扩展Allen关系谓词的基于扫描的高速缓存高效区间连接（扩展版）
Cache-Efficient Sweeping-Based Interval Joins for Extended Allen Relation Predicates (Extended Version)
摘要：
我们开发了一个家庭的高效平面扫描间隔连接算法，可以评估范围广泛的间隔谓词，如艾伦的关系和参数化的关系。我们的技术是基于一个框架，其组件可以灵活地结合在不同的方式来支持所需的间隔关系。在时态数据库中，我们的算法可以利用一个众所周知的和灵活的访问方法，时间轴索引，从而进一步扩展了它支持的操作集。此外，采用紧凑的数据结构，无间隙哈希映射，我们有效地利用CPU缓存。在实验评估中，我们表明，我们的方法比最先进的技术快几倍，规模更好，同时更适合实时事件处理。
英文摘要：
We develop a family of efficient plane-sweeping interval join algorithms that can evaluate a wide range of interval predicates such as Allen's relationships and parameterized relationships. Our technique is based on a framework, components of which can be flexibly combined in different manners to support the required interval relation. In temporal databases, our algorithms can exploit a well-known and flexible access method, the Timeline Index, thus expanding the set of operations it supports even further. Additionally, employing a compact data structure, the gapless hash map, we utilize the CPU cache efficiently. In an experimental evaluation, we show that our approach is several times faster and scales better than state-of-the-art techniques, while being much better suited for real-time event processing.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
