package org.apache.hadoop.mapreduce.io; import java.io.DataInput;
import java.io.DataOutput;
import java.io.IOException; import org.apache.hadoop.io.WritableComparable; /***
* customize writable eg.order
*
* @author nele
*
*/
public class OrderWritable implements WritableComparable<OrderWritable> { private String orderId; private float price; public OrderWritable() {
} public OrderWritable(String orderId, float price) {
set(orderId, price);
} public void set(String orderId, float price) {
this.orderId = orderId;
this.price = price;
} public String getOrderId() {
return orderId;
} public void setOrderId(String orderId) {
this.orderId = orderId;
} public float getPrice() {
return price;
} public void setPrice(float price) {
this.price = price;
} public void write(DataOutput out) throws IOException {
out.writeUTF(orderId);
out.writeFloat(price);
} public void readFields(DataInput in) throws IOException {
this.orderId = in.readUTF();
this.price = in.readFloat();
} public int compareTo(OrderWritable o) {
int comp = this.orderId.compareTo(o.orderId);
if (comp == 0) {
return Float.valueOf(this.price).compareTo(Float.valueOf(o.price));
}
return comp;
} @Override
public String toString() {
return orderId + "\t" + price;
} @Override
public int hashCode() {
final int prime = 31;
int result = 1;
result = prime * result + ((orderId == null) ? 0 : orderId.hashCode());
result = prime * result + Float.floatToIntBits(price);
return result;
} @Override
public boolean equals(Object obj) {
if (this == obj)
return true;
if (obj == null)
return false;
if (getClass() != obj.getClass())
return false;
OrderWritable other = (OrderWritable) obj;
if (orderId == null) {
if (other.orderId != null)
return false;
} else if (!orderId.equals(other.orderId))
return false;
if (Float.floatToIntBits(price) != Float.floatToIntBits(other.price))
return false;
return true;
} }
这样就可以,在mapreduce中使用。
需要根据具体的情境具体的设计。