使用向量搜索集合

要为您的新集合创建索引，请在开发工具控制台中发送以下请求。默认情况下，这将创建具有欧几里得距离和 32 倍压缩的索引。

PUT housing-index
{
  "settings": {
    "index.knn": true
  },
  "mappings": {
    "properties": {
      "housing-vector": {
        "type": "knn_vector",
        "dimension": 3,
        "space_type": "l2"
      },
      "title": {
        "type": "text"
      },
      "price": {
        "type": "long"
      },
      "location": {
        "type": "geo_point"
      }
    }
  }
}

要使用不同的压缩级别，请在字段映射compression_level中进行设置。以下示例创建了一个compression_level设置为 1x 的索引。

PUT housing-index-1x
{
  "settings": {
    "index.knn": true
  },
  "mappings": {
    "properties": {
      "housing-vector": {
        "type": "knn_vector",
        "dimension": 3,
        "compression_level": "1x",
        "space_type": "l2"
      },
      "title": {
        "type": "text"
      },
      "price": {
        "type": "long"
      },
      "location": {
        "type": "geo_point"
      }
    }
  }
}

支持的压缩级别为 1 倍、2 倍、8 倍、16 倍和 32 倍。

要将文档编入索引housing-index，您可以使用系统生成的 ID (POST) 或用户提供的 ID (PUT)。

# System-generated document ID
POST housing-index/_doc
{
  "housing-vector": [10, 20, 30],
  "title": "2 bedroom in downtown Seattle",
  "price": "2800",
  "location": "47.71, 122.00"
}

# User-provided document ID
PUT housing-index/_doc/100
{
  "housing-vector": [10, 20, 30],
  "title": "2 bedroom in downtown Seattle",
  "price": "2800",
  "location": "47.71, 122.00"
}

要搜索与索引中的属性相似的属性，请发送以下查询。默认情况下，搜索响应会从中排除原始向量，_source以减少延迟和有效载荷大小。

GET housing-index/_search
{
  "size": 5,
  "query": {
    "knn": {
      "housing-vector": {
        "vector": [10, 20, 30],
        "k": 2
      }
    }
  }
}

响应将该housing-vector字段排除在外_source：

{
  "took": 10,
  "timed_out": false,
  "_shards": {
    "total": 0,
    "successful": 0,
    "skipped": 0,
    "failed": 0
  },
  "hits": {
    "total": {
      "value": 1,
      "relation": "eq"
    },
    "max_score": 1,
    "hits": [
      {
        "_index": "housing-index",
        "_id": "100",
        "_score": 1,
        "_source": {
          "price": "2800",
          "location": "47.71, 122.00",
          "title": "2 bedroom in downtown Seattle"
        }
      }
    ]
  }
}

打开亚马逊 OpenSearch 服务控制台。

在左侧导航窗格中，选择收藏，然后选择房屋收藏。

选择删除，然后确认删除。

要为您的集合创建单个索引，请在 Dev Tools 控制台中发送以下请求：

PUT housing-index-filtered
{
  "settings": {
    "index.knn": true
  },
  "mappings": {
    "properties": {
      "housing-vector": {
        "type": "knn_vector",
        "dimension": 3,
        "space_type": "l2",
        "method": {
          "name": "hnsw"
        }
      },
      "title": {
        "type": "text"
      },
      "price": {
        "type": "long"
      },
      "location": {
        "type": "geo_point"
      }
    }
  }
}

要将单个文档索引到 housing-index-filtered 中，请发送以下请求：

POST housing-index-filtered/_doc
{
  "housing-vector": [
    10,
    20,
    30
  ],
  "title": "2 bedroom in downtown Seattle",
  "price": "2800",
  "location": "47.71, 122.00"
}

要搜索西雅图给定价格和给定距离范围内的公寓数据，请发送以下请求：

GET housing-index-filtered/_search
{
  "size": 5,
  "query": {
    "knn": {
      "housing-vector": {
        "vector": [
          0.1,
          0.2,
          0.3
        ],
        "k": 5,
        "filter": {
          "bool": {
            "must": [
              {
                "query_string": {
                  "query": "Find me 2 bedroom apartment in Seattle under $3000 ",
                  "fields": [
                    "title"
                  ]
                }
              },
              {
                "range": {
                  "price": {
                    "lte": 3000
                  }
                }
              },
              {
                "geo_distance": {
                  "distance": "100miles",
                  "location": {
                    "lat": 48,
                    "lon": 121
                  }
                }
              }
            ]
          }
        }
      }
    }
  }
}