【大数据系列】windows下连接Linux环境开发

一、配置文件

1.core-site.xml

<configuration>
<property>
<name>fs.defaultFS</name>
<value>hdfs://www.node1.com:9000</value>
</property>
</configuration>

2、hdfs-site.xml

<configuration>
<property>
<name>dfs.replication</name>
<value>2</value>
</property>
</configuration>

3、yarn-site.xml

<property>
<name>yarn.resourcemanager.hostname</name>
<value>www.node1.com</value>
</property>
<property>
<name>yarn.nodemanager.aux-services</name>
<value>mapreduce_shuffle</value>
</property>
</configuration>

4、slaves

www.node2.com
www.node3.com

二、建立本地连接

三、创建MapReduceProject

1、File -- new - Other --MapReduceProject

2、建立测试文件

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;
import org.apache.hadoop.util.GenericOptionsParser;

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();

String[] otherArgs = new GenericOptionsParser(conf, args).getRemainingArgs();
if (otherArgs.length != 2) {
System.err.println(otherArgs.length);
System.err.println("Usage: wordcount <in> <out>");
System.exit(2);
}
System.out.println(otherArgs[0]);
System.out.println(otherArgs[1]);
Job job = new Job(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(otherArgs[0]));
FileOutputFormat.setOutputPath(job, new Path(otherArgs[1]));
System.exit(job.waitForCompletion(true) ? 0 : 1);
}
}

3、run configuration

hdfs://www.node1.com:9000/usr/wc
hdfs://www.node1.com:9000/usr/wc/output

4、run

5、part-r-00000

apple    2
banana    1
cat    1
dog    1
hadoop    1
hadpp    1
hello    1
mapreduce    1
name    1
world    1
yarn    2

6、wc.txt

hadoop hello
hadpp world
apple dog
banana cat
mapreduce name
yarn
apple
yarn