元数据与数据治理｜Intellij IDEA提交远程Hadoop MapReduce任务（第八篇）

本是古典何须时尚 2022-03-29 13:00 169阅读 0赞

## 1.新建IntelliJ下空的的maven项目 ##

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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

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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

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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

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## 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

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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。

作者：Chowkin  
链接：https://www.jianshu.com/p/41569d558fde  
來源：简书

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