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Hadoop实现共同出现的单词(Word co-occurrence)(二)
2014-11-24 03:08:19 来源: 作者: 【 】 浏览:8
Tags:Hadoop 实现 共同 出现 单词 Word co-occurrence
super(TextPair.class);
}
@Override
public int compare(byte[] b1, int s1, int l1, byte[] b2, int s2, int l2){
try {
int firstl1 = WritableUtils.decodeVIntSize(b1[s1]) + readVInt(b1, s1);
int firstl2 = WritableUtils.decodeVIntSize(b2[s2]) + readVInt(b2, s2);
int cmp = TEXT_COMPARATOR.compare(b1, s1, firstl1, b2, s2, firstl2);
if(cmp != 0)
return cmp;
return TEXT_COMPARATOR.compare(b1, s1 + firstl1, l1 - firstl1,
b2, s2 + firstl2, l1 - firstl2);
}catch (IOException e) {
throw new IllegalArgumentException(e);
}
}
}//End of Comparator
static { // register this comparator
WritableComparator.define(TextPair.class, new Comparator());
}


// Compare only the first part of the pair, so that reduce is called once for each value of the first part.
public static class FirstComparator extends WritableComparator {
private static final Text.Comparator TEXT_COMPARATOR = new Text.Comparator();
public FirstComparator() {
super(TextPair.class);
}
@Override
public int compare(byte[] b1, int s1, int l1, byte[] b2, int s2, int l2){
try {
int firstl1 = WritableUtils.decodeVIntSize(b1[s1]) + readVInt(b1, s1);
int firstl2 = WritableUtils.decodeVIntSize(b2[s2]) + readVInt(b2, s2);
return TEXT_COMPARATOR.compare(b1, s1, firstl1, b2, s2, firstl2);
}catch (IOException e) {
throw new IllegalArgumentException(e);
}
}
/*
@Override
public int compare(WritableComparator a, WritableComparator b) {
if(a instanceof TextPair && b instanceof TextPair)
return ((TextPair)a).first.compareTo(((TextPair)b).first);
return super.compare(a, b);
}*/
}//End of FirstComparator
}//End of TextPair

//Partition based on the first part of the pair.
public static class FirstPartitioner extends Partitioner{
@Override
public int getPartition(TextPair key, IntWritable value, int numPartitions) {
return Math.abs(key.getFirst().toString().indexOf(0) * 127) % numPartitions;//May be some trouble here.
}
}//End of FirstPartitioner


public static class MyMapper extends Mapper {
private final static IntWritable one = new IntWritable(1);
private static Text word0 = new Text();
private static Text word1 = new Text();
private String pattern = "[^a-zA-Z0-9-']";


@Override
public void map(LongWritable inKey, Text inValue, Context context)throws IOException, InterruptedException {
String line = inValue.toString();
line = line.replaceAll(pattern, " ");
line = line.toLowerCase();
String[] str = line.split(" +");
for(int i=0; i< str.length-1; i++)
{
word0.set(str[i]);
word1.set(str[i+1]);
TextPair pair = new TextPair(word0, word1);
context.write(pair, one);
}
}
}//End of MapClass
public static class MyReducer extends Reducer {
private IntWritable result = new IntWritable();

@Override
public void reduce(TextPair inKey, Iterable inValues, Context context) throws IOException, InterruptedException {
int sum = 0;
for (IntWritable val : inValues) {
sum += val.get();
}
result.set(sum);
context.write(inKey, result);
}
}//End of MyReducer

public static void main(String[] args) throws Exception {
Configuration conf = new Configuration();
//conf.set("Hadoop.job.ugi", "sunguoli,cs402");
String[] otherArgs = new GenericOptionsParser(conf, args).getRemainingArgs();
//if (otherArgs.length !

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