mapreduce编程（二）－ 大象书中求每一年的最高温度

转自：http://blog.csdn.net/heyutao007/article/details/5890165

书上的例子是为了取出一年当中气温最高的值，那么将年份和气温做了一个复合的key. 

1 通过设置了partitioner来进行分区。因为分区是按照年份来进行，所以同年的数据就可以分区到一个reducer中。

2 自定义key比较器，按照年份升序，温度值降序。这样map输出的所有kv对就是按照年份升序，温度值降序排列的。

3 自定义分组比较器，所有同一年的数据属于同一个组，那么在reduce输出的时候，只需要取第一个value就能达到输出一年最高气温的目的。 

代码：

 package temperature;
 import java.io.DataInput;
 import java.io.DataOutput;
 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.LongWritable;
 import org.apache.hadoop.io.NullWritable;
 import org.apache.hadoop.io.Text;
 import org.apache.hadoop.io.WritableComparable;
 import org.apache.hadoop.io.WritableComparator;
 import org.apache.hadoop.mapreduce.Job;
 import org.apache.hadoop.mapreduce.Mapper;
 import org.apache.hadoop.mapreduce.Partitioner;
 import org.apache.hadoop.mapreduce.Reducer;
 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 Temperature {
     // 自己定义的key类应该实现WritableComparable接口
     public static class IntPair implements WritableComparable {
         int first;
         int second;
         /**
          * Set the left and right values.
          */
         public void set(int left, int right) {
             first = left;
             second = right;
         }
         public int getFirst() {
             return first;
         }
         public int getSecond() {
             return second;
         }
         @Override
         // 反序列化
         public void readFields(DataInput in) throws IOException {
             // TODO Auto-generated method stub
             first = in.readInt();
             second = in.readInt();
         }
         @Override
         // 序列化
         public void write(DataOutput out) throws IOException {
             // TODO Auto-generated method stub
             out.writeInt(first);
             out.writeInt(second);
         }
         @Override
         // key的比较
         public int compareTo(IntPair o) {
             // TODO Auto-generated method stub
             if (first != o.first) {
                 return first < o.first ? -1 : 1;
             } else if (second != o.second) {
                 return second < o.second ? -1 : 1;
             } else {
                 return 0;
             }
         }
         // 新定义类应该重写的两个方法
         @Override
         public int hashCode() {
             return first * 157 + second;
         }
         @Override
         public boolean equals(Object right) {
             if (right == null)
                 return false;
             if (this == right)
                 return true;
             if (right instanceof IntPair) {
                 IntPair r = (IntPair) right;
                 return r.first == first && r.second == second;
             } else {
                 return false;
             }
         }
     }
     /**
      * 分区函数类。根据first确定Partition。
      */
     public static class FirstPartitioner extends
             Partitioner {
         @Override
         public int getPartition(IntPair key, NullWritable value,
                 int numPartitions) {
             return Math.abs(key.getFirst() * 127) % numPartitions;
         }
     }
     /**
      * key比较函数类。first升序，second降序。
      */
     public static class KeyComparator extends WritableComparator {
         protected KeyComparator() {
             super(IntPair.class, true);
         }
         @Override
         public int compare(WritableComparable w1, WritableComparable w2) {
             IntPair ip1 = (IntPair) w1;
             IntPair ip2 = (IntPair) w2;
             int l = ip1.getFirst();
             int r = ip2.getFirst();
             int cmp = (l == r ? 0 : (l < r ? -1 : 1));
             if (cmp != 0) {
                 return cmp;
             }
             l = ip1.getSecond();
             r = ip2.getSecond();
             return l == r ? 0 : (l < r ? 1 : -1); // reverse
         }
     }
     /**
      * 分组函数类。属于同一个组的value会放到同一个迭代器中，而比较是否是同一组需要使用GroupingComparator比较器。
      */
     // 第二种方法，继承WritableComparator
     public static class GroupingComparator extends WritableComparator {
         protected GroupingComparator() {
             super(IntPair.class, true);
         }
         @Override
         // Compare two WritableComparables.
         public int compare(WritableComparable w1, WritableComparable w2) {
             IntPair ip1 = (IntPair) w1;
             IntPair ip2 = (IntPair) w2;
             int l = ip1.getFirst();
             int r = ip2.getFirst();
             return l == r ? 0 : (l < r ? -1 : 1);
         }
     }
     // 自定义map
     public static class Map extends
             Mapper {
         private final IntPair intkey = new IntPair();
         public void map(LongWritable key, Text value, Context context)
                 throws IOException, InterruptedException {
             String line = value.toString();
             StringTokenizer tokenizer = new StringTokenizer(line);
             int left = 0;
             int right = 0;
             if (tokenizer.hasMoreTokens()) {
                 left = Integer.parseInt(tokenizer.nextToken());
                 if (tokenizer.hasMoreTokens())
                     right = Integer.parseInt(tokenizer.nextToken());
                 intkey.set(left, right);
                 context.write(intkey, NullWritable.get());
             }
         }
     }
     // 自定义reduce
     //
     public static class Reduce extends
             Reducer {
         private final IntWritable left = new IntWritable();
         private final IntWritable right = new IntWritable();
         public void reduce(IntPair key, Iterable values,
                 Context context) throws IOException, InterruptedException {
             left.set(key.getFirst());
             right.set(key.getSecond());
             context.write(left, right);
         }
     }
     /**
      * @param args
      */
     public static void main(String[] args) throws IOException,
             InterruptedException, ClassNotFoundException {
         // TODO Auto-generated method stub
         // 读取hadoop配置
         Configuration conf = new Configuration();
         // 实例化一道作业
         Job job = new Job(conf, "temperature");
         job.setJarByClass(Temperature.class);
         // Mapper类型
         job.setMapperClass(Map.class);
         // 不再需要Combiner类型，因为Combiner的输出类型
         // IntWritable>对Reduce的输入类型不适用
         // job.setCombinerClass(Reduce.class);
         // Reducer类型
         job.setReducerClass(Reduce.class);
         // 分区函数
         job.setPartitionerClass(FirstPartitioner.class);
         // key比较函数
         job.setSortComparatorClass(KeyComparator.class);
         // 分组函数
         job.setGroupingComparatorClass(GroupingComparator.class);
         // map 输出Key的类型
         job.setMapOutputKeyClass(IntPair.class);
         // map输出Value的类型
         job.setMapOutputValueClass(NullWritable.class);
         // rduce输出Key的类型，是Text，因为使用的OutputFormatClass是TextOutputFormat
         job.setOutputKeyClass(IntWritable.class);
         // rduce输出Value的类型
         job.setOutputValueClass(IntWritable.class);
         // 将输入的数据集分割成小数据块splites，同时提供一个RecordReder的实现。
         job.setInputFormatClass(TextInputFormat.class);
         // 提供一个RecordWriter的实现，负责数据输出。
         job.setOutputFormatClass(TextOutputFormat.class);
         // 输入hdfs路径
         FileInputFormat.setInputPaths(job, new Path(args[0]));
         // 输出hdfs路径
         FileOutputFormat.setOutputPath(job, new Path(args[1]));
         // 提交job
         System.exit(job.waitForCompletion(true) ? 0 : 1);
     }
 }