Hadoop大数据案例之搜狗五百万数据分析

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最近使用了hadoop中的hive、mapreduce以及HBASE对网上的一个搜狗五百万的数进行了一个比较实际的数据分析，适合新手去练习，好处是在接触较大的数据流的时候能碰到平时接触不到的问题，通过这些问题能够对自己有一个较好的提升，为以后接触到实际的大数据项目打一些有效的基础。

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数据源：https://download.csdn.net/download/leoe_/10429414
数据说明：搜狗五百万数据，是经过处理后的搜狗搜索引擎生产数据，具有真实性，大数据性，能够较好的满足分布式计算应用开发课程设计的数据要求。
搜狗数据的格式： 访问时间\t用户ID\t[查询词]\t该URL在返回结果中的排名\t用户点击的顺序号\t用户点击的URL。
其中，用户ID是根据用户使浏览器访问搜索引擎时的Cookie信息自动赋值，即同一次使用浏览器输入的不同查询对应一个用户ID。

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操作要求：

1.将原始数据加载到HDFS平台。
2.将原始数据中的时间字段拆分并拼接，添加年、月、日、小时字段。
3.将处理后的数据加载到HDFS平台。
4.以下操作分别通过MR和Hive实现。

• 查询总条数
• 非空查询条数
• 无重复总条数
• 独立UID总数
• 查询频度排名（频度最高的前50词）
• 查询次数大于2次的用户总数
• 查询次数大于2次的用户占比
• Rank在10以内的点击次数占比
• 直接输入URL查询的比例
• 查询搜索过”仙剑奇侠传“的uid，并且次数大于3

5.将4每步骤生成的结果保存到HDFS中。
6.将5生成的文件通过Java API方式导入到HBase（一张表）。
7.通过HBase shell命令查询6导出的结果。

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源数据处理

1.将原始数据加载到HDFS平台。

hadoop fs -put sogou.500w.utf8 /sogou/data

2.将原始数据中的时间字段拆分并拼接，添加年、月、日、小时字段。

bash sogou-log-extend.sh sogou.500w.utf8 sogou.500w.utf8.ext

其中sogou-log-extend.sh文件的内#!/bin/bash

#infile=/root/file/sogou.500w.utf8
infile=$1
#outfile=/root/filesogou.500w.utf8.final
outfile=$2
awk -F '\t' '{print $0"\t"substr($1,0,5)"year\t"substr($1,5,2)"month\t"substr($1,7,2)"day\t"substr($1,8,2)"hour"}' $infile > $outfile

3.处理后的数据加载到HDFS平台。

hadoop fs -put sogou.500w.utf8.ext /sogou/data

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Hive分析数据

首先要先将数据导入到hive仓库中：

1. 查看数据库：show databases
2. 创建数据库: create database sogou
3. 使用数据库: use sogou
4. 创建sougou表：Create table sougou(time string,uuid string,name string,num1 int,num2 int,url string) Row format delimited fields terminated by '\t';
5. 加载数据到表里：Load data local inpath 'sogou.500w.utf8' into table sougou;
6. 查看表信息：desc sogou;
   

---

• 查询总条数
  
  • HQL：select count(*) from sougou
• 非空查询条数
  
  • HQL：select count(*) from sougou where name is not null and name !='';
• 无重复总条数
  
  • HQL：select count(*) from (select * from sougou group by time,num1,num2,uuid,name,url having count(*)=1) a;
• 独立UID总数
  
  • HQL：select count(distinct uuid) from sougou;
• 查询频度排名（频度最高的前50词）
  
  • HQL：select name,count(*) as pd from sougou group by name order by pd desc limit 50;
• 查询次数大于2次的用户总数
  
  • HQL：select count(a.uuid) from (select uuid,count(*) as cnt from sougou group by uuid having cnt > 2) a;
• Rank在10以内的点击次数占比
  
  • HQL：select count(*) from sougou where num1<11;
• 直接输入URL查询的比例
  
  • HQL：select count(*) from sougou where url like "http://v.ku6.com/show/ZZoLCC-NMTue3NQE.html";
• 查询搜索过”仙剑奇侠传“的uid，并且次数大于3
  
  • HQL：select uuid,count(*) as uu from sougou where name='仙剑奇侠传' group by uuid having uu>3;

