基于Spark的DOTA2 Matches数据分析_无前后端
舟率率 10/31/2025 pythonscalabottle
原地址:https://dblab.xmu.edu.cn/blog/3489/
# 项目概况
# 数据类型
DOTA2 Matches数据 (opens new window)
# 开发环境
centos7
# 软件版本
python3.8.18、hadoop3.2.0、spark3.1.2、scala2.12.18、jdk8
# 开发语言
python
# 开发流程
数据上传(linux本地)->数据计算(spark)->数据存储(linux本地)->后端(bottle)->前端(html+js+css)
# 可视化图表
# 操作步骤
# python安装包
pip3 install bottle==0.12.25 -i https://pypi.tuna.tsinghua.edu.cn/simple
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# 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
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# 上传文件夹
mkdir -p /data/jobs/project/
cd /data/jobs/project/
# 解压 "data" 目录下的 "data.7z" 压缩包到当前目录
# 上传 "project-spark-dota-data-analysis" 整个文件夹
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# 上传文件到hdfs
cd /data/jobs/project/project-spark-dota-data-analysis/data/
hdfs dfs -mkdir /data/
hdfs dfs -rm -r /data/*
hdfs dfs -put -f hero_names.csv /data/
hdfs dfs -put -f player_ratings.csv /data/
hdfs dfs -put -f test_labels.csv /data/
hdfs dfs -put -f test_player.csv /data/
hdfs dfs -ls /data/
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# spark数据分析
cd /data/jobs/project/
# 对项目 "project-spark-dota-data-analysis" 进行打包
# 打包命令: mvn clean package -Dmaven.test.skip=true
# cd /data/jobs/project/project-spark-dota-data-analysis/
# mvn clean package -Dmaven.test.skip=true
# yes | cp /data/jobs/project/project-spark-dota-data-analysis/target/project-spark-dota-data-analysis-jar-with-dependencies.jar /data/jobs/project/
# 上传 "project-spark-dota-data-analysis/target/" 目录下的 "project-spark-dota-data-analysis-jar-with-dependencies.jar" 文件 到 "/data/jobs/project/" 目录
spark-submit \
--master local[*] \
--class org.example.DOTA2 \
/data/jobs/project/project-spark-dota-data-analysis-jar-with-dependencies.jar /data/ /data/jobs/project/project-spark-dota-data-analysis/myapp/static
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# 启动可视化
cd /data/jobs/project/project-spark-dota-data-analysis/myapp/
python3 web.py
# 浏览器访问: http://master:9999/
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