hadoop自定义类型
hadoop为用户提供了自定义类型的接口，对于key，需要重写实现WritableComparable，而对于value，只需重写实现Writable即可。但是在作为reduce的输出的时，输出格式为TextOutputFormat时，不能正常显示。还需要自定义OutputFormat。
常用的几个函数：
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private double []values = null;public VectorWritable(){}public VectorWritable(double []a){this.values =a;}public double get(int index){return this.values[index];}public int getLen(){return this.values.length;}public void set(double []a){this.values = a;}?
?需要重写的几个函数：
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@Overridepublic void readFields(DataInput arg0) throws IOException {// TODO Auto-generated method stubthis.values = new double[arg0.readInt()];for(int i=0;i<this.values.length;i++){double tmp = arg0.readDouble();this.values[i] = tmp;}}@Overridepublic void write(DataOutput arg0) throws IOException {// TODO Auto-generated method stubarg0.writeInt(this.values.length);for(int i=0;i<this.values.length;i++){arg0.writeDouble(this.values[i]);}}?
?其实就是序列化和反序列化的需要重写
Map：
public static class TestMap extends Mapper<Object,Text,Text,VectorWritable>{private static Text outputkey = new Text("1");private static VectorWritable Vector = new VectorWritable();public void map(Object key, Text rawLine, Context context)throws IOException, InterruptedException{String []parts = rawLine.toString().trim().split(",");int len = parts.length;double []tmp = new double[len];for(int i=0;i<len;i++){ tmp[i] = Double.valueOf(parts[i]);}Vector.set(tmp);context.write(outputkey, Vector);}}??Reduce：
public static class TestReduceextends Reducer<Object,VectorWritable,Text,DoubleWritable>{private static Text outputkey = new Text("1");private static DoubleWritable output = new DoubleWritable();public void reduce(Object key,Iterable<VectorWritable>value,Context context)throws IOException, InterruptedException{for(VectorWritable vm : value){int len = vm.getLen();for(int i=0;i<len;i++){double x = vm.get(i);//System.out.println(x);output.set(x);context.write(outputkey, output);}}}}??
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