---

MapReduce分析数据

(1)查询总条数

package com.hadoop;

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

import java.io.IOException;

public class MRCountAll {
    public static Integer i = 0;
    public static boolean flag = true;

    public static class CountAllMap extends Mapper<Object, Text, Text, Text> {

        @Override
        protected void map(Object key, Text value, Mapper<Object, Text, Text, Text>.Context context)
                throws IOException, InterruptedException {
            i++;
        }

    }

    public static void  runcount(String Inputpath, String Outpath) {
        Configuration conf = new Configuration();
        conf.set("fs.defaultFS", "hdfs://192.168.136.100:9000");
        Job job = null;
        try {
            job = Job.getInstance(conf, "count");
        } catch (IOException e) {
            // TODO Auto-generated catch block
            e.printStackTrace();
        }
        job.setJarByClass(MRCountAll.class);
        job.setMapperClass(CountAllMap.class);
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(Text.class);

        try {
            FileInputFormat.addInputPath(job, new Path(Inputpath));
        } catch (IllegalArgumentException e) {
            // TODO Auto-generated catch block
            e.printStackTrace();
        } catch (IOException e) {
            // TODO Auto-generated catch block
            e.printStackTrace();
        }
        FileOutputFormat.setOutputPath(job, new Path(Outpath));

        try {
            job.waitForCompletion(true);
        } catch (ClassNotFoundException e) {
            // TODO Auto-generated catch block
            e.printStackTrace();
        } catch (IOException e) {
            // TODO Auto-generated catch block
            e.printStackTrace();
        } catch (InterruptedException e) {
            // TODO Auto-generated catch block
            e.printStackTrace();
        }
    }

    public static void main(String[] args) throws Exception {
        runcount("/sogou/data/sogou.500w.utf8", "/sogou/data/CountAll");
        System.out.println("总条数:  " + i);
    }

}

(2)非空查询条数

package com.hadoop;

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

import java.io.IOException;

public class CountNotNull {
    public static String Str = "";
    public static int i = 0;
    public static boolean flag = true;

    public static class wyMap extends Mapper<Object, Text, Text, IntWritable> {
        @Override
        protected void map(Object key, Text value, Mapper<Object, Text, Text, IntWritable>.Context context)
                throws IOException, InterruptedException {
            String[] values = value.toString().split("\t");
            if (!values[2].equals(null) && values[2] != "") {
                context.write(new Text(values[1]), new IntWritable(1));
                i++;
            }
        }
    }



    public static void run(String inputPath, String outputPath) {
        Configuration conf = new Configuration();
        conf.set("fs.defaultFS", "hdfs://192.168.136.100:9000");

        Job job = null;
        try {
            job = Job.getInstance(conf, "countnotnull");
        } catch (IOException e) {
            // TODO Auto-generated catch block
            e.printStackTrace();
        }
        assert job != null;
        job.setJarByClass(CountNotNull.class);
        job.setMapperClass(wyMap.class);
        //job.setReducerClass(wyReduce.class);

        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(IntWritable.class);

        try {
            FileInputFormat.addInputPath(job, new Path(inputPath));
        } catch (IllegalArgumentException e) {
            e.printStackTrace();
        } catch (IOException e) {
            e.printStackTrace();
        }
        try {
            FileOutputFormat.setOutputPath(job, new Path(outputPath));
            job.waitForCompletion(true);
        } catch (ClassNotFoundException e) {
            e.printStackTrace();
        } catch (IOException e) {
            e.printStackTrace();
        } catch (InterruptedException e) {
            e.printStackTrace();
        }

    }

    public static void main(String[] args) {
        run("/sogou/data/sogou.500w.utf8", "/sogou/data/CountNotNull");
        System.out.println("非空条数:  " + i);
    }

}

(3)无重复总条数

package com.hadoop;

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

import java.io.File;
import java.io.IOException;

public class CountNotRepeat {

    public static int i = 0;
    public static class NotRepeatMap extends Mapper<Object , Text , Text, Text>{
        @Override
        protected void map(Object key, Text value, Mapper<Object, Text, Text, Text>.Context context) throws IOException, InterruptedException {

            String text = value.toString();
            String[] values = text.split("\t");
            String time = values[0];
            String uid = values[1];
            String name = values[2];
            String url = values[5];
            context.write(new Text(time+uid+name+url), new Text("1"));

