图条目存储为图形中的属性。GeoExpand利用此类位图条目可能会尽早终止图形遍历过程，从而减少查询延迟。由于空间位图条目是使用轻量级数据结构表示的，因此它们不会增加很多存储或维护开销。这使GeoExpand成为切实可行的解决方案。基于Neo4j核心内核内部实现的实验证明，与Neo4j中使用的经典Expand运算符相比，GeoExpand运算符的查询响应时间高出两个数量级。