Puede consultar datos de una tabla mediante un SDK o desde la página Query Test en la consola de OpenSearch Vector Search Edition.
1. Configuración de la lista de permitidos de acceso público
Si accede a una instancia de OpenSearch Vector Search Edition desde la Virtual Private Cloud (VPC) donde reside la instancia y utiliza el mismo vSwitch, omita este paso.
Para obtener más información sobre cómo acceder a una instancia de OpenSearch Vector Search Edition desde un entorno local o desde Internet, consulte Configure the public access whitelist.
2. Consulta de datos en una tabla
Uso de un SDK
El siguiente código de ejemplo muestra cómo usar el SDK para Python para consultar datos en una tabla.
Agregar dependencias:
pip install alibabacloud-ha3engine-vectorCódigo de demostración para consultar datos:
from alibabacloud_ha3engine_vector.client import Client
from alibabacloud_ha3engine_vector.models import Config
from alibabacloud_ha3engine_vector.models import QueryRequest
config = Config(
# For private network calls, use the private endpoint.
endpoint="<your_api_endpoint>",
# The instance ID. You can find this in the upper-left corner of the instance details page. Example: ha-cn-i7*****605
instance_id="<your_instance_id>",
# The username. Find it in the Network Information section of the instance details page.
access_user_name="<your_username>",
# The password. You can change it in the Network Information section of the instance details page.
access_pass_word="<your_password>")
client = Client(config)
request = QueryRequest(table_name="<your_table_name>",
vector=[0.1, 0.2, 0.3],
include_vector=True,
top_k=10)
result = client.query(request)
print(result.body)Para obtener más información sobre los SDK de otros lenguajes de programación, consulte Query data.
Si usa el SDK para Python, debe quitar el prefijo http:// al especificar el parámetro endpoint.
Respuesta de ejemplo:
{
"totalCount": 1,
"result": [
{
"id": "1",
"vector": [
0.0019676426891237499,
...
],
"score": 0.0
}
],
"totalTime": 2.688
}Uso de la consola de OpenSearch
En la consola de OpenSearch Vector Search Edition, haga clic en Instances en el panel de navegación izquierdo. Localice la instancia deseada y haga clic en Query Test en la columna Actions.
En la página Query Test, seleccione la tabla de índice deseada.
Seleccione la pestaña vector query. En la lista desplegable table name, elija la tabla de índice deseada, por ejemplo, fengxue. En el área de entrada JSON de la izquierda, introduzca la consulta y haga clic en Search. Los resultados de la consulta y el tiempo transcurrido aparecerán a la derecha.
Ejemplo:
{
"vector": [0.0019676427,0.005902928,0.021644069,0.21644068,0.12199384,0.043288138,0.007870571,0.0,0.08460863,0.041320495,0.043288138,0.035417568,0.011805856,0.055093993,0.12592913,0.017708784,0.021644069,0.0019676427,0.0,0.0,0.0019676427,0.078705706,0.1987319,0.041320495,0.039352853,0.0039352854,0.007870571,0.0039352854,0.0039352854,0.017708784,0.035417568,0.06886749,0.0019676427,0.0019676427,0.013773498,0.049191065,0.2125054,0.22824654,0.123961486,0.0039352854,0.0,0.0,0.021644069,0.14560555,0.078705706,0.1987319,0.22824654,0.005902928,0.064932205,0.0019676427,0.0019676427,0.021644069,0.027546996,0.035417568,0.22824654,0.22824654,0.1337997,0.023611711,0.009838213,0.007870571,0.0039352854,0.0039352854,0.017708784,0.20069954,0.033449925,0.005902928,0.019676426,0.035417568,0.015741142,0.029514639,0.13183205,0.123961486,0.029514639,0.0,0.027546996,0.22824654,0.15741141,0.0,0.0039352854,0.043288138,0.18889369,0.072802775,0.055093993,0.17315255,0.08460863,0.0019676427,0.007870571,0.035417568,0.22824654,0.10034977,0.009838213,0.021644069,0.062964566,0.027546996,0.015741142,0.04525578,0.086576276,0.033449925,0.023611711,0.017708784,0.0,0.0,0.03738521,0.072802775,0.16724962,0.035417568,0.031482283,0.20463483,0.043288138,0.011805856,0.0039352854,0.051158708,0.023611711,0.11412327,0.13183205,0.16134669,0.049191065,0.023611711,0.0039352854,0.0039352854,0.049191065,0.035417568,0.015741142,0.0039352854,0.03738521,0.08264099,0.094446845,0.021644069],
"topK": 10,
"includeVector": true
}Respuesta de ejemplo:
[
{
"vector": [
0.0019676426891237497,
0.0059029278345406055,
...
],
"id": "0",
"score": 0
}
]Sintaxis de consulta relacionada: