Creates a new copy of this KnnVectorValues. This is helpful when you need to access different values at once, to avoid overwriting the underlying vector returned.

dimension

open override fun dimension(): Int

Return the dimension of the vectors

discretizedDimensions

fun discretizedDimensions(): Int

getAcceptOrds

open fun getAcceptOrds(acceptDocs: Bits?): Bits?

Returns a Bits accepting docs accepted by the argument and having a vector value

getCorrectiveTerms

open override fun getCorrectiveTerms(targetOrd: Int): OptimizedScalarQuantizer.QuantizationResult

Retrieve the corrective terms for the given vector ordinal. For the dot-product family of distances, the corrective terms are, in order

iterator

open fun iterator(): KnnVectorValues.DocIndexIterator

Create an iterator for this instance.

ordToDoc

open fun ordToDoc(ord: Int): Int

Return the docid of the document indexed with the given vector ordinal. This default implementation returns the argument and is appropriate for dense values implementations where every doc has a single value.

scorer

abstract fun scorer(query: FloatArray): VectorScorer?

open fun scorer(query: ByteArray): VectorScorer?

Return a VectorScorer for the given query vector.

size

open override fun size(): Int

Return the number of vectors for this field.

vectorValue

open override fun vectorValue(targetOrd: Int): ByteArray

Return the vector value for the given vector ordinal which must be in 0, size() - 1, otherwise IndexOutOfBoundsException is thrown. The returned array may be shared across calls.