QUERY

Use the DBMS_VECTOR.QUERY function to perform a similarity search operation which returns the top-k results as a JSON array.

Syntax

Query is overloaded and supports a version with query_vector passed in as a VECTOR type in addition to CLOB.

DBMS_VECTOR.QUERY (
    TAB_NAME             IN VARCHAR2,
    VEC_COL_NAME         IN VARCHAR2,
    QUERY_VECTOR         IN CLOB,
    TOP_K                IN NUMBER,
    VEC_PROJ_COLS        IN JSON_ARRAY_T DEFAULT NULL,
    IDX_NAME             IN VARCHAR2 DEFAULT NULL,
    DISTANCE_METRIC      IN VARCHAR2 DEFAULT 'COSINE',
    USE_INDEX            IN BOOLEAN DEFAULT TRUE,
    ACCURACY             IN NUMBER DEFAULT 90,
    IDX_PARAMETERS       IN CLOB DEFAULT NULL
) return JSON_ARRAY_T;

DBMS_VECTOR.QUERY (
    TAB_NAME             IN VARCHAR2,
    VEC_COL_NAME         IN VARCHAR2,
    QUERY_VECTOR         IN VECTOR,
    TOP_K                IN NUMBER,
    VEC_PROJ_COLS        IN JSON_ARRAY_T DEFAULT NULL,
    IDX_NAME             IN VARCHAR2 DEFAULT NULL,
    DISTANCE_METRIC      IN VARCHAR2 DEFAULT 'COSINE',
    USE_INDEX            IN BOOLEAN DEFAULT TRUE,
    ACCURACY             IN NUMBER DEFAULT 90,
    IDX_PARAMETERS       IN CLOB DEFAULT NULL
) return JSON_ARRAY_T;

Parameters

Table 10 DBMS_VECTOR.QUERY

Parameter	Description
tab_name	Table name to query
vec_col_name	Vector column name
query_vector	Query vector passed in as CLOB or VECTOR.
top_k	Number of results to be returned.
vec_proj_cols	Columns to be projected as part of the result.
idx_name	Optional index hint.
distance_metric	Distance computation metric. Defaults to COSINE. Can also be MANHATTAN, HAMMING, DOT, EUCLIDEAN, L2_SQUARED, EUCLIDEAN_SQUARED, or JACCARD.
use_index	Specifies whether the search is an approximate search or exact search. Defaults to TRUE (that is, approximate).
accuracy	Specifies the minimum desired query accuracy.
idx_parameters	Specifies values of efsearch, neighbor partition probes, and rescore factor passed in, formatted as JSON.