Freemaker在大规模数据处理中的应用与性能优化  

Freemaker’s Application and Performance Optimization in Large-Scale Data Processing

作　　者：马中海 MA Zhonghai(Xi’an Huawei Cloud Computing Technology Co.,Ltd.,Xi’an Shaanxi 710100,China)

机构地区：[1]西安华为云计算技术有限公司,陕西西安710100

出　　处：《信息与电脑》2025年第2期176-178,共3页Information & Computer

摘　　要：Freemarker是一种轻量级模板引擎,广泛应用于电商平台和金融系统中的大规模数据处理。文章分析了Freemarker的技术架构,重点探讨了其模板设计、缓存机制与并行处理的优化策略。通过模板简化、缓存优化和分布式并行处理,系统在高并发数据处理中表现出显著性能提升。以电商平台订单处理为案例,优化后每秒订单处理量提升5倍,平均渲染时间缩短80%,内存占用减少50%,CPU使用率和系统负载显著降低,系统在高并发场景下运行稳定。文章的优化策略为Freemarker在大规模数据处理中的应用提供了技术支持,并为类似场景提供了借鉴。Freemarker is a lightweight template engine,which is widely used in large-scale data processing in e-commerce platforms and financial systems.The paper analyzes the technical architecture of Freemarker,focusing on its template design,caching mechanism and optimization strategy for parallel processing.Through template simplification,cache optimization,and distributed parallel processing,the system shows significant performance improvement in high-concurrency data processing.Taking e-commerce platform order processing as an example,the order processing per second is increased by 5 times,the average rendering time is shortened by 80%,the memory usage is reduced by 50%,the CPU usage and system load are significantly reduced,and the system runs stably in high-concurrency scenarios.The optimization strategy in the paper provides technical support for the application of Freemarker in large-scale data processing,and provides a reference for similar scenarios.

关 键 词：Freemaker 数据处理 性能优化 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]