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From "Streckfus, William [USA]" <streckfus_will...@bah.com>
Subject Grouping Values for Reducer Input
Date Mon, 13 Apr 2009 21:53:13 GMT
Hi Everyone,
 
I'm working on a relatively simple MapReduce job with a slight complication
with regards to the ordering of my key/values heading into the reducer. The
output from the mapper might be something like
 
cat -> doc5, 1
cat -> doc1, 1
cat -> doc5, 3
...
 
Here, 'cat' is my key and the value is the document ID and the count (my own
WritableComparable.) Originally I was going to create a HashMap in the
reduce method and add an entry for each document ID and sum the counts for
each. I realized the method would be better if the values were in order like
so:
 
cat -> doc1, 1
cat -> doc5, 1
cat -> doc5, 3
...
 
Using this style I can continue summing until I reach a new document ID and
just collect the output at this point thus avoiding data structures and
object creation costs. I tried setting
JobConf.setOutputValueGroupingComparator() but this didn't seem to do
anything. In fact, I threw an exception from the Comparator I supplied but
this never showed up when running the job. My map output value consists of a
UTF and a Long so perhaps the Comparator I'm using (identical to
Text.Comparator) is incorrect:
public int compare(byte[] b1, int s1, int l1, byte[] b2, int s2, int l2) {
    int n1 = WritableUtils.decodeVIntSize(b1[s1]);
    int n2 = WritableUtils.decodeVIntSize(b2[s2]);

    return compareBytes(b1, s1 + n1, l1 - n1, b2, s2 + n2, l2 - n2);
}

In my final output I'm basically running into the same word -> documentID
being output multiple times. So for the above example I have multiple lines
with cat -> doc5, X.
 
Reducer method just in case:
public void reduce(Text key, Iterator<TermFrequencyWritable> values,
OutputCollector<Text, TermFrequencyWritable> output, Reporter reporter)
throws IOException {
    long sum = 0;
    String lastDocID = null;

    // Iterate through all values
    while(values.hasNext()) {
        TermFrequencyWritable value = values.next();

        // Encountered new document ID = record and reset
        if(!value.getDocumentID().equals(lastDocID)) {
            // Ignore first go through
            if(sum != 0) {
                termFrequency.setDocumentID(lastDocID);
                termFrequency.setFrequency(sum);
                output.collect(key, termFrequency);
            }

            sum = 0;
            lastDocID = value.getDocumentID();
        }

        sum += value.getFrequency();
    }

    // Record last one
    termFrequency.setDocumentID(lastDocID);
    termFrequency.setFrequency(sum);
    output.collect(key, termFrequency);
}

 
Any ideas (Using Hadoop .19.1)?
 
Thanks,
- Bill

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