Research And Application Of Distributed Processing Architecture In Commercial Bank's Operational Data Store System

Under the development of economic globalization, the opening and competition has become the mainstream of financial development in twenty-first century, and the competition between international banks tends to be fiercer. If commercial banks want to succeed in this process and keep developing, they need speed up their financial and technological innovations to improve the core competition. As the development of financial information, the information system of commercial banks becomes more centralized, and the requirement of data interchange between system and system becomes more and more frequent. They not only require high quality but also require high efficiency. The commercial bank operational data store system is built for this goal.Massive data highly effective processing is the challenge to the commercial bank Operational Data Storage System.The traditional-style architeture which processing depends on mainframe is low scalability and flexibility but high costs. This Architecture brought about serious constraints on the supporting to the commercial bank Operational Data Storage Systems to the growing business.By analyzing, this thesis proposed that build commercial bank operational data storage system through the cluster-distributed architecture to address these issues. First, the principles of grid computing is the theoretical support. Second, from the structure of the deployment of hardware and software design descript the feasibility of the Architeture and the implementation methods. By contrasting the application of the system, We ultimate proofed that the distributed processing architecture is advanced. And we explore an effective method for the commercial bank information system in massive data processing.