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摘要

随着医药行业的快速发展，数据量呈爆发式增长，如何高效分析医药销售数据以辅助决策成为关键。本文设计并实现了一套基于 Spark 的医药销售数据分析系统。采用 Python 语言进行开发，借助 Hadoop 分布式存储与计算框架的强大能力，实现对海量医药销售数据的高效存储与并行处理。前端采用 Django 框架构建用户交互界面，为管理员提供直观便捷的操作体验，涵盖系统首页、个人中心、医药销售及预测信息等功能模块。后端则依托 MySQL 数据库存储用户信息、医药销售数据及预测信息等各类数据，确保数据的安全性与完整性。管理员可通过系统查询、添加、删除医药销售数据，还能基于药品名称、规格、类型及销售地区等多维度信息进行销售数量预测，系统以可视化图表形式展示医药销售总数、详情、各类统计信息及预测结果，为医药销售决策提供有力支持，有效提升医药销售管理效率与精准度。

关键词：医药；Spark；销售；

Abstract

With the rapid development of the pharmaceutical industry, the volume of data has grown explosively. How to efficiently analyze pharmaceutical sales data to assist in decision-making has become the key. This paper designs and implements a set of pharmaceutical sales data analysis system based on Spark. The development is carried out using the Python language and with the help of the powerful capabilities of the Hadoop distributed storage and computing framework, efficient storage and parallel processing of massive pharmaceutical sales data are achieved. The front end adopts the Django framework to build the user interaction interface, providing administrators with an intuitive and convenient operation experience, covering functional modules such as the system home page, personal center, medical sales and forecast information. The back end relies on the MySQL database to store various types of data such as user information, pharmaceutical sales data and forecast information, ensuring the security and integrity of the data. Administrators can query, add and delete medical sales data through the system. They can also predict sales quantities based on multi-dimensional information such as drug names, specifications, types and sales regions. The system presents the total number of medical sales, details, various statistical information and prediction results in the form of visual charts, providing strong support for medical sales decisions. Effectively enhance the efficiency and accuracy of pharmaceutical sales management.

Key words:Medicine Spark; Sales