package wordcount;
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>{ //继承泛型类Mapper
private final static IntWritable one = new IntWritable(1); //定义hadoop数据类型IntWritable实例one，并且赋值为1
private Text word = new Text(); //定义hadoop数据类型Text实例word
public void map(Object key, Text value, Context context) throws IOException, InterruptedException { //实现map函数
StringTokenizer itr = new StringTokenizer(value.toString());//Java的字符串分解类，默认分隔符“空格”、“制表符(‘\t’)”、“换行符(‘\n’)”、“回车符(‘\r’)”
while (itr.hasMoreTokens()) { //循环条件表示返回是否还有分隔符。
word.set(itr.nextToken()); // nextToken()：返回从当前位置到下一个分隔符的字符串，word.set()：Java数据类型与hadoop数据类型转换
context.write(word, one); //hadoop全局类context输出函数write;
}
}
}
public static class IntSumReducer extends Reducer<Text,IntWritable,Text,IntWritable> { //继承泛型类Reducer
private IntWritable result = new IntWritable(); //实例化IntWritable
public void reduce(Text key, Iterable<IntWritable> values, Context context ) throws IOException, InterruptedException { //实现reduce
int sum = 0;
for (IntWritable val : values) //循环values，并记录单词个数
sum += val.get();
result.set(sum); //Java数据类型sum，转换为hadoop数据类型result
context.write(key, result); //输出结果到hdfs
}
}
public static void main(String[] args) throws Exception {
Configuration conf = new Configuration(); //实例化Configuration
/***********
GenericOptionsParser是hadoop框架中解析命令行参数的基本类。 getRemainingArgs();返回数组【一组路径】
*********/
/**********
函数实现
public String[] getRemainingArgs() {
return (commandLine == null) ? new String[]{} : commandLine.getArgs();
}
/********
//总结上面：返回数组【一组路径】
String[] otherArgs = new GenericOptionsParser(conf, args).getRemainingArgs();
//如果只有一个路径，则输出需要有输入路径和输出路径
if (otherArgs.length < 2) {
System.err.println("Usage: wordcount <in> [<in>...] <out>");
System.exit(2);
}
Job job = Job.getInstance(conf, "word count"); //实例化job
job.setJarByClass(wordcount.class); //为了能够找到wordcount这个类
job.setMapperClass(TokenizerMapper.class); //指定map类型
/********
指定CombinerClass类
这里很多人对CombinerClass不理解
************/
job.setCombinerClass(IntSumReducer.class);
job.setReducerClass(IntSumReducer.class); //指定reduce类
job.setOutputKeyClass(Text.class); //rduce输出Key的类型，是Text
job.setOutputValueClass(IntWritable.class); // rduce输出Value的类型
for (int i = 0; i < otherArgs.length - 1; ++i)
FileInputFormat.addInputPath(job, new Path(otherArgs)); //添加输入路径
FileOutputFormat.setOutputPath(job, new Path(otherArgs[otherArgs.length - 1])); //添加输出路径
System.exit(job.waitForCompletion(true) ? 0 : 1); //提交job
}
}