kNN Query

The kNN query finds the k nearest vectors to a query vector, as measured by a similarity metric. It is used for performing k-nearest neighbor (kNN) search on fields of type dense_vector.

Note that the kNN query can't be used as a regular query (e.g. in a Search request or within a Bool query); it can only be executed using the kNN Search request.

In order to use the kNN query import the following:

import zio.Chunk
import zio.elasticsearch.query.KNNQuery
import zio.elasticsearch.ElasticQuery._

You can create a kNN query using the kNN method this way:

val query: KNNQuery[Any] = kNN(field = "vectorField", k = 2, numCandidates = 5, queryVector = Chunk(1.0, 2.0, 3.0))

You can create a type-safe kNN query using the kNN method this way:

val query: KNNQuery[Document] = kNN(field = Document.vectorField, k = 2, numCandidates = 5, queryVector = Chunk(1.0, 2.0, 3.0))

Parameter k represents the number of nearest neighbors to return as top hits, while numCandidates represents the number of nearest neighbor candidates to consider per shard. Parameter k must be less than or equal to numCandidates.

If you want to change the similarity, you can use similarity method:

val queryWithSimilarity: KNNQuery[Document] =
  kNN(field = Document.vectorField, k = 2, numCandidates = 5, queryVector = Chunk(1.0, 2.0, 3.0)).similarity(3.0)

You can find more information about kNN query here.