摘 要
基于 Hadoop 的超市进货推荐系统是一个旨在优化超市商品库存管理和采购
流程的数据分析平台。该系统利用 Hadoop 的强大数据处理能力，通过大数据分
析和机器学习算法，对超市的销售数据、顾客行为以及市场趋势进行深入分析。
系统能够为超市管理者提供智能的商品进货建议，预测不同商品的需求量，从而
帮助超市减少库存积压和缺货情况。系统还包括一个直观的用户界面，供管理员
和前台用户使用。管理员可以通过用户管理、商品管理等功能高效地维护超市运
营，而前台用户可以浏览商品、参与论坛讨论并接收个性化推荐。整个系统的实
现旨在提高超市运营效率，增强顾客满意度，并通过数据驱动的决策支持，提升
超市的市场竞争力。
根据本系统的基本设计思路，本系统在设计方面前台采用了 java 技术等进
行基本的页面设计，后台数据库采用 MySQL。本系统的实现为超市进货推荐系统
的运行打下了基础，为超市进货推荐提供良好的条件。
最后我们通过需求分析、测试调整，与超市进货的实际需求相结合，设计实
现了基于 Hadoop 的超市进货推荐系统。
关键词：超市；Hadoop；MySQL 数据库
Abstract
The supermarket purchase recommendation system based on Hadoop is a data
analysis platform designed to optimize the supermarket inventory management and
procurement process. The system utilizes the powerful data processing power of
Hadoop to conduct in-depth analysis of supermarket sales data, customer behavior
and market trends through big data analysis and machine learning algorithms. The
system can provide intelligent suggestions for supermarket managers to purchase
goods and predict the demand for different goods, thus helping supermarkets to
reduce inventory overstock and out of stock. The system also includes an intuitive
user interface for administrators and front office users. Administrators can efficiently
maintain supermarket operations through user management, product management and
other functions, while front desk users can browse products, participate in forum
discussions and receive personalized recommendations. The implementation of the
entire system aims to improve the supermarket's operational efficiency, enhance
customer satisfaction, and enhance the supermarket's market competitiveness through
data-driven decision support.
According to the basic design ideas of the system, the system uses java
technology for basic page design in the front end of the design, and MySQL is used in
the background database. The realization of this system lays a foundation for the
operation of the supermarket purchase recommendation system, and provides good
conditions for the supermarket purchase recommendation.
