IntelliJ IDEA 开发hadoop 配置与打jar包

之前一直使用hadoop-streaming，克服心里抵触，开始使用java！！

1. 安装intelliJ环境

下载链接：
下载免费版足够我用了^_^!
然后按照官方说明
（1）解压安装包：

tar -zxvf idea-2016.1.1.tar.gz -C your_path

（2）安装：
执行解压后bin目录下的 idea.sh

2.基本开发需要导入的jar包

2.1创建工程

file->new->project

2.2选择开发jdk

选择java开发

选择jdk，new->jdk

选择需要的jdk版本

然后一路next，创建工程名

2.3创建工程后选择HADOOP开发需要的jar包

（1）file->project structure
（2）在窗口左侧栏选择Modules

（3）添加需要的jar包

我的jar包目录是
/home/warrior/bigData/hadoop/share/hadoop/common 目录下的 hadoop-common-2.6.0.jar
/home/warrior/bigData/hadoop/share/hadoop/mapreduce 目录下的 hadoop-mapreduce-client-common-2.6.0.jar和hadoop-mapreduce-client-core-2.6.0.jar

3. map-reduce程序基本框架

yourMapper extends Mapper ...... 然后重构 map 方法
yourReducer extends Reducer ...... 然后重构reduce方法
最后main方法里面实现hadoop conf设置

import org.apache.hadoop.conf.Configuration;
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.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 org.omg.CORBA.Object;

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

/**
 * Created by warrior on 16-4-15.
 */
public class wordCount {
    public static class WCMapper
        extends Mapper<Object, Text, Text, IntWritable>{

        private final static IntWritable one = new IntWritable(1);
        private Text word = new Text();

    public void map(Object key, Text value, Context context
    ) throws IOException, InterruptedException {
        StringTokenizer itr = new StringTokenizer(value.toString());
        while (itr.hasMoreTokens()) {
            word.set(itr.nextToken());
            context.write(word, one);
        }
    }
}

    public static class WCReducer
        extends Reducer<Text, IntWritable, Text, IntWritable>{
        private IntWritable result = new IntWritable();
        public void reduce(Text key, Iterable<IntWritable> values, Context context
            ) throws IOException, InterruptedException{
            Integer sum = 0;
            for(IntWritable val : values){
                sum += val.get();
            }
            result.set(sum);
            context.write(key, result);
        }
    }

    public static void main(String[] args) throws Exception{
        Configuration conf = new Configuration();
        Job job = Job.getInstance(conf, "word count!!");
        job.setJarByClass(wordCount.class);
        job.setMapperClass(WCMapper.class);
        job.setCombinerClass(WCReducer.class);
        job.setReducerClass(WCReducer.class);
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(IntWritable.class);
        FileInputFormat.addInputPath(job, new Path(args[0]));
        FileOutputFormat.setOutputPath(job, new Path(args[1]));
        System.exit(job.waitForCompletion(true)? 0:1);
    }
}

4. intelliJ 完成 hadoop可执行jar包生成

（1）file->project structure
（2）在窗口中选择Artifacts

（3）生成空JAR包，然后在Name处，命名jar包

（4）然后在output layout处添加生成包

（5）然后apply,完成。回到开发环境，通过build->build artifacts->build 或者 rebuild

5. 生成jar包后，job提交

hadoop jar ./out/artifacts/invertedList/invertedList.jar hdfs_input_path hdfs_output_path

参考：

http://blog.sina.com.cn/s/blog_3fe961ae0102uy42.html

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