Module org.elasticsearch.simdvec

Package org.elasticsearch.simdvec.internal.vectorization

Class MemorySegmentES91OSQVectorsScorer

java.lang.Object

org.elasticsearch.simdvec.ES91OSQVectorsScorer

org.elasticsearch.simdvec.internal.vectorization.MemorySegmentES91OSQVectorsScorer

public final class MemorySegmentES91OSQVectorsScorer
extends ES91OSQVectorsScorer

Panamized scorer for quantized vectors stored as a MemorySegment^PREVIEW.

Field Summary

Fields inherited from class org.elasticsearch.simdvec.ES91OSQVectorsScorer

additionalCorrections, bulkSize, dimensions, FOUR_BIT_SCALE, in, length, lowerIntervals, targetComponentSums, upperIntervals

Constructor Summary

Constructors

Constructor	Description
MemorySegmentES91OSQVectorsScorer(org.apache.lucene.store.IndexInput in, int dimensions, int bulkSize)

Method Summary

Modifier and Type	Method	Description
long	quantizeScore(byte[] q)	compute the quantize distance between the provided quantized query and the quantized vector that is read from the wrapped IndexInput.
void	quantizeScoreBulk(byte[] q, int count, float[] scores)	compute the quantize distance between the provided quantized query and the quantized vectors that are read from the wrapped IndexInput.
float	scoreBulk(byte[] q, float queryLowerInterval, float queryUpperInterval, int queryComponentSum, float queryAdditionalCorrection, org.apache.lucene.index.VectorSimilarityFunction similarityFunction, float centroidDp, float[] scores)	compute the distance between the provided quantized query and the quantized vectors that are read from the wrapped IndexInput.

Methods inherited from class org.elasticsearch.simdvec.ES91OSQVectorsScorer

score

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Details

MemorySegmentES91OSQVectorsScorer

public MemorySegmentES91OSQVectorsScorer(org.apache.lucene.store.IndexInput in,
 int dimensions,
 int bulkSize)

Method Details

quantizeScore

public long quantizeScore(byte[] q)
                   throws IOException

Description copied from class: ES91OSQVectorsScorer

compute the quantize distance between the provided quantized query and the quantized vector that is read from the wrapped IndexInput.

Overrides:

quantizeScore in class ES91OSQVectorsScorer

Throws:

IOException

quantizeScoreBulk

public void quantizeScoreBulk(byte[] q,
 int count,
 float[] scores)
                       throws IOException

Description copied from class: ES91OSQVectorsScorer

compute the quantize distance between the provided quantized query and the quantized vectors that are read from the wrapped IndexInput. The number of quantized vectors to read is determined by {code count} and the results are stored in the provided scores array.

Overrides:

quantizeScoreBulk in class ES91OSQVectorsScorer

Throws:

IOException

scoreBulk

public float scoreBulk(byte[] q,
 float queryLowerInterval,
 float queryUpperInterval,
 int queryComponentSum,
 float queryAdditionalCorrection,
 org.apache.lucene.index.VectorSimilarityFunction similarityFunction,
 float centroidDp,
 float[] scores)
                throws IOException

Description copied from class: ES91OSQVectorsScorer

compute the distance between the provided quantized query and the quantized vectors that are read from the wrapped IndexInput.

The number of vectors to score is defined by ES91OSQVectorsScorer.bulkSize. The expected format of the input is as follows: First the quantized vectors are read from the input,then all the lower intervals as floats, then all the upper intervals as floats, then all the target component sums as shorts, and finally all the additional corrections as floats.

The results are stored in the provided scores array.

Overrides:

scoreBulk in class ES91OSQVectorsScorer

Throws:

IOException