Hadoop基础（二十九）：数据清洗（ETL）（二）复杂解析版

数据清洗案例实操-复杂解析版

1．需求

对Web访问日志中的各字段识别切分，去除日志中不合法的记录。根据清洗规则，输出过滤后的数据。

（1）输入数据

（2）期望输出数据

都是合法的数据

2．实现代码

（1）定义一个bean，用来记录日志数据中的各数据字段

package com.atguigu.mapreduce.log;

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("01").append(this.remote_addr);
        sb.append("01").append(this.remote_user);
        sb.append("01").append(this.time_local);
        sb.append("01").append(this.request);
        sb.append("01").append(this.status);
        sb.append("01").append(this.body_bytes_sent);
        sb.append("01").append(this.http_referer);
        sb.append("01").append(this.http_user_agent);
        
        return sb.toString();
    }
}

（2）编写LogMapper类

package com.atguigu.mapreduce.log;
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 = parseLog(line);
        
        if (!bean.isValid()) {
            return;
        }
        
        k.set(bean.toString());
        
        // 3 输出
        context.write(k, NullWritable.get());
    }

    // 解析日志
    private LogBean parseLog(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

package com.atguigu.mapreduce.log;
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 {
        
// 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);
    }
}