基于增量日志的数据组合视图定位更新方法

Data Composition View Positioning Update Approach with Incremental Logs

数据服务作为一种面向跨域异构数据源的统一数据模型,能够将数据资源以服务的形式进行发布,并根据用户的数据需求,通过组合若干个数据服务生成数据组合视图。然而,由于数据源是自治的,当数据发生变化时,如何以最小的代价实时更新数据组合视图是数据服务技术需要解决的关键问题。为此,提出一种基于增量日志的数据组合视图定位更新方法,先根据数据源日志的增量变化获取最新变更数据,然后通过定位属性计算组合视图中差异元组的索引号,并根据变更类型直接对组合视图中的差异元组执行数据更新操作,最终给出了基于日志的更新数据实时获取算法和数据组合视图定位更新算法。在跨域异构电梯数据服务系统中对本更新方法进行了评价,结果表明,当变更元组数量所占比例远小于元组总数或数据组合视图的属性个数较多时,定位更新方法的更新效率比现有方法高。

Data resources stored in different units and departments in cloud environment are cross-domain,heterogeneous and complex.As a unified data model for cross-origin and heterogeneous data sources,data service can publish data sources in the form of services,and generate data composition view by composing several data services according to users’data requirements.Since the data sources are autonomous,it becomes a key issue to update data composition view in real time with minimal cost.This paper proposes a data composition view positioning update approach based on incremental logs.The latest data changes of data sources are captured according to incremental logs,and then the attributes and tuples in data composition view are indexed.The index numbers of different tuples can be calculated with positioning attributes.The corresponding tuple update operations can be performed according to data changes’type.A log-based update data acquisition algorithm and a data composition view positioning update algorithm are presented.The proposed approach has been evaluated in a cross-origin heterogeneous elevator data service system by using datasets from multiple departments.When the proportion of the number of changed tuples is much smaller than the total number of tuples,the update efficiency of positioning update approach is much higher than existing methods.When the number of attributes of the data composition view is larger,the update efficiency of the positioning update approach is much higher than existing methods.