投入驱动的存储与计算一体化的事务处理效率优化方法

An investment defined transaction processing optimization approach with collaborative storage and computation adaptation

事务处理技术是报告信息一致性和可靠性的关键技术,决定了Web服务是否可以应用于电子商务。类型化的数据、信息和知识等资源繁杂冗余,导致资源存储和处理效率低下,长事务的处理过程往往会持续较长时间,使得锁定资源的策略不能一直适用,为了协调事务型资源存储和计算代价,提出了一种投入驱动的事务处理方法。从资源建模、资源处理、处理优化和资源管理等角度进行研究,基于对现有知识图谱概念的拓展提出了一种三层可自动抽象调整的解决架构。这个架构包括:数据图谱、信息图谱和知识图谱等三个层面,关键在于对搜索目标资源对象类型转移代价和在资源存储空间上的存储代价的计算,并根据用户投入协同调整搜索目标资源对象的搜索机制和存储方案,从而降低资源搜索的时间复杂度和资源存储的空间复杂度,优化事务处理的时空效率。

Transaction processing technology is a key technology for reporting information consistency and reliability,and determines whether Web services can be applied to e-commerce.Typed resources such as data,information and knowledge are complicated and redundant,resulting in low storage and processing efficiency of resources.Processing of long transactions often lasts for a long time so that the strategy of locking resources cannot always be applied.We propose an investment defined transaction processing approach towards temporal and spatial optimization with collaborative storage and computation adaptation.In terms of resource modeling,resource processing,processing optimization and resource management,we propose a three-layer solution architecture that can be automatically abstracted and adjusted based on expanding the existing concepts of knowledge graph.The architecture includes three layers that are data graph,information graph,and knowledge graph.The key lies in the calculation of type transferring cost and storage cost on the resource storage space of search target resource objects,and the adjustment of the search mechanism and storage scheme of search target resource objects according to users＇ investment,thus reducing the temporal complexity of resource searching and spatial complexity of resource storage and optimizing the temporal and spatial efficiency.