偏序时态XML索引TempPartialIndex

时态数据管理是常规数据管理的深化和扩展，具有理论研究的意义与实践应用的价值.时态数据索引是时态数据管理的重要技术支撑，是其中的一个研究热点.首先，提出了一种时态数据结构，通过数据节点间的偏序关系，可将常规的二维时间区间的处理转化为基于偏序的时态等价类上的一维的处理，该数据结构可以快速有效地处理时态操作；其次，在该新型时态数据结构基础上研究了时态XML索引TempPartialIndex，其基本特征是将时态数据结构整合到非时态的XML索引中，即，将其整合到语义层之中，通过时态过滤和语义过滤掉大量节点之后，再进行结构连接；另外，着重讨论了基于TempPartialIndex“一次一集合”及其时态变量查询和增量式的动态更新机制.同时，仿真结果表明：TempPartialIndex能够有效地支持时态XML的各类查询及更新操作，技术上具有可行性和有效性.

Temporal XML Index Based on Temporal Partial-Order Relationship

Temporal data management is an extended field of data management, and the research on this field has theoretical significance and practical application value. The index of temporal data is crucial to temporal data management and thus is one of the hot research topics. First, based on the partial-order mathematical relationship, this paper proposes a data structure which can convert a temporal query processing of two-dimension into one-dimension. This structure can process all the temporal relationship operations efficiently. Secondly, this paper presents an indexing scheme called TempPartialIndex which combines temporal partial-order data structure into non-temporal XML index. In TempPartialIndex schema, the processing of query begins with mapping and filtering with the semantic and temporal constraints so that a large number of nodes will be filtered out and only a few nodes will be left. Then a structural join algorithm is executed on the left nodes. Furthermore, the paper discusses the query based on set-at-a-time, the temporal variable query and modification. Simulations show that TempPartialIndex can process the temporal XML query and update efficiently.