时态拟序数据索引TQD-tree更新技术

介绍基于线序划分（LOP）的时态拟序索引技术TQD-tree，基于前期研究成果实现增量更新.能否实现增量更新是时态索引技术成败的关键.首先，讨论TQD-tree所需数据结构和LOP实现算法；其次，讨论实现增量更新算法；再次，讨论批量更新的可行性；最后，完成仿真评估以表明更新技术可行性和有效性.实现批量更新，减少扫描重构TQD-tree次数，能大大提高系统效率.研究时态数据索引更新技术能解决大数据管理框架中实时响应和频繁更新的基本需求.

Updating Technique of Temporal Quasi-Order Data Index

This paper introduces TQD-tree which is a Temporal Quasi-Order index technique based on Line Order Partition (LOP), and realize incremental update for preliminary study. Whether the incremental update can be realized or not is the key to the success of temporal index technology. First, the data structure and LOP implementation algorithm of TQD-tree are discussed; Second, the incremental update algorithm is discussed; Third, the feasibility of batch update is discussed; Finally, the simulation evaluation is completed to show the feasibility and effectiveness of the updating technology. To achieve batch update and reduce the number of scanning and reconstructing TQD-tree, the system efficiency can be greatly improved. Research on temporal data index update technology can solve the basic requirements of real-time response and frequent update in big data management framework.