Design And Implementation Of Cross-border Data Synchronization System

With the rapid development of enterprise informatization,due to improper design,technological development or enterprise development,the components of the various business systems of the enterprise are incompatible,and the data is isolated from each other,forming a 'information Island' situation.The purpose of enterprise informatization is to improve the production efficiency.The inability of data exchange between various systems will affect the coordination between various departments of the enterprise and reduce the production efficiency of the enterprise.Especially after the emergence of multinational businesses,because of the network environment,the performance has become more obvious,which has increased the operating costs of enterprises.Starting from the background of actual business requirements,the thesis designs and implements a cross-border data synchronization system.The purpose is to support incremental data synchronization of heterogeneous databases under high-latency networks and high concurrency.The thesis mainly discusses the design and implementation of the cross-border data synchronization system from the perspectives of project background,system requirements analysis,system function design and implementation,and system function testing,and finally puts forward the system's shortcomings and prospects.This system is mainly divided into four modules,which are basic function module,configuration management module,data synchronization module and monitoring module.The data synchronization module is the core function module of the system.By comparing the advantages and disadvantages of commonly used incremental data acquisition methods,the system chooses to subscribe to incremental data through database log analysis.In the face of high-latency and high-concurrency application scenarios,this paper designs a two-layer cache architecture and dynamic task scheduling function,using event-driven mode and asynchronous thread processing to ensure that the system can guarantee high availability in a high-concurrency environment.At the same time,the time used for data processing through the system is reduced.At present,the system has been put into operation,and the performance and availability have reached expectations.The processing capacity of a single node in highlatency scenarios can reach up to 200 TPS,and 500 TPS in low-latency scenarios.