hadoop-MapReduce框架之计数器应用以及数据清洗（ETL）

1.计数器应用

　　hadoop为每个作业维护若干个内置计数器，以描述多项指标；例如：某些计数器记录已处理的字节数和记录数，使用户可监控已经处理的输入数据量和已产生的输出数据量；

　　1.1 计数器API

　　　　1.1.1 采用枚举的方式统计计数

　　　　　　enumMyCounter(MALFORORMED,NORMAL)

　　　　1.1.2 采用计数器组，计数器名称的方式统计

　　　　　　context.getCount("countGroup","counter").increment(1);

　　　　1.1.3 计数结果在程序运行后的控制台上查看；

2.数据清洗

　　在运行核心业务MapReduce程序之前，往往要先对数据进行清除，清理掉不符合用户要求的数据；清理的过程往往只需要运行mapper程序，不需要运行reduce程序；

3.数据清洗需求

　　3.1 需求

　　　　去除日志中字段长度小于等于11的日志；

　　　　（1）输入数据

　　　　（2）输出数据

　　　　　　每行字段长度大于11；

　　3.2 需求分析

　　　　需要在map阶段对输入的数据根据规则进行过滤清洗；

4.数据清洗案例--简单版

　　4.1 mapper编写

package com.wn.etl;

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

import java.io.IOException;

public class ETLMapper extends Mapper<LongWritable, Text,Text, NullWritable> {

    @Override
    protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
        String[] fields = value.toString().split(" ");
        if (fields.length>11){
            context.write(value,NullWritable.get());
            context.getCounter("ETL","True").increment(1);
        }else{
            context.getCounter("ETL","False").increment(1);
        }
    }
}

　　4.2 driver编写

package com.wn.etl;

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;

import java.io.IOException;

public class ETLDriver {
    public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
        Job job = Job.getInstance(new Configuration());
        job.setJarByClass(ETLDriver.class);
        job.setMapperClass(ETLMapper.class);
        job.setNumReduceTasks(0);

        job.setMapOutputKeyClass(Text.class);
        job.setMapOutputValueClass(NullWritable.class);

        FileInputFormat.setInputPaths(job,new Path("E:\\北大青鸟\\大数据04\\hadoop\\ETL"));
        FileOutputFormat.setOutputPath(job,new Path("E:\\北大青鸟\\大数据04\\hadoop\\outETL"));

        boolean b = job.waitForCompletion(true);
        System.exit(b ? 0 : 1);
    }
}

　　　　

5.数据清理案例--复杂版

　　5.1 bean编写

package com.wn.etl2;

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
    private String time_local;  //记录访问时间与时区
    private String request; //记录请求的url和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题内容大小
    private String http_referer;    //用来记录从哪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("\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();
    }
}

　　5.2 mapper编写

package com.wn.etl2;

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

import java.io.IOException;

public class LogMapper extends Mapper<LongWritable, Text,Text, NullWritable> {

    private LogBean logBean=new LogBean();

    private Text k=new Text();

    @Override
    protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
        String line = value.toString();
        parseLog(line);
        if (logBean.isValid()){
            k.set(logBean.toString());
            context.write(k,NullWritable.get());
            context.getCounter("ETL","True").increment(1);
        }else{
            context.getCounter("ETL","False").increment(1);
        }
    }

    private void parseLog(String line) {
        String[] fields= line.split(" ");
        if (fields.length>11){
            //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(true);
            }
        }else{
            logBean.setValid(false);
        }
    }
}

　　5.3 driver编写

package com.wn.etl2;

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;

import java.io.IOException;

public class LogDriver {
    public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
        Job job = Job.getInstance(new Configuration());
        job.setJarByClass(LogDriver.class);
        job.setMapperClass(LogMapper.class);
        job.setNumReduceTasks(0);

        job.setMapOutputKeyClass(Text.class);
        job.setMapOutputValueClass(NullWritable.class);

        FileInputFormat.setInputPaths(job,new Path("E:\\北大青鸟\\大数据04\\hadoop\\ETL"));
        FileOutputFormat.setOutputPath(job,new Path("E:\\北大青鸟\\大数据04\\hadoop\\outETL"));

        boolean b = job.waitForCompletion(true);
        System.exit(b ? 0 : 1);
    }
}