【mapreudce】6.对Nginx的access日志进行数据清洗，我们提取出文件数据的ip，时间，url

1.首先我们需要一个util辅助类

package cn.cutter.demo.hadoop.mapreduce.nginxlog.util;

import java.text.ParseException;
import java.text.SimpleDateFormat;
import java.util.Date;
import java.util.Locale;

/**
 * @ClassName AccessLogUtil
 * @Description 
 * @Author xiaof
 * @Date 2019/5/15 22:07
 * @Version 1.0
 **/
public class AccessLogUtil {

    public static final SimpleDateFormat FORMAT = new SimpleDateFormat(
            "d/MMM/yyyy:HH:mm:ss", Locale.ENGLISH);
    public static final SimpleDateFormat dateformat1 = new SimpleDateFormat(
            "yyyyMMddHHmmss");/**
     * 解析英文时间字符串
     *
     * @param string
     * @return
     * @throws ParseException
     */
    private static Date parseDateFormat(String string) {
        Date parse = null;
        try {
            parse = FORMAT.parse(string);
        } catch (ParseException e) {
            e.printStackTrace();
        }
        return parse;
    }

    /**
     * 解析日志的行记录
     *
     * @param line
     * @return 数组含有5个元素，分别是ip、时间、url、状态、流量,请求来源
     */
    public static String[] parse(String line) {
        String ip = parseIP(line);
        String time = parseTime(line);
        String url = parseURL(line);
        String status = parseStatus(line);
        String traffic = parseTraffic(line);
        String sourcePath = parseSource(line);

        return new String[] { ip, time, url, status, traffic, sourcePath };
    }

    private static String parseTraffic(String line) {

//        final String trim = line.substring(line.lastIndexOf("-") + 1)
//                .trim();

        int start = line.indexOf(""");
        int second = line.indexOf(""", start + 1);
        int three = line.indexOf(""", second + 1);
        final String trim = line.substring(second + 1, three)
                .trim();

        String traffic = trim.split(" ")[1];
        return traffic;
    }

    private static String parseStatus(String line) {
        int start = line.indexOf(""");
        int second = line.indexOf(""", start + 1);
        int three = line.indexOf(""", second + 1);
        final String trim = line.substring(second + 1, three)
                .trim();
        String status = trim.split(" ")[0];
        return status;
    }

    private static String parseURL(String line) {
        final int first = line.indexOf(""");
        final int second = line.indexOf(""", first + 1);
        final int last = line.lastIndexOf(""");
        String url = line.substring(first + 1, second);
        return url;
    }

    private static String parseTime(String line) {
        final int first = line.indexOf("[");
        final int last = line.indexOf("+0800]");
        String time = line.substring(first + 1, last).trim();
        Date date = parseDateFormat(time);
        return dateformat1.format(date);
    }

    private static String parseIP(String line) {
        String ip = line.substring(0, line.indexOf("-")).trim();
        return ip;
    }

    private static String parseSource(String line) {
        final int end = line.lastIndexOf(""");
        final int start = line.lastIndexOf(""", end - 1);

        String sourcePath = line.substring(start + 1, end).trim();

        return sourcePath;
    }


    public static void main(String args[]) {

        String s1 = "10.25.24.133 - admin [07/Mar/2019:14:19:53 +0800] "GET /oss-eureka-server/console HTTP/1.1" 200 21348 "http://218.200.65.200:9425/oss-web/main.jsp" "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/70.0.3538.77 Safari/537.36"
";

        String result[] = AccessLogUtil.parse(s1);

        for(int i = 0; i < result.length; ++i) {
            System.out.println(result[i]);
        }

    }
}

2.map类

package cn.cutter.demo.hadoop.mapreduce.nginxlog.map;

import cn.cutter.demo.hadoop.mapreduce.nginxlog.util.AccessLogUtil;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;

import java.io.IOException;

/**
 * @ProjectName: cutter-point
 * @Package: cn.cutter.demo.hadoop.mapreduce.nginxlog.map
 * @ClassName: NginxAccessLogMap
 * @Author: xiaof
 * @Description: ${description}
 * @Date: 2019/5/17 11:12
 * @Version: 1.0
 */
public class NginxAccessLogCleanMap extends Mapper<LongWritable, Text, LongWritable, Text> {

