Hadoop之个性化键类型

前面我们的Piont3D类型能够作为一个值来满足mapper的使用。但是如果我们也想用Point3D对象作为键呢？在Hadoop的MR中，如果向一个reduce任务分发不同的（key, value）对，reducer将有序地对键进行处理。所以键的类型必须实现一个更加严格的接口，WritableComparable。除了它是一个Writable，可以被在网络传输之外，它们也遵循Java的Comparable接口。下面的代码扩展了Piont3D来满足这个接口的要求：

public class Point3D implements WritableComparable{

public float x;

public float y;

public float z;

public Point3D(float x, float y, float z){

this.x = x;

this.y = y;

this.z = z;

}

public Point3D(){

this(0.0f, 0.0f, 0.0f);

}

public void readFields(DataInput in) throws IOException{

x = in.readFloat();

y = in.readFloat();

z = in.readFload();

}

public String toString(){

return Float.toString(x) + "," + Float.toString(y) + "," + Float.toString(z);

}

/* 返回从到原点的欧氏距离 */

public float distanceFromOrigin(){

return (float)Math.sqrt(x*x + y*y + z*z);

}

public int compareTo(Point3D other){

float myDistance = distanceFromOrigin();

float otherDistance = other.distanceFromOrign();

return Float.compare(myDistance, otherDistance);

}

public boolean equals(Object o){

if(!(other instanceof Point3D)){

return false;

}

Point3D other = (Point3D)o;

return this.x == other.x && this.y == other.y && this.z == other.z;

}

public int hashCode(){

return Float.floatToIntBits(x) ^Float.floatToIntBits(y)^Float.floatToIntBits(z);

}

}

实现hashCode()对于key类型来说是重要的；在Partitioner部分中将说明原因。hashCode()和equals()在这个版本中也一并提供了。