hadoop学习笔记

临摹了一个代码：

import java.io.IOException;?
import java.util.Iterator;?
import java.util.StringTokenizer;?
?
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.mapred.FileInputFormat;?
import org.apache.hadoop.mapred.FileOutputFormat;?
import org.apache.hadoop.mapred.JobClient;?
import org.apache.hadoop.mapred.JobConf;?
import org.apache.hadoop.mapred.MapReduceBase;?
import org.apache.hadoop.mapred.Mapper;?
import org.apache.hadoop.mapred.OutputCollector;?
import org.apache.hadoop.mapred.Reducer;?
import org.apache.hadoop.mapred.Reporter;?
import org.apache.hadoop.mapred.TextInputFormat;?
import org.apache.hadoop.mapred.TextOutputFormat;?
/**
*?
* 描述：WordCount explains by Felix
* @author Hadoop Dev Group
*/?
public class WordCount?
{?
?
??? /**
???? * MapReduceBase类:实现了Mapper和Reducer接口的基类（其中的方法只是实现接口，而未作任何事情）
???? * Mapper接口：
???? * WritableComparable接口：实现WritableComparable的类可以相互比较。所有被用作key的类应该实现此接口。
???? * Reporter 则可用于报告整个应用的运行进度，本例中未使用。?
???? *?
???? */?
??? public static class Map extends MapReduceBase implements?
??????????? Mapper<LongWritable, Text, Text, IntWritable>?
??? {?
??????? /**
???????? * LongWritable, IntWritable, Text 均是 Hadoop 中实现的用于封装 Java 数据类型的类，这些类实现了WritableComparable接口，
???????? * 都能够被串行化从而便于在分布式环境中进行数据交换，你可以将它们分别视为long,int,String 的替代品。
???????? */?
??????? private final static IntWritable one = new IntWritable(1);?
??????? private Text word = new Text();?
?????????
??????? /**
???????? * Mapper接口中的map方法：
???????? * void map(K1 key, V1 value, OutputCollector<K2,V2> output, Reporter reporter)
???????? * 映射一个单个的输入k/v对到一个中间的k/v对
???????? * 输出对不需要和输入对是相同的类型，输入对可以映射到0个或多个输出对。
???????? * OutputCollector接口：收集Mapper和Reducer输出的<k,v>对。
???????? * OutputCollector接口的collect(k, v)方法:增加一个(k,v)对到output 输出是map(k,list(v1,v2……))
???????? */?
??????? public void map(LongWritable key, Text value,?
??????????????? OutputCollector<Text, IntWritable> output, Reporter reporter)?
??????????????? throws IOException?
??????? {?
??????????? String line = value.toString();?
??????????? StringTokenizer tokenizer = new StringTokenizer(line);?
??????????? while (tokenizer.hasMoreTokens())?
??????????? {?
??????????????? word.set(tokenizer.nextToken());?
??????????????? output.collect(word, one);?
??????????? }?
??????? }?
??? }?
?
??? public static class Reduce extends MapReduceBase implements?
??????????? Reducer<Text, IntWritable, Text, IntWritable>?
??? {?
??????? public void reduce(Text key, Iterator<IntWritable> values,?
??????????????? OutputCollector<Text, IntWritable> output, Reporter reporter)?
??????????????? throws IOException?
??????? {?
??????????? int sum = 0;?
??????????? while (values.hasNext())?
??????????? {?
??????????????? sum += values.next().get();?
??????????? }?
??????????? output.collect(key, new IntWritable(sum));?
??????? }?
??? }?
?
??? public static void main(String[] args) throws Exception?
??? {?
??????? /**
???????? * JobConf：map/reduce的job配置类，向hadoop框架描述map-reduce执行的工作
???????? * 构造方法：JobConf()、JobConf(Class exampleClass)、JobConf(Configuration conf)等
???????? */?
??????? JobConf conf = new JobConf(WordCount.class);?
??????? conf.setJobName("wordcount");?????????? //设置一个用户定义的job名称?
?
??????? conf.setOutputKeyClass(Text.class);??? //为job的输出数据设置Key类?
??????? conf.setOutputValueClass(IntWritable.class);?? //为job输出设置value类?
?
??????? conf.setMapperClass(Map.class);???????? //为job设置Mapper类?
??????? conf.setCombinerClass(Reduce.class);????? //为job设置Combiner类?
??????? conf.setReducerClass(Reduce.class);??????? //为job设置Reduce类?
?
??????? conf.setInputFormat(TextInputFormat.class);??? //为map-reduce任务设置InputFormat实现类?
??????? conf.setOutputFormat(TextOutputFormat.class);? //为map-reduce任务设置OutputFormat实现类?
?
??????? /**
???????? * InputFormat描述map-reduce中对job的输入定义
???????? * setInputPaths():为map-reduce job设置路径数组作为输入列表
???????? * setInputPath()：为map-reduce job设置路径数组作为输出列表
???????? */?
??????? FileInputFormat.setInputPaths(conf, new Path(args[0]));?
??????? FileOutputFormat.setOutputPath(conf, new Path(args[1]));?
?
??????? JobClient.runJob(conf);???????? //运行一个job?
??? }?
}?

把相应的jar包放在eclipse里了，然后把源代码和jar文件达成个jar包，放在hadoop服务器上。编写word.txt文件放在特定目录中 我放在了bin下。

运行 ./hadoop jar /opt/gy.jar hadoop.WordCount word.txt? out?

统计完的文件在out下。定时的话采用crontab定时