bugmakerrrrrr opened a new issue, #13185:
URL: https://github.com/apache/lucene/issues/13185
### Description
Currently, in the KNN retrieval process, we use
`VectorSimilarityFunction#compare` to calculate the score between the target
vector and the current vector. This method requires recalculating the norm of
the target vector each time. To avoid this repetition, we can pass the square
norm of the target vector to score method. I suggest modifying the relevant
interface as follows:
```
@functionalInterface
public interface ByteVectorScorer {
float score(byte[] vector);
}
@functionalInterface
public interface FloatVectorScorer {
float score(float[] vector);
}
public enum VectorSimilarityFunction {
EUCLIDEAN {
@Override
public ByteVectorScorer getVectorScorer(byte[] target) {
return vector -> 1 / (1f + squareDistance(target, vector));
}
@Override
public FloatVectorScorer getVectorScorer(float[] target) {
return vector -> 1 / (1 + squareDistance(target, vector));
}
},
COSINE {
@Override
public ByteVectorScorer getVectorScorer(byte[] target) {
int squareNorm = dotProduct(target, target);
return vector -> (1 + cosine(target, vector, squareNorm)) / 2;
}
@Override
public FloatVectorScorer getVectorScorer(float[] target) {
double squareNorm = dotProduct(target, target);
return vector -> Math.max((1 + cosine(target, vector,
squareNorm)) / 2, 0);
}
};
public abstract ByteVectorScorer getVectorScorer(byte[] target);
public abstract FloatVectorScorer getVectorScorer(float[] target);
}
```
Any thoughts？
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