Performance of RowSimilarityJob is not good
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Key: MAHOUT-468
URL: https://issues.apache.org/jira/browse/MAHOUT-468
Project: Mahout
Issue Type: Test
Components: Collaborative Filtering
Affects Versions: 0.4
Reporter: Hui Wen Han
Fix For: 0.4
I have done a test ,
Preferences records: 680,194
distinct users: 23,246
distinct items:437,569
SIMILARITY_CLASS_NAME=SIMILARITY_COOCCURRENCE
maybePruneItemUserMatrixPath:16.50M
weights:13.80M
pairwiseSimilarity:18.81G
Job RowSimilarityJob-RowWeightMapper-WeightedOccurrencesPerColumnReducer:used
32 sec
Job RowSimilarityJob-CooccurrencesMapper-SimilarityReducer:used 4.30 hours
I think the reason may be following:
1) We used SequenceFileOutputFormat,it cause job can only be run by n ( n=
Hadoop node counts ) mappers or reducers concurrently.
2) We stored redundant info.
for example :
the output of CooccurrencesMapper:
(ItemIndexA,similarity),(ItemIndexA,ItemIndexB,similarity)
3) Some frequently used code
https://issues.apache.org/jira/browse/MAHOUT-467
4) allocate many local variable in loop (need confirm )
In Class DistributedUncenteredZeroAssumingCosineVectorSimilarity
@Override
public double weight(Vector v) {
double length = 0.0;
Iterator<Element> elemIterator = v.iterateNonZero();
while (elemIterator.hasNext()) {
double value = elemIterator.next().get(); //this one
length += value * value;
}
return Math.sqrt(length);
}
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