Java编写MapReduce程序
1、java开发map_reduce程序
2、配置系统环境变量HADOOP_HOME，指向hadoop安装目录（如
果你不想招惹不必要的麻烦，不要在目录中包含空格或者中文字符）把HADOOP_HOME/bin加到PATH环境变量（非必要，只是为了方便）
3、如果是在windows下开发，需要添加windows的库文件
1)把盘中共享的bin目录覆盖HADOOP_HOME/bin
2)如果还是不行，把其中的hadoop.dll复制到c:\windows\system32目录下，可能需要重启机器
4、建立新项目，引入hadoop需要的jar文件
代码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 {
7 @Override
8 protected void map(LongWritable key, Text value,
Mapper.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、代码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 {
7 @Override
8 protected void reduce(Text key, Iterable values,
9 Reducer.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、代码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中的文件拉到本地来运行
1 FileInputFormat.setInputPaths(job,"hdfs://master:9000/wcinput/");
2 FileOutputFormat.setOutputPath(job,new Path(
"hdfs://master:9000/wcoutput2/"));
注意这里是把hdfs文件拉到本地来运行，如果观察输出的话会观察到jobID带有local字样同时这样的运行方式是不需要yarn的(自己停掉yarn服务做实验)
9、在远程服务器执行
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/"));
如果遇到权限问题，配置执行时的虚拟机参DHADOOP_USER_NAME=root
10、也可以将hadoop的四个配置文件拿下来放到src根目录下，就不需要进行手工配置了，默认到classpath目录寻找
11、或者将配置文件放到别的地方，使用conf.addResource(.class.getClassLoader.getResourceAsStream)方式添加，不推荐使用绝对路径的方式
12、建立maven-hadoop项目：
1
2 4.0.0
3 mashibing.com
4 maven
5 0.0.1-SNAPSHOT
6 wc
7 hello mp
8
9 UTF-8 10 2.7.3
11
12
13
14 junit
15 junit
16 4.12
17
18
19 org.apache.hadoop
20 hadoop-client
21 ${hadoop.version}
22
23
24 org.apache.hadoop
25 hadoop-common
26 ${hadoop.version}
27
28
29 org.apache.hadoop
30 hadoop-hdfs
31 ${hadoop.version}
32
33
34
13、配置log4j.properties，放到src/main/resources目录下
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