        }
    }

    public static class NotRepeatReduc extends Reducer<Text , IntWritable, Text, IntWritable>{
        @Override
        protected void reduce(Text key, Iterable<IntWritable> values, Reducer<Text,IntWritable,Text,IntWritable>.Context context) throws IOException, InterruptedException {
            i++;
            context.write(new Text(key.toString()),new IntWritable(i));
        }
    }

    public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
        Configuration conf = new Configuration();
        conf.set("fs.defaultFS", "hdfs://192.168.136.100:9000");

        Job job = null;
        try {
            job = Job.getInstance(conf, "countnotnull");
        } catch (IOException e) {
            // TODO Auto-generated catch block
            e.printStackTrace();
        }
        assert job != null;
        job.setJarByClass(CountNotRepeat.class);
        job.setMapperClass(NotRepeatMap.class);
        job.setReducerClass(NotRepeatReduc.class);

        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(Text.class);

        try {
            FileInputFormat.addInputPath(job, new Path("/sogou/data/sogou.500w.utf8"));
        } catch (IllegalArgumentException e) {
            e.printStackTrace();
        } catch (IOException e) {
            e.printStackTrace();
        }
        try {
            FileOutputFormat.setOutputPath(job, new Path("/sogou/data/CountNotRepeat"));
            job.waitForCompletion(true);
        } catch (ClassNotFoundException e) {
            e.printStackTrace();
        } catch (IOException e) {
            e.printStackTrace();
        } catch (InterruptedException e) {
            e.printStackTrace();
        }

        System.out.println("无重复总条数为:  " + i);

    }
}

(4)独立UID总数

package com.hadoop;

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

import java.io.IOException;

public class CountNotMoreUid {

    public static int i = 0;
    public static class UidMap extends Mapper<Object , Text , Text, Text>{
        @Override
        protected void map(Object key, Text value, Mapper<Object, Text, Text, Text>.Context context) throws IOException, InterruptedException {

            String text = value.toString();
            String[] values = text.split("\t");
            String uid = values[1];
            context.write(new Text(uid), new Text("1"));

        }
    }

    public static class UidReduc extends Reducer<Text , IntWritable, Text, IntWritable>{
        @Override
        protected void reduce(Text key, Iterable<IntWritable> values, Reducer<Text,IntWritable,Text,IntWritable>.Context context) throws IOException, InterruptedException {
            i++;
            context.write(new Text(key.toString()),new IntWritable(i));
        }
    }

    public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
        Configuration conf = new Configuration();
        conf.set("fs.defaultFS", "hdfs://192.168.136.100:9000");

        Job job = null;
        try {
            job = Job.getInstance(conf, "countnotnull");
        } catch (IOException e) {
            // TODO Auto-generated catch block
            e.printStackTrace();
        }
        assert job != null;
        job.setJarByClass(CountNotNull.class);
        job.setMapperClass(UidMap.class);
        job.setReducerClass(UidReduc.class);

        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(Text.class);

        try {
            FileInputFormat.addInputPath(job, new Path("/sogou/data/sogou.500w.utf8"));
        } catch (IllegalArgumentException e) {
            e.printStackTrace();
        } catch (IOException e) {
            e.printStackTrace();
        }
        try {
            FileOutputFormat.setOutputPath(job, new Path("/sogou/data/CountNotMoreUid"));
            job.waitForCompletion(true);
        } catch (ClassNotFoundException e) {
            e.printStackTrace();
        } catch (IOException e) {
            e.printStackTrace();
        } catch (InterruptedException e) {
            e.printStackTrace();
        }

        System.out.println("独立UID条数:  " + i);

    }
}

(5)查询频度排名（频度最高的前50词）

package com.hadoop;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;

import java.io.IOException;
import java.util.TreeMap;


public class CountTop50 {

    public static class TopMapper  extends Mapper<LongWritable, Text, Text, LongWritable>{
        Text text =new Text();

