This resource allows you to create Vector Search Endpoint in Databricks. Vector Search is a serverless similarity search engine that allows you to store a vector representation of your data, including metadata, in a vector database. The Vector Search Endpoint is used to create and access vector search indexes.
resource "databricks_vector_search_endpoint" "this" {
name = "vector-search-test"
endpoint_type = "STANDARD"
}
The following arguments are supported (change of any parameter leads to recreation of the resource):
name
- (Required) Name of the Vector Search Endpoint to create.endpoint_type
(Required) Type of Vector Search Endpoint. Currently only accepting single value: STANDARD
(See documentation for the list of currently supported values).In addition to all the arguments above, the following attributes are exported:
id
- The same as the name of the endpoint.creator
- Creator of the endpoint.creation_timestamp
- Timestamp of endpoint creation (milliseconds).last_updated_user
- User who last updated the endpoint.last_updated_timestamp
- Timestamp of the last update to the endpoint (milliseconds).endpoint_id
- Unique internal identifier of the endpoint (UUID).num_indexes
- Number of indexes on the endpoint.endpoint_status
- Object describing the current status of the endpoint consisting of the following fields:
state
- Current state of the endpoint. Currently following values are supported: PROVISIONING
, ONLINE
, and OFFLINE
.message
- Additional status message.The resource can be imported using the name of the Vector Search Endpoint
terraform import databricks_vector_search_endpoint.this <endpoint-name>