Performance Optimizations of Monolithic Architecture in High-frequency Data Access System
With its unique way of deploying data and programs locally,the monolithic architecture achieves efficiency and stability that other architectures cannot match.Therefore,it still has a place in the cloud era and is quite suitable for high-frequency data access scenarios facing massive data.However,there are also a series of problems such as the resource capacity of a single machine being difficult to cope with data growth,performance jitters due to high resource consumption such as data loading when starting a service,and a sudden increase in transaction time due to cold data after service or data updates.In this paper,optimization solutions are proposed to ef-fectively alleviate these problems.These solutions include reducing the memory capacity requirements of a single machine by using memory mapping with specified address and shared memory technology,decoupling data and applications through the introduction of an intermediate control layer,minimizing resource loading costs through copy-on-write technology,and accelerating memory access efficiency through hardware memory management units and page table heating.In practical validation,the monolithic architecture not only supports higher data capacity but also maintains stable transaction response times while ensuring rapid data loading.Furthermore,it still retains the performance advantages of the monolithic architecture.This improved design expands the applicability of the monolithic architecture,providing a universal optional solution for real-time transaction systems with massive data and high-frequency data access requirements.
monolithic architecturememory mappingshared memoryhigh-frequency data accesscopy-on-write
万方数据
维普