        @Override
        protected void map(LongWritable key, Text value,Context context)
                throws IOException, InterruptedException {
            String[] line= value.toString().split("\t");
            String keys = line[2];
            text.set(keys);
            context.write(text,new LongWritable(1));
        }
    }


    public static class TopReducer extends Reducer< Text,LongWritable, Text, LongWritable>{
        Text text = new Text();
        TreeMap<Integer,String > map = new TreeMap<Integer,String>();
        @Override
        protected void reduce(Text key, Iterable<LongWritable> value, Context context)
                throws IOException, InterruptedException {
            int sum=0;//key出现次数
            for (LongWritable ltext : value) {
                sum+=ltext.get();
            }
            map.put(sum,key.toString());
            //去前50条数据
            if(map.size()>50){
                map.remove(map.firstKey());
            }
        }

        @Override
        protected void cleanup(Context context)
                throws IOException, InterruptedException {
            for(Integer count:map.keySet()){
                context.write(new Text(map.get(count)), new LongWritable(count));
            }
        }
    }



    public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
        Configuration conf = new Configuration();
        conf.set("fs.defaultFS", "hdfs://192.168.136.100:9000");

        Job job = Job.getInstance(conf, "count");
        job.setJarByClass(CountTop50.class);
        job.setJobName("Five");

        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(LongWritable.class);

        job.setMapperClass(TopMapper.class);
        job.setReducerClass(TopReducer.class);



        FileInputFormat.addInputPath(job, new Path("/sogou/data/sogou.500w.utf8"));
        FileOutputFormat.setOutputPath(job, new Path("/sogou/data/CountTop50"));

        job.waitForCompletion(true);
    }




}

(6)查询次数大于2次的用户总数

package com.hadoop;

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

import java.io.IOException;

public class CountQueriesGreater2 {

    public static int total = 0;
    public static class MyMaper extends Mapper<Object, Text, Text, IntWritable> {


        protected void map(Object key, Text value, Mapper<Object, Text, Text, IntWritable>.Context context)
                throws IOException, InterruptedException {

            String[] str = value.toString().split("\t");
            Text word;
            IntWritable one = new IntWritable(1);
            word = new Text(str[1]);
            context.write(word, one);
        }

    }


    public static class MyReducer extends Reducer<Text, IntWritable, Text, IntWritable> {
        @Override
        protected void reduce(Text arg0, Iterable<IntWritable> arg1,
                              Reducer<Text, IntWritable, Text, IntWritable>.Context arg2) throws IOException, InterruptedException {
            // arg0是一个单词 arg1是对应的次数
            int sum = 0;
            for (IntWritable i : arg1) {
                sum += i.get();
            }
            if(sum>2){
                total=total+1;
            }
            //arg2.write(arg0, new IntWritable(sum));
        }

    }

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

        Configuration conf = new Configuration();
        conf.set("fs.defaultFS", "hdfs://192.168.136.100:9000");
        // 1.实例化一个Job
        Job job = Job.getInstance(conf, "six");
        // 2.设置mapper类
        job.setMapperClass(MyMaper.class);
        // 3.设置Combiner类 不是必须的
        // job.setCombinerClass(MyReducer.class);
        // 4.设置Reducer类
        job.setReducerClass(MyReducer.class);
        // 5.设置输出key的数据类型
        job.setOutputKeyClass(Text.class);
        // 6.设置输出value的数据类型
        job.setOutputValueClass(IntWritable.class);
        // 设置通过哪个类查找job的Jar包
        job.setJarByClass(CountQueriesGreater2.class);
        // 7.设置输入路径
        FileInputFormat.addInputPath(job, new Path("/sogou/data/sogou.500w.utf8"));
        // 8.设置输出路径
        FileOutputFormat.setOutputPath(job, new Path("/sogou/data/CountQueriesGreater2"));
        // 9.执行该作业
        job.waitForCompletion(true);
        System.out.println("查询次数大于2次的用户总数：" + total + "条");


    }

}

(7)查询次数大于2次的用户占比

package com.hadoop;



import java.io.IOException;
import java.util.StringTokenizer;

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

public class CountQueriesGreaterPro {
    /*
     *
     * InputFormat ->FileInputFormat(子类)-> TextInputFormat(子类)
     * 程序当中默认调用的就是TextInputFormat 1.验证数据路径是否合法 2.TextInputFormat默认读取数据，就是一行一行读取的
     *
     * 开始执行map，一个map就是一个task（是一个Java进程，运行在JVM上的）
     * map执行完毕后，会执行combiner（可选项），对一个map中的重复单词进行合并，value是一个map中出现的相同单词次数。
     * shuffle(partitioner分区，进行不同map的值并按key排序)
     * Reducer接收所有map数据，并将具有相同key的value值合并
     *
     * OutputFormat ->FileOutputFormat(子类)->TextOutputFormat(子类) 1.验证数据路径是否合法
     * 2.TextOutputFormat写入文件格式是 key + "\t" + value + "\n"
     */

