Hadoop示例程序之单词统计MapReduce
在eclipse下新建一个map/reduce Project1,新建文件MyMap.java
import java.io.IOException;
import java.util.StringTokenizer;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;
public class MyMap extends Mapper<Object, Text, Text, IntWritable> {
private final static IntWritable one = new IntWritable(1);
private Text word;
public void map(Object key, Text value, Context context)
throws IOException, InterruptedException {
String line = value.toString();
StringTokenizer tokenizer = new StringTokenizer(line);
while (tokenizer.hasMoreTokens()) {
word = new Text();
word.set(tokenizer.nextToken());
context.write(word, one);
}
}
}
2，新建文件MyReduce.java:
import java.io.IOException;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Reducer;
public class MyReduce extends
Reducer<Text, IntWritable, Text, IntWritable> {
public void reduce(Text key, Iterable<IntWritable> values, Context context)
throws IOException, InterruptedException {
int sum = 0;
for (IntWritable val : values) {
sum += val.get();
}
context.write(key, new IntWritable(sum));
}
}
3，新建一个文件MyDriver.java
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.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.input.TextInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;
public class MyDriver {
public static void main(String[] args) throws Exception,InterruptedException {
Configuration conf=new Configuration();
Job job=new Job(conf,"Hello Hadoop World");
job.setJarByClass(MyDriver.class);
job.setMapOutputKeyClass(Text.class);
job.setMapOutputValueClass(IntWritable.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(IntWritable.class);
job.setMapperClass(MyMap.class);
job.setCombinerClass(MyReduce.class);
job.setReducerClass(MyReduce.class);
job.setInputFormatClass(TextInputFormat.class);
job.setOutputFormatClass(TextOutputFormat.class);
FileInputFormat.setInputPaths(job, new Path("./input/555.txt"));
FileOutputFormat.setOutputPath(job, new Path("./input/out.txt"));
job.waitForCompletion(true);
}
}
好了，见证奇迹的时刻到了，先在工程目录下创建一个目录input,并在下面新建文件555.txt,
Hello World 555 hahaha
Hello World
保存，运行java应用程序
在input下多了个文件目录:out.txt，该目录下有个文件part-r-0000文件，
打开后文件的内容是：
555 1
Hello 2
World 2
hahaha 1
算是搞定了。。。
运行中碰到包错：
org.apache.hadoop.fs.ChecksumException: Checksum error:
这个好办 只要将工程文件下的CRC数据校验文件删除就可以了
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