查询数据

1、配置公网白名单

如果用户的访问环境是同个虚拟交换的VPC环境，可以忽略此步骤。

本地环境或公网环境请参考公网白名单配置。

2、查询表数据

SDK查询

这里以Python为例：

添加依赖：

pip install alibabacloud-ha3engine-vector

查询数据demo：

from alibabacloud_ha3engine_vector.client import Client
from alibabacloud_ha3engine_vector.models import Config
from alibabacloud_ha3engine_vector.models import QueryRequest

config = Config(
        #  私网域名调用请填写endpoint
        endpoint="<API域名>",
        #  实例名称，可在实例详情页左上角查看，例:ha-cn-i7*****605
        instance_id="<实例id>",
        #  用户名，可在实例详情页>网络信息 查看
        access_user_name="<用户名>",
        #  密码，可在实例详情页>网络信息 修改
        access_pass_word="<用户名密码>")
client = Client(config)

request = QueryRequest(table_name="<表名>",
                    	vector=[0.1, 0.2, 0.3],
                        include_vector=True,
                        top_k=10)
result = client.query(request)
print(result.body)

其他查询SDK可参考查询数据。

相应结果示例：

{
    "totalCount": 1,
    "result": [
        {
            "id": "1",
            "vector": [
                0.0019676426891237499,
               ...
            ],
            "score": 0.0
        }
    ],
    "totalTime": 2.688
}

控制台查询

1. 在向量检索版控制台>【实例管理】>【查询测试】页面：

2. 在查询测试页面选择对应的索引表进行查询：

示例：

{
  "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
}

相应结果：

[
  {
    "vector": [
      0.0019676426891237497,
      0.0059029278345406055,
   	...
    ],
    "id": "0",
    "score": 0
  }
]

相关查询语法：

• 向量查询

• 主键查询

• filter表达式