    // Text是一个能够写入文件的Java String数据类型
    // IntWritable是能够写入文件的int数据类型
    // 头两个参数表示的是输入数据key和value的数据类型
    // 后两个数据表示的就是输出数据key和value的数据类型
    public static int total1 = 0;
    public static int total2 = 0;
    public static class MyMaper extends Mapper<Object, Text, Text, IntWritable> {

        @Override
        // key是行地址
        // value是一行字符串
        protected void map(Object key, Text value, Mapper<Object, Text, Text, IntWritable>.Context context)
                throws IOException, InterruptedException {

            total2++;
            String[] str = value.toString().split("\t");
            Text word;
            IntWritable one = new IntWritable(1);
            word = new Text(str[1]);
            context.write(word, one);
            // 执行完毕后就是一个单词 对应一个value(1)
        }

    }

    // 头两个参数表示的是输入数据key和value的数据类型
    // 后两个数据表示的就是输出数据key和value的数据类型
    public static class MyReducer extends Reducer<Text, IntWritable, Text, IntWritable> {

        @Override
        protected void reduce(Text arg0, Iterable<IntWritable> arg1,
                              Reducer<Text, IntWritable, Text, IntWritable>.Context arg2) throws IOException, InterruptedException {

            // arg0是一个单词 arg1是对应的次数
            int sum = 0;
            for (IntWritable i : arg1) {
                sum += i.get();
            }
            if(sum>2){
                total1++;
            }
            arg2.write(arg0, new IntWritable(sum));
        }

    }

    public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
        System.out.println("seven begin");
        Configuration conf = new Configuration();
        conf.set("fs.defaultFS", "hdfs://192.168.136.100:9000");
        // 1.实例化一个Job
        Job job = Job.getInstance(conf, "seven");
        // 2.设置mapper类
        job.setMapperClass(MyMaper.class);
        // 3.设置Combiner类 不是必须的
        // job.setCombinerClass(MyReducer.class);
        // 4.设置Reducer类
        job.setReducerClass(MyReducer.class);
        // 5.设置输出key的数据类型
        job.setOutputKeyClass(Text.class);
        // 6.设置输出value的数据类型
        job.setOutputValueClass(IntWritable.class);
        // 设置通过哪个类查找job的Jar包
        job.setJarByClass(CountQueriesGreaterPro.class);
        // 7.设置输入路径
        FileInputFormat.addInputPath(job, new Path("/sogou/data/sogou.500w.utf8"));
        // 8.设置输出路径
        FileOutputFormat.setOutputPath(job, new Path("/sogou/data/CountQueriesGreaterPro"));
        // 9.执行该作业
        job.waitForCompletion(true);
        System.out.println("total1="+total1+"\ttotal2="+total2);
        float percentage = (float)total1/(float)total2;
        System.out.println("查询次数大于2次的用户占比为：" + percentage*100+"%");
        System.out.println("over");

    }

}

(8)Rank在10以内的点击次数占比

package com.hadoop;

import java.io.IOException;

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

public class CountRank {
    public static int sum1 = 0;
    public static int sum2 = 0;

    public static class MyMapper extends Mapper<Object, Text, Text, Text> {

        @Override
        protected void map(Object key, Text value, Mapper<Object, Text, Text, Text>.Context context)
                throws IOException, InterruptedException {
            sum2++;
            String[] str = value.toString().split("\t");
            int rank = Integer.parseInt(str[3]);
            if(rank<11)
            {
                sum1=sum1+1;

            }
        }

    }

    public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
        Configuration conf = new Configuration();
        conf.set("fs.defaultFS", "hdfs://192.168.136.100:9000");
        Job job = Job.getInstance(conf, "eight");
        job.setMapperClass(MyMapper.class);

        job.setOutputKeyClass(Text.class);

        job.setOutputValueClass(Text.class);

        job.setJarByClass(CountRank.class);

