SecondarySort代码的注释
package org.apache.hadoop.examples; 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.RawComparator; import org.apache.hadoop.io.Text; import org.apache.hadoop.io.WritableComparable; import org.apache.hadoop.io.WritableComparator; import org.apache.hadoop.mapreduce.lib.input.FileInputFormat; import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat; 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.util.GenericOptionsParser; /** * hadoop的map/reduce自带的例子代码，目的是演示二次排序， * 输入是文本文件，文本的每行是两个用空格分隔的整数，程序的输出结果是 * 按前一个整数排序，然后按后一个整数排序。应用场景是：数据join的reduce * 端的算法。 * * To run: bin/hadoop jar build/hadoop-examples.jar secondarysort * in-dir out-dir */ public class SecondarySort { /** * 自定义map的输出key类型，而不是默认的Text类型，他必须实现接口comparable ，作用是输出中对key自定义排序（倒序），实现中必须提供数据的读写方法（readFields，write）。等于（equals）和比较方法（compareTo）。 * */ public static class IntPair implements WritableComparable { private int first = 0; private int second = 0; /** * 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; } /** * 按编码读两个整数，编码是：读第一个整数+ Integer.MIN_VALUE+读第二个整数 + Integer.MIN_VALUE * Encoded as: MIN_VALUE -> 0, 0 -> -MIN_VALUE, MAX_VALUE-> -1 */ @Override public void readFields(DataInput in) throws IOException { first = in.readInt() + Integer.MIN_VALUE; second = in.readInt() + Integer.MIN_VALUE; } /*按编码写两个整数。编码是：写第一个整数-Integer.MIN_VALUE +写第二个整数 - Integer.MIN_VALUE */ @Override public void write(DataOutput out) throws IOException { out.writeInt(first - Integer.MIN_VALUE); out.writeInt(second - Integer.MIN_VALUE); } /*哈希方法，估计用于对象比较 */ @Override public int hashCode() { return first * 157 + second; } /*等于方法，和compareTo方法用于排序，而且两者必须一致，不然，排序的结果可能不对。 */ @Override public boolean equals(Object right) { if (right instanceof IntPair) { IntPair r = (IntPair) right; return r.first == first && r.second == second; } else { return false; } } /** 内置的静态类，用于对象的排序比较。如果没有这个类，排序的话 用 IntPair类自身的等于和比较函数来排序*/ public static class Comparator extends WritableComparator { public Comparator() { super(IntPair.class); } /*排序方法，b1第一个对象的字节数组第一个元素，s1首个字节的长度， l1整个字节数组的长度， b2第二个对象的字节数组第一个元素，s2首个字节的长度， l2整个字节数组的长度， */ public int compare(byte[] b1, int s1, int l1, byte[] b2, int s2, int l2) { return compareBytes(b1, s1, l1, b2, s2, l2);//比较对象的字节数组，遇到第一个不同立即返回 } } static { // 登记比较器comparator，对象 IntPair按比较器的定义排序 WritableComparator.define(IntPair.class, new Comparator()); } /*对象的比较方法 */ @Override public int compareTo(IntPair o) { if (first != o.first) { return first < o.first ? -1 : 1; } else if (second != o.second) { return second < o.second ? -1 : 1; } else { return 0; } } } /** * pair对象的Partitioner方法。默认是hashpartition方法。 目的是按前一个整数（firest）来决定让那个reducer来处理 */ public static class FirstPartitioner extends Partitioner{ @Override public int getPartition(IntPair key, IntWritable value, int numPartitions) { return Math.abs(key.getFirst() * 127) % numPartitions; } } /** * reducer的输出按第一个整数来输出，自定义的比较器 */ public static class FirstGroupingComparator implements RawComparator { /*比较字节数组，注释掉该函数会报错 */ @Override public int compare(byte[] b1, int s1, int l1, byte[] b2, int s2, int l2) { return WritableComparator.compareBytes(b1, s1, Integer.SIZE/8, b2, s2, Integer.SIZE/8); } /*作用不明，注释掉改函数，不会报错。 */ @Override public int compare(IntPair o1, IntPair o2) { int l = o1.getFirst(); int r = o2.getFirst(); return l == r ? 0 : (l < r ? -1 : 1); } }/**mapper类，输出的key是自定义的IntPair * Read two integers from each line and generate a key, value pair * as ((left, right), right). */ public static class MapClass extends Mapper { private final IntPair key = new IntPair(); private final IntWritable value = new IntWritable(); @Override public void map(LongWritable inKey, Text inValue, Context context) throws IOException, InterruptedException { StringTokenizer itr = new StringTokenizer(inValue.toString()); int left = 0; int right = 0; if (itr.hasMoreTokens()) { left = Integer.parseInt(itr.nextToken()); if (itr.hasMoreTokens()) { right = Integer.parseInt(itr.nextToken()); } key.set(left, right); value.set(right); context.write(key, value); } } } /**reducer类 * A reducer class that just emits the sum of the input values. */ public static class Reduce extends Reducer { private static final Text SEPARATOR = new Text("------------------------------------------------"); private final Text first = new Text(); @Override public void reduce(IntPair key, Iterable values, Context context ) throws IOException, InterruptedException { context.write(SEPARATOR, null); first.set(Integer.toString(key.getFirst())); for(IntWritable value: values) { context.write(first, value); } } } public static void main(String[] args) throws Exception { Configuration conf = new Configuration(); String[] otherArgs = new GenericOptionsParser(conf, args).getRemainingArgs(); if (otherArgs.length != 2) { System.err.println("Usage: secondarysrot "); System.exit(2); } Job job = new Job(conf, "secondary sort");//生成job对象 job.setJarByClass(SecondarySort.class);//指定jar包的名字 job.setMapperClass(MapClass.class);//设置mapper类 job.setReducerClass(Reduce.class);//设置reducer类 // group and partition by the first int in the pair job.setPartitionerClass(FirstPartitioner.class);//设置自定义的partition类 job.setGroupingComparatorClass(FirstGroupingComparator.class); //设置分组比较器。（按前一个整数来输出） // the map output is IntPair, IntWritable job.setMapOutputKeyClass(IntPair.class);//设置mapper输出的key类型 job.setMapOutputValueClass(IntWritable.class);//设置mapper输出的value类型 // the reduce output is Text, IntWritable job.setOutputKeyClass(Text.class); //设置reducer输出的key的类型 job.setOutputValueClass(IntWritable.class);//设置reuducer输出的value的类型 FileInputFormat.addInputPath(job, new Path(otherArgs[0]));//设置输入路径 FileOutputFormat.setOutputPath(job, new Path(otherArgs[1]));//设置输出路径 System.exit(job.waitForCompletion(true) ? 0 : 1); } } ?