Class PerFieldKnnVectorsFormat.FieldsReader

    • Constructor Detail

      • FieldsReader

        public FieldsReader​(SegmentReadState readState)
                     throws IOException
        Create a FieldsReader over a segment, opening VectorReaders for each KnnVectorsFormat specified by the indexed numeric vector fields.
        Parameters:
        readState - defines the fields
        Throws:
        IOException - if one of the delegate readers throws
    • Method Detail

      • getFieldReader

        public KnnVectorsReader getFieldReader​(String field)
        Return the underlying VectorReader for the given field
        Parameters:
        field - the name of a numeric vector field
      • checkIntegrity

        public void checkIntegrity()
                            throws IOException
        Description copied from class: KnnVectorsReader
        Checks consistency of this reader.

        Note that this may be costly in terms of I/O, e.g. may involve computing a checksum value against large data files.

        Specified by:
        checkIntegrity in class KnnVectorsReader
        Throws:
        IOException
      • search

        public TopDocs search​(String field,
                              float[] target,
                              int k,
                              Bits acceptDocs,
                              int visitedLimit)
                       throws IOException
        Description copied from class: KnnVectorsReader
        Return the k nearest neighbor documents as determined by comparison of their vector values for this field, to the given vector, by the field's similarity function. The score of each document is derived from the vector similarity in a way that ensures scores are positive and that a larger score corresponds to a higher ranking.

        The search is allowed to be approximate, meaning the results are not guaranteed to be the true k closest neighbors. For large values of k (for example when k is close to the total number of documents), the search may also retrieve fewer than k documents.

        The returned TopDocs will contain a ScoreDoc for each nearest neighbor, in order of their similarity to the query vector (decreasing scores). The TotalHits contains the number of documents visited during the search. If the search stopped early because it hit visitedLimit, it is indicated through the relation TotalHits.Relation.GREATER_THAN_OR_EQUAL_TO.

        The behavior is undefined if the given field doesn't have KNN vectors enabled on its FieldInfo. The return value is never null.

        Specified by:
        search in class KnnVectorsReader
        Parameters:
        field - the vector field to search
        target - the vector-valued query
        k - the number of docs to return
        acceptDocs - Bits that represents the allowed documents to match, or null if they are all allowed to match.
        visitedLimit - the maximum number of nodes that the search is allowed to visit
        Returns:
        the k nearest neighbor documents, along with their (similarity-specific) scores.
        Throws:
        IOException
      • ramBytesUsed

        public long ramBytesUsed()
        Description copied from interface: Accountable
        Return the memory usage of this object in bytes. Negative values are illegal.