Reference documentation and code samples for the Google Cloud Ai Platform V1 Client class IndexConfig.
Configuration for vector indexing.
Generated from protobuf message google.cloud.aiplatform.v1.FeatureView.IndexConfig
Namespace
Google \ Cloud \ AIPlatform \ V1 \ FeatureViewMethods
__construct
Constructor.
| Parameters | |
|---|---|
| Name | Description |
data |
array
Optional. Data for populating the Message object. |
↳ tree_ah_config |
IndexConfig\TreeAHConfig
Optional. Configuration options for the tree-AH algorithm (Shallow tree + Asymmetric Hashing). Please refer to this paper for more details: https://arxiv.org/abs/1908.10396 |
↳ brute_force_config |
IndexConfig\BruteForceConfig
Optional. Configuration options for using brute force search, which simply implements the standard linear search in the database for each query. It is primarily meant for benchmarking and to generate the ground truth for approximate search. |
↳ embedding_column |
string
Optional. Column of embedding. This column contains the source data to create index for vector search. embedding_column must be set when using vector search. |
↳ filter_columns |
array
Optional. Columns of features that're used to filter vector search results. |
↳ crowding_column |
string
Optional. Column of crowding. This column contains crowding attribute which is a constraint on a neighbor list produced by FeatureOnlineStoreService.SearchNearestEntities to diversify search results. If NearestNeighborQuery.per_crowding_attribute_neighbor_count is set to K in SearchNearestEntitiesRequest, it's guaranteed that no more than K entities of the same crowding attribute are returned in the response. |
↳ embedding_dimension |
int
Optional. The number of dimensions of the input embedding. |
↳ distance_measure_type |
int
Optional. The distance measure used in nearest neighbor search. |
getTreeAhConfig
Optional. Configuration options for the tree-AH algorithm (Shallow tree
- Asymmetric Hashing). Please refer to this paper for more details: https://arxiv.org/abs/1908.10396
| Returns | |
|---|---|
| Type | Description |
IndexConfig\TreeAHConfig|null |
|
hasTreeAhConfig
setTreeAhConfig
Optional. Configuration options for the tree-AH algorithm (Shallow tree
- Asymmetric Hashing). Please refer to this paper for more details: https://arxiv.org/abs/1908.10396
| Parameter | |
|---|---|
| Name | Description |
var |
IndexConfig\TreeAHConfig
|
| Returns | |
|---|---|
| Type | Description |
$this |
|
getBruteForceConfig
Optional. Configuration options for using brute force search, which simply implements the standard linear search in the database for each query. It is primarily meant for benchmarking and to generate the ground truth for approximate search.
| Returns | |
|---|---|
| Type | Description |
IndexConfig\BruteForceConfig|null |
|
hasBruteForceConfig
setBruteForceConfig
Optional. Configuration options for using brute force search, which simply implements the standard linear search in the database for each query. It is primarily meant for benchmarking and to generate the ground truth for approximate search.
| Parameter | |
|---|---|
| Name | Description |
var |
IndexConfig\BruteForceConfig
|
| Returns | |
|---|---|
| Type | Description |
$this |
|
getEmbeddingColumn
Optional. Column of embedding. This column contains the source data to create index for vector search. embedding_column must be set when using vector search.
| Returns | |
|---|---|
| Type | Description |
string |
|
setEmbeddingColumn
Optional. Column of embedding. This column contains the source data to create index for vector search. embedding_column must be set when using vector search.
| Parameter | |
|---|---|
| Name | Description |
var |
string
|
| Returns | |
|---|---|
| Type | Description |
$this |
|
getFilterColumns
Optional. Columns of features that're used to filter vector search results.
| Returns | |
|---|---|
| Type | Description |
Google\Protobuf\Internal\RepeatedField |
|
setFilterColumns
Optional. Columns of features that're used to filter vector search results.
| Parameter | |
|---|---|
| Name | Description |
var |
string[]
|
| Returns | |
|---|---|
| Type | Description |
$this |
|
getCrowdingColumn
Optional. Column of crowding. This column contains crowding attribute which is a constraint on a neighbor list produced by FeatureOnlineStoreService.SearchNearestEntities to diversify search results. If NearestNeighborQuery.per_crowding_attribute_neighbor_count is set to K in SearchNearestEntitiesRequest, it's guaranteed that no more than K entities of the same crowding attribute are returned in the response.
| Returns | |
|---|---|
| Type | Description |
string |
|
setCrowdingColumn
Optional. Column of crowding. This column contains crowding attribute which is a constraint on a neighbor list produced by FeatureOnlineStoreService.SearchNearestEntities to diversify search results. If NearestNeighborQuery.per_crowding_attribute_neighbor_count is set to K in SearchNearestEntitiesRequest, it's guaranteed that no more than K entities of the same crowding attribute are returned in the response.
| Parameter | |
|---|---|
| Name | Description |
var |
string
|
| Returns | |
|---|---|
| Type | Description |
$this |
|
getEmbeddingDimension
Optional. The number of dimensions of the input embedding.
| Returns | |
|---|---|
| Type | Description |
int |
|
hasEmbeddingDimension
clearEmbeddingDimension
setEmbeddingDimension
Optional. The number of dimensions of the input embedding.
| Parameter | |
|---|---|
| Name | Description |
var |
int
|
| Returns | |
|---|---|
| Type | Description |
$this |
|
getDistanceMeasureType
Optional. The distance measure used in nearest neighbor search.
| Returns | |
|---|---|
| Type | Description |
int |
|
setDistanceMeasureType
Optional. The distance measure used in nearest neighbor search.
| Parameter | |
|---|---|
| Name | Description |
var |
int
|
| Returns | |
|---|---|
| Type | Description |
$this |
|
getAlgorithmConfig
| Returns | |
|---|---|
| Type | Description |
string |
|