Intellij IDEA提交远程Hadoop MapReduce任务

1.新建IntelliJ下空的的maven项目

直接next即可。

2.配置依赖

编辑pom.xml文件，添加apache源和hadoop依赖

基础依赖hadoop-core和hadoop-common；
读写HDFS，需要依赖hadoop-hdfs和hadoop-client；
如果需要读写HBase，则还需要依赖hbase-client

 <properties>
        <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
    </properties>

    <name>hadoop</name>
    <url>http://maven.apache.org</url>

    <dependencies>
        <dependency>
            <groupId>org.apache.hadoop</groupId>
            <artifactId>hadoop-common</artifactId>
            <version>2.8.1</version>
        </dependency>

        <dependency>
            <groupId>org.apache.hadoop</groupId>
            <artifactId>hadoop-hdfs</artifactId>
            <version>2.8.1</version>
        </dependency>

        <dependency>
            <groupId>org.apache.hadoop</groupId>
            <artifactId>hadoop-client</artifactId>
            <version>2.8.1</version>
        </dependency>

    </dependencies>

3.添加core-site.xml到resources文件

将虚拟机上的hadoop下/etc/hadoop/core-site.xml文件拷贝到此项目下resources文件夹下

注意master是我虚拟机ip地址的映射，如果没有配置hosts文件那么这里应该填的是你虚拟机的IP地址。

4.编写一个WordCount类

WordCount.java


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 WordCount {

    public static class TokenizerMapper
            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 IntSumReducer
            extends Reducer<Text,IntWritable,Text,IntWritable> {
        private IntWritable result = new IntWritable();

        public void reduce(Text key, Iterable<IntWritable> values,
                           Context context
        ) throws IOException, InterruptedException {
            int 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();
        conf.set("mapreduce.cluster.local.dir","/Users/CHOUKIN/hadoop/var");//在此处有一坑，本地需要添加一个缓存文件夹
        Job job = Job.getInstance(conf, "word count");
        job.setJarByClass(WordCount.class);
        job.setMapperClass(TokenizerMapper.class);
        job.setCombinerClass(IntSumReducer.class);
        job.setReducerClass(IntSumReducer.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);
    }
}

注意：conf.set("mapreduce.cluster.local.dir","/Users/CHOUKIN/hadoop/var");//在此处有一坑，本地需要添加一个缓存文件夹
如果没有这个本地缓存文件夹，会报以下错误

查询hadoop官网docs关于mapred-default.xml参数简介

mapreduce.cluster.local.dir :
The local directory where MapReduce stores intermediate data files. May be a comma-separated list of directories on different devices in order to spread disk i/o. Directories that do not exist are ignored.

这个参数是MapReduce 存储中间数据文件的本地目录。对不同的设备上的目录可以用逗号分隔，用以加快磁盘 i/o 。不存在的目录将被忽略。

5.配置运行参数

在Intellij菜单栏中选择Run->Edit Configurations，在弹出来的对话框中点击+，新建一个Application配置。配置Main class为WordCount（可以点击右边的...选择），

为Program arguments添加输入路径以及输出路径，记得把ip地址改为自己虚拟机的ip地址

6.运行程序

拷贝了一篇满分英语作文在test.txt里，运行结果如下

每次运行时检查hdfs上是否有output文件夹，如果有，请删除output文件夹。

感谢我的基友月巴巴提供了莫大的帮助

参考：
hadoop文档关于mapred-default.xml参数详解

常用 Hadoop 集群参数(mapred-default.xml)

Intellij IDEA提交远程Hadoop MapReduce任务