onion23的博客

1. Spark-SQL 基本操作需求将下列JSON格式数据复制到Linux系统中，并保存命名为employee.json{ "id":1 , "name":"Ella" , "age":36 }{ "id":2, "name":"Bob","age":29 }{ "id":3 , "name":"Jack","age":29 }{ "id":4 , "name":"Jim","age·":28 }{ "id":4 , "name":"Jim","age":28 }{ "i

1. 在本地路径下创建文本文件 /test/words.txt，内容如下：python java cpp c hello world hadoop hdfspython java cpp c hello world hadoop hdfspython java cpp c hello world hadoop hdfspython java cpp c hello world hadoop hdfspython java cpp c hello world hadoop hdfspy

安装环境：Linux CentOS7https://blog.youkuaiyun.com/qq_43598179/article/details/106070236

表数据表1 students_data.txt21434,Sara,F,21,20,73,classC41443,Mary,M,19,30,90,classA43333,Dery,F,20,40,85,classB45454,Mary,F,22,10,91,classA14634,Henry,M,18,50,56,classC12656,Shary,M,19,60,93,classA27676,Heary,M,21,30,81,classB96785,Jeliy,M,23,40,88

参考视频：【狂野大数据】一天搞定大数据之MapReduce目录1. MapReduce 运行流程2. 规划自定义的 MapReduce 程序3. 代码实现1. MapReduce 运行流程MapReduce主要经过三个阶段：① Map阶段1）以<k1, v1>格式读取文本文件，其中k1为文本偏移量，通常定义为数字类型（如LongWritable），v2为文本，通常定义为Text类型2）自定义语句，用于处理<k1, v1>及生成<k2, v.