论文标题
关于关系和树结构数据（扩展）的跨模型结合查询
Cross-Model Conjunctive Queries over Relation and Tree-structured Data (Extended)
论文作者
论文摘要
连词查询是数据库查询的最基本和中央类别。随着管理和处理大量不同数据的需求的持续增长，几乎没有研究关系和树数据之间的结合查询。在本文中，我们研究了关系和树结构数据（XML和JSON）的跨模型结合查询（CMCQ）。为了有效地处理有界中间结果的CMCQ，我们首先用位置信息编码树节点。使用树节点原始标签值和编码位置值，它允许我们提出的算法CMJoin同时连接关系和树数据，从而避免大量的中间结果。根据标签值和编码位置值的总结果，CMJOIN实现了最坏情况的最优性。实验结果表明，在运行时间和中间结果大小方面，提出的技术回答CMCQ的效率和可伸缩性。
Conjunctive queries are the most basic and central class of database queries. With the continued growth of demands to manage and process the massive volume of different types of data, there is little research to study the conjunctive queries between relation and tree data. In this paper, we study of Cross-Model Conjunctive Queries (CMCQs) over relation and tree-structured data (XML and JSON). To efficiently process CMCQs with bounded intermediate results, we first encode tree nodes with position information. With tree node original label values and encoded position values, it allows our proposed algorithm CMJoin to join relations and tree data simultaneously, avoiding massive intermediate results. CMJoin achieves worst-case optimality in terms of the total result of label values and encoded position values. Experimental results demonstrate the efficiency and scalability of the proposed techniques to answer a CMCQ in terms of running time and intermediate result size.
