VectorIndex
Contains the configuration settings for a vector index, including the index name, vector attribute, dimensions, distance function, search schema, and projection.
Contents
Note
In the following list, the required parameters are described first.
- Dimensions
-
The number of dimensions in each vector.
Type: Long
Valid Range: Minimum value of 1.
Required: Yes
- DistanceFunction
-
The distance function used to calculate similarity between vectors. Valid values:
COSINE,EUCLIDEAN,DOT_PRODUCT.Type: String
Valid Values:
COSINE | DOT_PRODUCT | EUCLIDEANRequired: Yes
- IndexName
-
The name of the vector index.
Type: String
Length Constraints: Minimum length of 3. Maximum length of 255.
Pattern:
[a-zA-Z0-9_.-]+Required: Yes
- Projection
-
Specifies attributes that are copied (projected) from the table into the vector index.
Type: Projection object
Required: Yes
- VectorAttribute
-
The vector attribute configuration for the index.
Type: VectorAttributeDefinition object
Required: Yes
- SearchSchema
-
The search schema that defines partition key and inline filter attributes for the vector index.
Every attribute that you reference in
SearchSchemamust also be declared in the table'sAttributeDefinitions, the same way key attributes are declared for a global secondary index. Otherwise, the request fails with aValidationException.Type: Array of SearchSchemaElement objects
Array Members: Minimum number of 1 item.
Required: No
See Also
For more information about using this API in one of the language-specific AWS SDKs, see the following:
