hadoop相关

执行wordcount

代码

package org.apache.hadoop.examples;

import java.io.IOException;

import java.util.Iterator;

import java.util.StringTokenizer;

import org.apache.hadoop.fs.Path;

import org.apache.hadoop.io.IntWritable;

import org.apache.hadoop.io.LongWritable;

import org.apache.hadoop.io.Text;

import org.apache.hadoop.mapred.FileInputFormat;

import org.apache.hadoop.mapred.FileOutputFormat;

import org.apache.hadoop.mapred.JobClient;

import org.apache.hadoop.mapred.JobConf;

import org.apache.hadoop.mapred.MapReduceBase;

import org.apache.hadoop.mapred.Mapper;

import org.apache.hadoop.mapred.OutputCollector;

import org.apache.hadoop.mapred.Reducer;

import org.apache.hadoop.mapred.Reporter;

import org.apache.hadoop.mapred.TextInputFormat;

import org.apache.hadoop.mapred.TextOutputFormat;

public class WordCount {

    public static class Map extends MapReduceBase implements

            Mapper<LongWritable, Text, Text, IntWritable> {

        private final static IntWritable one = new IntWritable();

        private Text word = new Text();

        public void map(LongWritable key, Text value,

                OutputCollector<Text, IntWritable> output, Reporter reporter)

                throws IOException {

            String line = value.toString();

            StringTokenizer tokenizer = new StringTokenizer(line);

            while (tokenizer.hasMoreTokens()) {

                word.set(tokenizer.nextToken());

                output.collect(word, one);

            }

        }

    }

    public static class Reduce extends MapReduceBase implements

            Reducer<Text, IntWritable, Text, IntWritable> {

        public void reduce(Text key, Iterator<IntWritable> values,

                OutputCollector<Text, IntWritable> output, Reporter reporter)

                throws IOException {

            int sum = ;

            while (values.hasNext()) {

                sum += values.next().get();

            }

            output.collect(key, new IntWritable(sum));

        }

    }

    public static void main(String[] args) throws Exception {

        JobConf conf = new JobConf(WordCount.class);

        conf.setJobName("wordcount");

        conf.setOutputKeyClass(Text.class);

        conf.setOutputValueClass(IntWritable.class);

        conf.setMapperClass(Map.class);

        conf.setCombinerClass(Reduce.class);

        conf.setReducerClass(Reduce.class);

        conf.setInputFormat(TextInputFormat.class);

        conf.setOutputFormat(TextOutputFormat.class);

        FileInputFormat.setInputPaths(conf, new Path(args[]));

        FileOutputFormat.setOutputPath(conf, new Path(args[]));

        JobClient.runJob(conf);

    }

}

首先进行编译：

javac -classpath ./share/hadoop/common/hadoop-common-2.7..jar:./share/hadoop/mapreduce/hadoop-mapreduce-client-core-2.7..jar -d WordCount ./WordCount/WordCount.java

然后压包

jar -cvf wordcount.jar org/*

在复制到hadoop的工作目录下

然后在hadoop工作目录下面新建一个input目录 mkdir input，在目录里面新建一个文件vi file1,输入以下内容：
hello world
hello hadoop
hello mapreduce
，把该文件上传到hadoop的分布式文件系统中去

./bin/hadoop fs -put input/file* input

（6）然后我们开始执行

./bin/hadoop jar wordcount.jar org.apache.hadoop.examples.WordCount input wordcount_output

（7）最后我们查看运行结果

./bin/hadoop fs -cat wordcount_output/part-r-00000

参考：

http://cardyn.iteye.com/blog/1356361

https://blog.csdn.net/qichangleixin/article/details/43376587

二.往hdfs写数据

java代码

import org.apache.hadoop.conf.Configuration;

import org.apache.hadoop.fs.FileSystem;

import org.apache.hadoop.fs.Path;

import org.apache.hadoop.io.IOUtils;

import java.io.*;

import java.net.URI;

/**

 * blog: http://www.iteblog.com/

 * Date: 14-1-2

 * Time: 下午6:09

 */

public class AppendContent {

    public static void main(String[] args) {

        String hdfs_path = "input/file1";//文件路径

        Configuration conf = new Configuration();

        conf.setBoolean("dfs.support.append", true);

        String inpath = "./append.txt";

        FileSystem fs = null;

        try {

            fs = FileSystem.get(URI.create(hdfs_path), conf);

            //要追加的文件流，inpath为文件

            InputStream in = new

                  BufferedInputStream(new FileInputStream(inpath));

            OutputStream out = fs.append(new Path(hdfs_path));

            IOUtils.copyBytes(in, out, , true);

        } catch (IOException e) {

            e.printStackTrace();

        }

    }

}

注意指定的hdfs路径，用hdfs://localhost:9000/input/路径一直不行，不知道什么原因。

编译

javac -classpath ./share/hadoop/common/hadoop-common-2.7..jar:./share/hadoop/mapreduce/hadoop-mapreduce-client-core-2.7..jar -d ./classes ./my_append/AppendContent.java

压包

jar -cvf ./my_jar/append.jar ./classes/*

运行

./bin/hadoop jar ./my_jar/append.jar AppendContent

AppendContent是类的名字

查看

./bin/hdfs dfs -cat input/*

或者代码可以改为通过args传参的方式传入hdfs路径，方便多进程操作

import org.apache.hadoop.conf.Configuration;

import org.apache.hadoop.fs.FileSystem;

import org.apache.hadoop.fs.Path;

import org.apache.hadoop.io.IOUtils;

import org.apache.hadoop.fs.FSDataInputStream;

import org.apache.hadoop.fs.FSDataOutputStream; 

import java.io.*;

import java.net.URI;

/**

 * blog: http://www.iteblog.com/

 * Date: 14-1-2

 * Time: 下午6:09

 */

public class AppendContent {

    public static void main(String[] args) {

        //String hdfs_path = "input/file1";//文件路径

        String hdfs_path = args[];

        Configuration conf = new Configuration();

        conf.setBoolean("dfs.support.append", true);

        //String inpath = "./append.txt";

        FileSystem fs = null;

        try {

            fs = FileSystem.get(URI.create(hdfs_path), conf);

            FSDataOutputStream out = fs.append(new Path(hdfs_path));

            String s="";

            for(int i=;i<;i++)

            {

                for(int j=;j<;j++)

                {

                    s+='a';

                }

                int readLen = s.getBytes().length;

                out.write(s.getBytes(), , readLen);

            }

            //int readLen = "0123456789".getBytes().length;    

            //while (-1 != readLen) 

            //out.write("0123456789".getBytes(), 0, readLen); 

            //要追加的文件流，inpath为文件

            //InputStream in = new

            //      BufferedInputStream(new FileInputStream(inpath));

            //OutputStream out = fs.append(new Path(hdfs_path));

            //IOUtils.copyBytes(in, out, 4096, true);

            } catch (IOException e) {

                e.printStackTrace();

            }

        }

    }

编译与压包命令同上，执行命令如下

./bin/hadoop jar ./my_jar/append.jar AppendContent input/file1

参考：https://blog.csdn.net/jameshadoop/article/details/24179413

https://blog.csdn.net/wypblog/article/details/17914021

脚本

#!/bin/bash

#开始时间

begin=$(date +%s%N)

for ((i=; i<;i++))

do

    {

        ./bin/hadoop jar ./my_jar/append.jar AppendContent input/file${i}

    }

done

wait

#结束时间

end=$(date +%s%N)

#spend=$(expr $end - $begin)

use_tm=`echo $end $begin | awk '{ print ($1 - $2) / 1000000000}'`

echo "花费时间为$use_tm"

二. java在ext3中的测试

程序

import java.io.*;

import java.net.URI;

import java.io.BufferedWriter;

import java.io.File;

import java.io.FileOutputStream;

import java.io.FileWriter;

import java.io.IOException;

import java.io.OutputStreamWriter;

import java.io.RandomAccessFile;

public class Toext3 {

    public static void main(String[] args) {

        //String hdfs_path = "input/file1";//文件路径

        String ext3_path = args[];

        FileWriter writer = null;

        //String inpath = "./append.txt";

        try {

            String s="";

            for(int i=;i<;i++)

            {

                s="";

                for(int j=;j<;j++)

                {

                    s+='b';

                }

                writer = new FileWriter(ext3_path, true);

                writer.write(s);

                System.out.println(ext3_path);

            }

        } catch (IOException e) {

          e.printStackTrace();

        }finally {

            try {

                if(writer != null){

                    writer.close();

                }

            } catch (IOException e) {

                e.printStackTrace();

            }

        }

  }

}

编译：

javac -classpath ./share/hadoop/common/hadoop-common-2.7..jar:./share/hadoop/mapreduce/hadoop-mapreduce-client-core-2.7..jar -d ./data/classes data/Toext3.java

运行

java -cp ./data/classes/ Toext3 ./data/ext3/file0

在运行中，-cp指明class文件的路径，Toext3指出要运行的类

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