    Text outputValue = new Text();

    @Override
    protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {

        //解析没行数据，获取不同的数据
        String data[] = AccessLogUtil.parse(value.toString());
        //组装前三个数据信息，输出到combine
        outputValue.set(data[0] + "	" + data[1] + "	" + data[2]);
        context.write(key, outputValue);
    }
}

3.reduce类

package cn.cutter.demo.hadoop.mapreduce.nginxlog.reduce;

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

import java.io.IOException;

/**
 * @ProjectName: cutter-point
 * @Package: cn.cutter.demo.hadoop.mapreduce.nginxlog.reduce
 * @ClassName: NginxAccessLogReduce
 * @Author: xiaof
 * @Description: 进行数据清洗
 * @Date: 2019/5/17 11:21
 * @Version: 1.0
 */
public class NginxAccessLogCleanReduce extends Reducer<LongWritable, Text, Text, NullWritable> {

    @Override
    protected void reduce(LongWritable key, Iterable<Text> values, Context context) throws IOException, InterruptedException {
        //循环所有遍历到的数据并输出
        for(Text v : values) {
            context.write(v, NullWritable.get());
        }
    }
}

4.启动类

package cn.cutter.demo.hadoop.mapreduce.nginxlog;

import cn.cutter.demo.hadoop.mapreduce.nginxlog.map.NginxAccessLogCleanMap;
import cn.cutter.demo.hadoop.mapreduce.nginxlog.reduce.NginxAccessLogCleanReduce;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.LongWritable;
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 org.apache.hadoop.util.GenericOptionsParser;

import java.io.IOException;
import java.net.URI;
import java.net.URISyntaxException;

/**
 * @ProjectName: cutter-point
 * @Package: cn.cutter.demo.hadoop.mapreduce.nginxlog
 * @ClassName: NginxAccessLogClean
 * @Author: xiaof
 * @Description: hadoop jar ./cutter-point-service1.jar NginxAccessLogClean /user/xiaof/nginx /user/xiaof/nginx/output
 * @Date: 2019/5/17 11:25
 * @Version: 1.0
 */
public class NginxAccessLogClean {

    public static void main(String args[]) throws IOException, URISyntaxException, ClassNotFoundException, InterruptedException {

        System.out.println("进入NginxAccessLogClean方法");
        Configuration conf = new Configuration();
//        conf.set("mapreduce.job.jar", "cutter-point-service1.jar"); //其中mr01.jar是你的导出的jar文件名。
        conf.set("fs.default.name", "hdfs://jyh-zhzw-inline-27:9000");
        conf.set("dfs.client.use.datanode.hostname", "true");
        GenericOptionsParser optionsParser = new GenericOptionsParser(conf, args);
        String[] remainingArgs = optionsParser.getRemainingArgs();

        //输出参数
        for(int i = 0; i < remainingArgs.length; ++i) {
            System.out.println(remainingArgs[i]);
        }

        Job job = Job.getInstance(conf, NginxAccessLogClean.class.getName());
        job.setJarByClass(NginxAccessLogClean.class);
        job.setMapperClass(NginxAccessLogCleanMap.class);
        job.setMapOutputKeyClass(LongWritable.class);
        job.setMapOutputValueClass(Text.class);
        job.setReducerClass(NginxAccessLogCleanReduce.class);
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(NullWritable.class);

        // 清理已存在的输出文件
        FileInputFormat.setInputPaths(job, remainingArgs[0]);
        FileOutputFormat.setOutputPath(job, new Path(remainingArgs[1]));
        FileSystem fs = FileSystem.get(new URI(remainingArgs[0]), conf);
        Path outPath = new Path(remainingArgs[1]);
        if (fs.exists(outPath)) {
            fs.delete(outPath, true);
        }

        boolean success = job.waitForCompletion(true);
        if(success){
            System.out.println("Clean process success!");
        }
        else{
            System.out.println("Clean process failed!");
        }
    }

}

数据源：

我们文件原始数据格式展示

 我们清洗之后数据展示

 展示数据