        FileInputFormat.addInputPath(job, new Path("/sogou/data/sogou.500w.utf8"));

        FileOutputFormat.setOutputPath(job, new Path("/sogou/data/CountRank"));
        job.waitForCompletion(true);
        System.out.println("sum1="+sum1+"\tsum2="+sum2);
        float percentage = (float)sum1/(float)sum2;
        System.out.println("Rank在10以内的点击次数占比：" +percentage*100+"%");

    }

}

(9)直接输入URL查询的比例

package com.hadoop;


import java.io.IOException;
import java.util.regex.Matcher;
import java.util.regex.Pattern;

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

public class CountURL {
    public static int sum1 = 0;
    public static int sum2 = 0;

    public static class MyMapper extends Mapper<Object, Text, Text, Text> {

        @Override
        protected void map(Object key, Text value, Mapper<Object, Text, Text, Text>.Context context)
                throws IOException, InterruptedException {
            String[] str = value.toString().split("\t");
            Pattern p = Pattern.compile("www");
            Matcher matcher = p.matcher(str[2]);
            matcher.find();
            try {
                if(matcher.group()!=null)
                    sum1++;
                sum2++;
            } catch (Exception e) {
                sum2++;
            }

        }

    }

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

        Configuration conf = new Configuration();
        conf.set("fs.defaultFS", "hdfs://192.168.136.100:9000");
        Job job = Job.getInstance(conf, "nine");
        job.setMapperClass(MyMapper.class);
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(Text.class);
        job.setJarByClass(CountURL.class);
        FileInputFormat.addInputPath(job, new Path("/sogou/data/sogou.500w.utf8"));
        FileOutputFormat.setOutputPath(job, new Path("/sogou/data/CountURL"));
        job.waitForCompletion(true);
        System.out.println("sum1="+sum1+"\tsum2="+sum2);
        float percentage = (float)sum1/(float)sum2;
        System.out.println("直接用url'%www%'查询的用户占比：" +percentage*100+"%");

    }

}

(10)查询搜索过”仙剑奇侠传“的uid，并且次数大于3

package com.hadoop;


import java.io.IOException;

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



public class CountUidGreater3 {
    public static String Str="";
    public static int i=0;
    public static class Map extends Mapper<Object, Text, Text, IntWritable>{
        @Override
        protected void map(Object key, Text value, Mapper<Object, Text, Text, IntWritable>.Context context)
                throws IOException, InterruptedException {
            String []values=value.toString().split("\t");
            String pattern="仙剑奇侠传";
            if(values[2].equals(pattern)){
                context.write(new Text(values[1]), new IntWritable(1));
            }
        }
    }
    public static class Reduce extends Reducer<Text, IntWritable, Text, IntWritable>{
        @Override
        protected void reduce(Text key, Iterable<IntWritable> value,
                              Reducer<Text, IntWritable, Text, IntWritable>.Context context) throws IOException, InterruptedException {

            int sum=0;
            for(IntWritable v:value){
                sum=sum+v.get();
            }
            if(sum>3){
                Str=Str+key.toString()+"\n";
                i++;
            }

        }

    }


    public static void main(String[] args) {
        Configuration conf=new Configuration();
        conf.set("fs.defaultFS", "hdfs://192.168.136.100:9000");

        Job job = null;
        try {
            job = Job.getInstance(conf, "count");
        } catch (IOException e) {
            // TODO Auto-generated catch block
            e.printStackTrace();
        }
        job.setJarByClass(CountUidGreater3.class);
        job.setMapperClass(Map.class);
        job.setReducerClass(Reduce.class);

        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(IntWritable.class);

        try {
            FileInputFormat.addInputPath(job, new Path("/sogou/data/sogou.500w.utf8"));
        } catch (IllegalArgumentException e) {
            // TODO Auto-generated catch block
            e.printStackTrace();
        } catch (IOException e) {
            // TODO Auto-generated catch block
            e.printStackTrace();
        }

        try {
            FileOutputFormat.setOutputPath(job, new Path("/sogou/data/CountUidGreater3"));
            job.waitForCompletion(true);
        } catch (ClassNotFoundException e) {
            // TODO Auto-generated catch block
            e.printStackTrace();
        } catch (IOException e) {
            // TODO Auto-generated catch block
            e.printStackTrace();
        } catch (InterruptedException e) {
            // TODO Auto-generated catch block
            e.printStackTrace();
        }
        System.out.println("i:  "+i);
        System.out.println(Str);
    }
}

