Mapreduce+hive练习

要求与说明：

Result文件数据说明：

Ip：106.39.41.166,（城市）

Date：10/Nov/2016:00:01:02 +0800,（日期）

Day：10,（天数）

Traffic: 54 ,（流量）

Type: video,（类型：视频video或文章article）

Id: 8701（视频或者文章的id）

测试要求：

1、 数据清洗：按照进行数据清洗，并将清洗后的数据导入hive数据库中。

两阶段数据清洗：

（1）第一阶段：把需要的信息从原始日志中提取出来

ip:    199.30.25.88

time:  10/Nov/2016:00:01:03 +0800

traffic:  62

文章： article/11325

视频： video/3235

（2）第二阶段：根据提取出来的信息做精细化操作

ip--->城市 city（IP）

date--> time:2016-11-10 00:01:03

day: 10

traffic:62

type:article/video

id:11325

Result.txt文件：

第一阶段源代码：

package hivetest;

import java.io.IOException;

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;
public class Hivetest1 {

    //  static ClassService service=new ClassService();
    public static class MyMapper extends Mapper<LongWritable, Text, Text/*map对应键类型*/, Text/*map对应值类型*/>
    {
         protected void map(LongWritable key, Text value,Context context)throws IOException, InterruptedException
         {
              String[] strNlist = value.toString().split(",");//如何分隔
              //LongWritable，IntWritable,Text等
              
              context.write(new Text(strNlist[0])/*map对应键类型*/,new Text(strNlist[1]+","+strNlist[2]+","+strNlist[3]+","+strNlist[4]+","+strNlist[5])/*map对应值类型*/);
         }
    }
    public static class MyReducer extends Reducer<Text/*map对应键类型*/, Text/*map对应值类型*/, Text/*reduce对应键类型*/, Text/*reduce对应值类型*/>
    {
        // static No1Info info=new No1Info();
         protected void reduce(Text key, Iterable<Text/*map对应值类型*/> values,Context context)throws IOException, InterruptedException
         {
             for (/*map对应值类型*/Text init : values)
             {
                 context.write( key/*reduce对应键类型*/, new Text(init)/*reduce对应值类型*/);
             }
         }
    }
    
    public static void main(String[] args) throws Exception {
        Configuration conf = new Configuration();        
        Job job = Job.getInstance();
        job.setJarByClass(Hivetest1.class);
        job.setMapperClass(MyMapper.class);
        job.setMapOutputKeyClass(/*map对应键类型*/Text.class);
        job.setMapOutputValueClass( /*map对应值类型*/Text.class);    
        // TODO: specify a reducer
        job.setReducerClass(MyReducer.class);
        job.setOutputKeyClass(/*reduce对应键类型*/Text.class);
        job.setOutputValueClass(/*reduce对应值类型*/Text.class);

        // TODO: specify input and output DIRECTORIES (not files)
        FileInputFormat.setInputPaths(job, new Path("hdfs://localhost:9000/user/hive/warehouse/test/result.txt"));
        FileOutputFormat.setOutputPath(job, new Path("hdfs://localhost:9000/user/hive/warehouse/result"));

        boolean flag = job.waitForCompletion(true);
        System.out.println("完成!");    //任务完成提示
        System.exit(flag ? 0 : 1);
        System.out.println();
    }

}

运行结果：

 第二阶段代码：

import java.lang.String;
import java.text.SimpleDateFormat;
import java.util.Date;
import java.util.Locale;
import java.io.IOException;
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;
public class sjqx {
     public static final SimpleDateFormat FORMAT = new SimpleDateFormat("d/MMM/yyyy:HH:mm:ss", Locale.ENGLISH); //原时间格式
     public static final SimpleDateFormat dateformat1 = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");//现时间格式
   private static Date parseDateFormat(String string) {         //转换时间格式
        Date parse = null;
        try {
            parse = FORMAT.parse(string);
        } catch (Exception e) {
            e.printStackTrace();
        }
        return parse;
    }
    public static class MyMapper extends Mapper<LongWritable, Text, Text/*map对应键类型*/, Text/*map对应值类型*/>
    {
         protected void map(LongWritable key, Text value,Context context)throws IOException, InterruptedException
         {
              String[] strNlist = value.toString().split(",");//如何分隔
              //LongWritable，IntWritable,Text等
              Date date = parseDateFormat(strNlist[1]);
              context.write(new Text(strNlist[0])/*map对应键类型*/,new Text(dateformat1.format(date)+" "+strNlist[2]+" "+strNlist[3]+" "+strNlist[4]+" "+strNlist[5])/*map对应值类型*/);
         }
    }
    public static class MyReducer extends Reducer<Text/*map对应键类型*/, Text/*map对应值类型*/, Text/*reduce对应键类型*/, Text/*reduce对应值类型*/>
    {
//        static No1Info info=new No1Info();
         protected void reduce(Text key, Iterable<Text/*map对应值类型*/> values,Context context)throws IOException, InterruptedException
         {
             for (/*map对应值类型*/Text init : values)
             {

                 context.write( key/*reduce对应键类型*/, new Text(init)/*reduce对应值类型*/);
             }
         }
    }
    
    public static void main(String[] args) throws Exception {
        Configuration conf = new Configuration();    
        Job job = Job.getInstance();
        //job.setJar("MapReduceDriver.jar");
        job.setJarByClass(sjqx.class);
        // TODO: specify a mapper
        job.setMapperClass(MyMapper.class);
        job.setMapOutputKeyClass(/*map对应键类型*/Text.class);
        job.setMapOutputValueClass( /*map对应值类型*/Text.class);
        
        // TODO: specify a reducer
        job.setReducerClass(MyReducer.class);
        job.setOutputKeyClass(/*reduce对应键类型*/Text.class);
        job.setOutputValueClass(/*reduce对应值类型*/Text.class);

        // TODO: specify input and output DIRECTORIES (not files)
        FileInputFormat.setInputPaths(job, new Path("hdfs://localhost:9000/test/in/result"));
        FileOutputFormat.setOutputPath(job, new Path("hdfs://localhost:9000/test/out"));

        boolean flag = job.waitForCompletion(true);
        System.out.println("SUCCEED!"+flag);    //任务完成提示
        System.exit(flag ? 0 : 1);
        System.out.println();
    }
}

运行结果：