1.新建IntelliJ下空的的maven項目
直接next即可。
2.配置依賴
編輯pom.xml文件，添加apache源和hadoop依賴
基礎依賴hadoop-core和hadoop-common；
讀寫HDFS，需要依賴hadoop-hdfs和hadoop-client；
如果需要讀寫HBase，則還需要依賴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
將虛擬機上的hadoop下/etc/hadoop/core-site.xml文件拷貝到此項目下resources文件夾下
注意master是我虛擬機ip地址的映射，如果沒有配置hosts文件那么這里應該填的是你虛擬機的IP地址。
4.編寫一個WordCount類
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");//在此處有一坑，本地需要添加一個緩存文件夾
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");//在此處有一坑，本地需要添加一個緩存文件夾
如果沒有這個本地緩存文件夾，會報以下錯誤
查詢hadoop官網docs關于mapred-default.xml參數簡介
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.
這個參數是MapReduce 存儲中間數據文件的本地目錄。對不同的設備上的目錄可以用逗號分隔，用以加快磁盤 i/o 。不存在的目錄將被忽略。
5.配置運行參數
在Intellij菜單欄中選擇Run->Edit Configurations，在彈出來的對話框中點擊+，新建一個Application配置。配置Main class為WordCount（可以點擊右邊的...選擇），
為Program arguments添加輸入路徑以及輸出路徑，記得把ip地址改為自己虛擬機的ip地址
6.運行程序
拷貝了一篇滿分英語作文在test.txt里，運行結果如下
每次運行時檢查hdfs上是否有output文件夾，如果有，請刪除output文件夾。
感謝我的基友月巴巴提供了莫大的幫助