---

5.将4每步骤生成的结果保存到HDFS中。
在第四步中的每个HQL前面加上：Insert overwrite directory ‘位置’

eg:Insert overwrite directory '/sogou/data/1' Select count(*) from sougou;

6.将5生成的文件通过Java API方式导入到HBase（一张表）。

package com.hadoop;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.hbase.HBaseConfiguration;
import org.apache.hadoop.hbase.client.Mutation;
import org.apache.hadoop.hbase.client.Put;
import org.apache.hadoop.hbase.mapreduce.TableMapReduceUtil;
import org.apache.hadoop.hbase.mapreduce.TableOutputFormat;
import org.apache.hadoop.hbase.mapreduce.TableReducer;
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.Mapper;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.input.TextInputFormat;

import java.io.IOException;

public class HBaseImport{

    // reduce输出的表名
    private static String tableName = "test";
    // 初始化连接
    static Configuration conf = null;
    static {
        conf = HBaseConfiguration.create();
        conf.set("hbase.rootdir", "hdfs://192.168.136.100:9000/hbase");
        conf.set("hbase.master", "hdfs://192.168.136.100:60000");
        conf.set("hbase.zookeeper.property.clientPort", "2181");
        conf.set("hbase.zookeeper.quorum", "master,slave1,slave2");
        conf.set(TableOutputFormat.OUTPUT_TABLE, tableName);
    }

    public static class BatchMapper extends
            Mapper<LongWritable, Text, LongWritable, Text> {
        protected void map(LongWritable key, Text value,
                           Mapper<LongWritable, Text, LongWritable, Text>.Context context)
                throws IOException, InterruptedException {
            String line = value.toString();
            Text v2s = new Text();
            v2s.set(line);
            context.write(key, v2s);
        }
    }

    public static class BatchReducer extends
            TableReducer<LongWritable, Text, NullWritable> {
        private String family = "info";

        @Override
        protected void reduce(
                LongWritable arg0,
                Iterable<Text> v2s,
                Reducer<LongWritable, Text, NullWritable, Mutation>.Context context)
                throws IOException, InterruptedException {
            for (Text v2 : v2s) {
                String[] splited = v2.toString().split("\t");
                String rowKey = splited[0];
                Put put = new Put(rowKey.getBytes());
                put.add(family.getBytes(), "raw".getBytes(), v2.toString()
                        .getBytes());
                context.write(NullWritable.get(), put);
            }
        }
    }

    public static void imputil(String str) throws IOException, ClassNotFoundException,
            InterruptedException {
        Job job = Job.getInstance(conf, HBaseImport.class.getSimpleName());
        TableMapReduceUtil.addDependencyJars(job);
        job.setJarByClass(HBaseImport.class);
        FileInputFormat.setInputPaths(job,str);
        job.setInputFormatClass(TextInputFormat.class);
        job.setMapperClass(BatchMapper.class);
        job.setMapOutputKeyClass(LongWritable.class);
        job.setMapOutputValueClass(Text.class);
        job.setReducerClass(BatchReducer.class);
        job.setOutputFormatClass(TableOutputFormat.class);
        job.waitForCompletion(true);
    }

    public static void main(String[] args) throws ClassNotFoundException, IOException, InterruptedException {
        String[] str={
                "hdfs://192.168.136.100:9000/sogou/data/1/000000_0",
                "hdfs://192.168.136.100:9000/sogou/data/2/000000_0",
                "hdfs://192.168.136.100:9000/sogou/data/3/000000_0",
                "hdfs://192.168.136.100:9000/sogou/data/4/000000_0",
                "hdfs://192.168.136.100:9000/sogou/data/5/000000_0",
                "hdfs://192.168.136.100:9000/sogou/data/6/000000_0",
                "hdfs://192.168.136.100:9000/sogou/data/9/000000_0",
                "hdfs://192.168.136.100:9000/sogou/data/10/000000_0"
                };
        for (String stri:str){
            imputil(stri);
        }
    }
}

7.通过HBase shell命令查询6导出的结果。
命令：scan ‘test’