源码见：https://github.com/hiszm/hadoop-train
HDFS项目实战
需求分析
使用HDFS Java API 才完成HDFS文件系统上的额文件的词频统计
例子/test/1.txt
==> ' hello world'
/test/2.txt
==> ' hello world world'
得出 hello 两个, world 三个
代码框架编写
- 1:读取HDFS上的文件
- 2:词频统计
- 3:将处理的结果混存起来 Map
- 4:将结果输出到HDFS
上下文
package com.bigdata.hadoop.hdfs;
import java.util.HashMap;
import java.util.Map;
//自定义上下文,缓存处理
public class Context {
private Map<Object,Object> cacheMap = new HashMap<Object, Object>();
public Map<Object,Object> getCacheMap (){
return cacheMap;
}
/**
* 写数据到缓存中
* @param key 单词
* @param value 次数
*/
public void write(Object key,Object value){
cacheMap.put(key,value);
}
/**
* 从缓存中获取数据
* @param key 单词
* @return 词频
*/
public Object get(Object key){
return cacheMap.get(key);
}
}
处理类实现
package com.bigdata.hadoop.hdfs;
public interface Mapper {
/**
* 自定义上下文
* @param line 读取到每一行数据
* @param context 上下文/缓存
*/
public void map(String line, Context context);
}package com.bigdata.hadoop.hdfs;
public class WordCount implements Mapper{
@Override
public void map(String line, Context context) {
String[] words = line.split("\t");
for(String word: words){
Object value = context.get(word);
if(value==null){//没有出现该单词
context.write(word,1);
}else{//已经有了,取出value再+1
int v =Integer.parseInt(value.toString());
context.write(word,v+1);
}
}
}
}功能实现
package com.bigdata.hadoop.hdfs;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.*;
import java.io.BufferedReader;
import java.io.File;
import java.io.InputStreamReader;
import java.net.URI;
import java.util.HashMap;
import java.util.Map;
import java.util.Set;
public class HDFSWCApp01 {
public static void main(String[] args) throws Exception{
//1:读取HDFS上的文件
Path input= new Path("/hdfsapi/local.txt");
FileSystem fs = FileSystem.get(new URI("hdfs://hadoop000:8020"),new Configuration(),"hadoop");
//?迭代器
RemoteIterator<LocatedFileStatus> iterator = fs.listFiles(input,false);
Mapper mapper =new WordCount();
//创建上下文
Context context= new Context();
while(iterator.hasNext()){
LocatedFileStatus file = iterator.next();
FSDataInputStream in = fs.open(file.getPath());
BufferedReader reader = new BufferedReader(new InputStreamReader(in));
String line="";
while ((line =reader.readLine())!=null){
//2:词频统计
//将业务逻辑处理完成后再返回給cache中
mapper.map(line,context);
}
reader.close();
in.close();
}
//3:将处理的结果混存起来 Map
Map<Object,Object> contextMap = context.getCacheMap();
//Map<Object,Object> contextMap = new HashMap<Object,Object>();
//4:将结果输出到HDFS
Path output =new Path("/hdfsapi/output/");
FSDataOutputStream out = fs.create(new Path(output,new Path("wc.out")));
Set<Map.Entry<Object,Object>> entries = contextMap.entrySet();
//迭代循环
for(Map.Entry<Object,Object> entry : entries){
out.write((entry.getKey().toString()+ "\t"+entry.getValue()+"\n").getBytes());
}
out.close();
fs.close();
System.out.println("统计完毕");
}
}
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com.bigdata.hadoop.hdfs.HDFSWCApp01
log4j:WARN No appenders could be found for logger (org.apache.hadoop.metrics2.lib.MutableMetricsFactory).
log4j:WARN Please initialize the log4j system properly.
log4j:WARN See http://logging.apache.org/log4j/1.2/faq.html#noconfig for more info.
统计完毕
Process finished with exit code 0hello world[hadoop@hadoop000 sbin]$ hadoop fs -text /hdfsapi/local.txt
hello world
hello hello
hello
world
[hadoop@hadoop000 sbin]$ hadoop fs -cat /hdfsapi/output/wc.out
1
world 2
hello 4