Java編寫MapReduce程序

1、java開發(fā)map_reduce程序
2、配置系統(tǒng)環(huán)境變量HADOOP_HOME，指向hadoop安裝目錄（如
果你不想招惹不必要的麻煩，不要在目錄中包含空格或者中文字符）把HADOOP_HOME/bin加到PATH環(huán)境變量（非必要，只是為了方便）
3、如果是在windows下開發(fā)，需要添加windows的庫文件
1)把盤中共享的bin目錄覆蓋HADOOP_HOME/bin
2)如果還是不行，把其中的hadoop.dll復(fù)制到c:\windows\system32目錄下，可能需要重啟機(jī)器

4、建立新項(xiàng)目，引入hadoop需要的jar文件
代碼WordMapper：

1 import java.io.IOException;
2 import org.apache.hadoop.io.IntWritable;
3 import org.apache.hadoop.io.LongWritable;
4 import org.apache.hadoop.io.Text;
5 import org.apache.hadoop.mapreduce.Mapper;
6 public class WordMapper extends Mapper<LongWritable,Text, 
  Text, IntWritable> {
7 @Override
8 protected void map(LongWritable key, Text value, 
  Mapper<LongWritable, Text, Text, IntWritable>.Context context)
9 throws IOException, InterruptedException {
10 String line = value.toString();
11 String[] words = line.split(" ");
12 for(String word : words) {
13 context.write(new Text(word),new IntWritable(1));
14 }
15 }
16 }

6、代碼WordReducer：

1 import java.io.IOException;
2 import org.apache.hadoop.io.IntWritable;
3 import org.apache.hadoop.io.LongWritable;
4 import org.apache.hadoop.io.Text;
5 import org.apache.hadoop.mapreduce.Reducer;
6 publicclassWordReducerextendsReducer<Text, IntWritable, Text, LongWritable> {
7 @Override
8 protected void reduce(Text key, Iterable<IntWritable> values,
9 Reducer<Text, IntWritable, Text, LongWritable>.Context context)
  throws IOException, InterruptedException {
10 long count = 0 ;
11 for(IntWritable v : values) {
12 count += v.get();
13  }
14  context.write(key,newLongWritable(count));
15  }

16  }

7、代碼Test：

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.lib.input.FileInputFormat;

import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;

  public class Test {
  public static void main(String[] args) throws Exception {
  Configuration conf = new Configuration();    
  Job job = Job.getInstance(conf);       
  job.setMapperClass(WordMapper.class);
  job.setReducerClass(WordReducer.class);
  job.setMapOutputKeyClass(Text.class);     
  job.setMapOutputValueClass(IntWritable.class);       
  job.setOutputKeyClass(Text.class);       
 job.setOutputValueClass(LongWritable.class);        
FileInputFormat.setInputPaths(job,"c:/bigdata/hadoop/test/test.txt"); FileOutputFormat.setOutputPath(job,newPath("c:/bigdata/hadoop/test/out/"));        
job.waitForCompletion(true);    
}
}

8、把hdfs中的文件拉到本地來運(yùn)行

1 FileInputFormat.setInputPaths(job,"hdfs://master:9000/wcinput/");
2 FileOutputFormat.setOutputPath(job,new Path(
  "hdfs://master:9000/wcoutput2/"));

注意這里是把hdfs文件拉到本地來運(yùn)行，如果觀察輸出的話會(huì)觀察到j(luò)obID帶有l(wèi)ocal字樣同時(shí)這樣的運(yùn)行方式是不需要yarn的(自己停掉yarn服務(wù)做實(shí)驗(yàn))
9、在遠(yuǎn)程服務(wù)器執(zhí)行

1 conf.set("fs.defaultFS","hdfs://master:9000/");
2 conf.set("mapreduce.job.jar","target/wc.jar");
3 conf.set("mapreduce.framework.name","yarn");
4 conf.set("yarn.resourcemanager.hostname","master");
5 conf.set("mapreduce.app-submission.cross-platform","true");
6 FileInputFormat.setInputPaths(job, "/wcinput/");
7 FileOutputFormat.setOutputPath(job, new Path("/wcoutput3/"));

如果遇到權(quán)限問題，配置執(zhí)行時(shí)的虛擬機(jī)參DHADOOP_USER_NAME=root
10、也可以將hadoop的四個(gè)配置文件拿下來放到src根目錄下，就不需要進(jìn)行手工配置了，默認(rèn)到classpath目錄尋找
11、或者將配置文件放到別的地方，使用conf.addResource(.class.getClassLoader.getResourceAsStream)方式添加，不推薦使用絕對路徑的方式
12、建立maven-hadoop項(xiàng)目：

1<projectxmlns="http://maven.apache.org/POM/4.0.0"xmlns:xsi
  ="http://www.w3.org/2001/XMLSchema-
 instance)"xsi:schemalocation="http://maven.apache.org/POM/4.0.0 
 http://maven.apache.org/xsd/maven-4.0.0.xsd">
2 <modelversion>4.0.0</modelversion>
3 <groupid>mashibing.com</groupid>
4 <artifactid>maven</artifactid>
5 <version>0.0.1-SNAPSHOT</version>
6 <name>wc</name>
7 <description>hello mp</description>
8 <properties>
9 <project.build.sourceencoding>UTF-8</project.build.sourceencoding>10 <hadoop.version>2.7.3</hadoop.version>
11 </properties>
12 <dependencies>
13 <dependency>
14  <groupId>junit</groupId>
15 <artifactId>junit</artifactId>
16  <version>4.12</version>
17 </dependency>
18 <dependency>
19 <groupId>org.apache.hadoop</groupId>
20 <artifactId>hadoop-client</artifactId>
21 <version>${hadoop.version}</version>
22 </dependency>
23 <dependency>
24 <groupId>org.apache.hadoop</groupId>
25 <artifactId>hadoop-common</artifactId>
26 <version>${hadoop.version}</version>
27 </dependency>
28 <dependency>
29 <groupId>org.apache.hadoop</groupId>
30 <artifactId>hadoop-hdfs</artifactId>
31 <version>${hadoop.version}</version>
32 </dependency>
33 </dependencies>
34 </project>

13、配置log4j.properties，放到src/main/resources目錄下

1 log4j.rootCategory=INFO, stdout
2 log4j.appender.stdout=org.apache.log4j.ConsoleAppender  
3 log4j.appender.stdout.layout=org.apache.log4j.PatternLayout  
4 log4j.appender.stdout.layout.ConversionPattern=[QC] %p [%t] 
  %C.%M(%L) | %m%n