MapReduce案例二：日志清洗复杂版

目录

• 一、数据样式
• 二、需求
• 三、分析
• 四、代码实现

一、数据样式

  网站日志的数据样例：
  

  文件下载

二、需求

• 1、对web访问日志中的各字段识别切分。
• 2、去除日志中不合法的记录，
• 3、根据统计需求，生成各类访问请求过滤数据。

三、分析

  网站日志数据类型，每一行中的每个字段用空格隔开，且每一行的字段数量并非一致。去除不合理字段数量的行。
  大于状态码大于400，HTTP错误。

四、代码实现

• 1、定义一个bean类，用来记录日志数据中的各数据字段。

public class LogBean {
    private String remote_addr;// 记录客户端的ip地址
    private String remote_user;// 记录客户端用户名称,忽略属性"-"
    private String time_local;// 记录访问时间与时区
    private String request;// 记录请求的url与http协议
    private String status;// 记录请求状态；成功是200
    private String body_bytes_sent;// 记录发送给客户端文件主体内容大小
    private String http_referer;// 用来记录从那个页面链接访问过来的
    private String http_user_agent;// 记录客户浏览器的相关信息

    private boolean valid = true;// 判断数据是否合法

    public String getRemote_addr() {
        return remote_addr;
    }

    public void setRemote_addr(String remote_addr) {
        this.remote_addr = remote_addr;
    }

    public String getRemote_user() {
        return remote_user;
    }

    public void setRemote_user(String remote_user) {
        this.remote_user = remote_user;
    }

    public String getTime_local() {
        return time_local;
    }

    public void setTime_local(String time_local) {
        this.time_local = time_local;
    }

    public String getRequest() {
        return request;
    }

    public void setRequest(String request) {
        this.request = request;
    }

    public String getStatus() {
        return status;
    }

    public void setStatus(String status) {
        this.status = status;
    }

    public String getBody_bytes_sent() {
        return body_bytes_sent;
    }

    public void setBody_bytes_sent(String body_bytes_sent) {
        this.body_bytes_sent = body_bytes_sent;
    }

    public String getHttp_referer() {
        return http_referer;
    }

    public void setHttp_referer(String http_referer) {
        this.http_referer = http_referer;
    }

    public String getHttp_user_agent() {
        return http_user_agent;
    }

    public void setHttp_user_agent(String http_user_agent) {
        this.http_user_agent = http_user_agent;
    }

    public boolean isValid() {
        return valid;
    }

    public void setValid(boolean valid) {
        this.valid = valid;
    }

    @Override
    public String toString() {
        StringBuilder sb = new StringBuilder();
        sb.append(this.valid);
        sb.append("\001").append(this.remote_addr);
        sb.append("\001").append(this.remote_user);
        sb.append("\001").append(this.time_local);
        sb.append("\001").append(this.request);
        sb.append("\001").append(this.status);
        sb.append("\001").append(this.body_bytes_sent);
        sb.append("\001").append(this.http_referer);
        sb.append("\001").append(this.http_user_agent);
        
        return sb.toString();
    }
}

• 2、编写LogMapper类。

import java.io.IOException;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;

public class LogMapper extends Mapper<LongWritable, Text, Text, NullWritable>{
    Text k = new Text();
    
    @Override
    protected void map(LongWritable key, Text value, Context context)
            throws IOException, InterruptedException {
        // 1 获取1行
        String line = value.toString();        
        // 2 解析日志是否合法
        LogBean bean = pressLog(line);        
        if (!bean.isValid()) {
            return;
        }        
        k.set(bean.toString());        
        // 3 输出
        context.write(k, NullWritable.get());
    }

    // 解析日志
    private LogBean pressLog(String line) {
        LogBean logBean = new LogBean();
        // 1 截取
        String[] fields = line.split(" ");   
        if (fields.length > 11) {
            // 2封装数据
            logBean.setRemote_addr(fields[0]);
            logBean.setRemote_user(fields[1]);
            logBean.setTime_local(fields[3].substring(1));
            logBean.setRequest(fields[6]);
            logBean.setStatus(fields[8]);
            logBean.setBody_bytes_sent(fields[9]);
            logBean.setHttp_referer(fields[10]);
            
            if (fields.length > 12) {
                logBean.setHttp_user_agent(fields[11] + " "+ fields[12]);
            }else {
                logBean.setHttp_user_agent(fields[11]);
            }           
            // 大于400，HTTP错误
            if (Integer.parseInt(logBean.getStatus()) >= 400) {
                logBean.setValid(false);
            }
        }else {
            logBean.setValid(false);
        }
        return logBean;
    }
}

• 3、编写LogDriver类。

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;

public class LogDriver {
    public static void main(String[] args) throws Exception {

        args = new String[]{"D:\\大数据API\\web.txt","D:\\大数据API\\data2"};

        // 1 获取job信息
        Configuration conf = new Configuration();
        Job job = Job.getInstance(conf);
        // 2 加载jar包
        job.setJarByClass(LogDriver.class);
        // 3 关联map
        job.setMapperClass(LogMapper.class);
        // 4 设置最终输出类型
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(NullWritable.class);
        // 5 设置输入和输出路径
        FileInputFormat.setInputPaths(job, new Path(args[0]));
        FileOutputFormat.setOutputPath(job, new Path(args[1]));
        // 6 提交
        job.waitForCompletion(true);
    }
}