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数据类型
超市商品销售数据
开发环境
centos7
软件版本
python3.8.18、hadoop3.2.0、spark3.1.2、mysql5.7.38、scala2.12.18、jdk8
开发语言
python、Scala
开发流程
数据上传(hdfs)->数据清洗(spark)->数据分析(spark)->数据存储(mysql)->后端(flask)->前端(html+js+css)
可视化图表
2025-05-13_221901.png
2025-05-13_221908.png
2025-05-13_230822.png
2025-05-13_230828.png
2025-05-13_230836.png
2025-05-13_230843.png
2025-05-13_230849.png
2025-05-13_230855.png
2025-05-13_230901.png
2025-05-13_230908.png
2025-05-13_230915.png
操作步骤
python安装包
pip3 install pandas==2.0.3 -i https://mirrors.aliyun.com/pypi/simple/
pip3 install flask==3.0.0 -i https://mirrors.aliyun.com/pypi/simple/
pip3 install flask-cors==4.0.1 -i https://mirrors.aliyun.com/pypi/simple/
pip3 install pymysql==1.1.0 -i https://mirrors.aliyun.com/pypi/simple/
启动MySQL
# 查看mysql是否启动 启动命令: systemctl start mysqld.service
systemctl status mysqld.service
# 进入mysql终端
# MySQL的用户名:root 密码:123456
# MySQL的用户名:root 密码:123456
# MySQL的用户名:root 密码:123456
mysql -uroot -p123456
启动Hadoop
# 离开安全模式: hdfs dfsadmin -safemode leave
# 启动hadoop
bash /export/software/hadoop-3.2.0/sbin/start-hadoop.sh
准备目录
mkdir -p /data/jobs/project/
cd /data/jobs/project/
# 上传 "project-spark-market-data-analysis" 整个文件夹
上传文件到hdfs
cd /data/jobs/project/project-spark-market-data-analysis/
hdfs dfs -mkdir -p /data/input/
hdfs dfs -rm -r /data/input/*
hdfs dfs -put -f data/market_sale_order.csv /data/input/
hdfs dfs -put -f data/market_sale_persons.csv /data/input/
hdfs dfs -put -f data/market_sale_return.csv /data/input/
hdfs dfs -ls /data/input/
程序打包
cd /data/jobs/project/project-spark-market-data-analysis/
mvn clean package -Dmaven.test.skip=true
cp target/project-spark-market-data-analysis-jar-with-dependencies.jar /data/jobs/project/
创建MySQL表
cd /data/jobs/project/project-spark-market-data-analysis/
# 请确认mysql服务已经启动了
# 快速执行.sql文件内的sql语句
mysql -u root -p < mysql/mysql.sql
spark数据清洗
cd /data/jobs/project/
spark-submit \
--master local[*] \
--class org.example.demo.SparkClean \
/data/jobs/project/project-spark-market-data-analysis-jar-with-dependencies.jar /data/input/market_sale_order.csv /data/input/market_sale_return.csv /data/input/market_sale_persons.csv /data/output/
spark数据分析
cd /data/jobs/project/
spark-submit \
--master local[*] \
--class org.example.demo.SparkAnalysis \
/data/jobs/project/project-spark-market-data-analysis-jar-with-dependencies.jar /data/output/
启动可视化
yes | cp -r /data/jobs/project/project-spark-market-data-analysis/可视化 /data/jobs/project/myapp
cd /data/jobs/project/myapp/
# windows本地运行: python3 app.py
python3 app.py pro
