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反向检索 percolate

反向查询：将查询存储到索引中，然后通过Percolate API定义文档以检索这些查询。

使用场景​

反向查询通常用于通知的场景

举例：用户订阅了对阿凡达电影感兴趣，当阿凡达电影上映时给该用户发送通知。

PUT /my-index
{
    "mappings": {
        "_doc": {
            "properties": {
                "message": {
                    "type": "text"
                },
                "query": {
                    "type": "percolator"
                }
            }
        }
    }
}

PUT /my-index/_doc/1?refresh
{
    "query" : {
        "match" : {
            "message" : "avatar"
        }
    }
}

执行反向查询，将文档文本与注册的query进行匹配：

GET /my-index/_search
{
    "query" : {
        "percolate" : {
            "field" : "query",
            "document" : {
                "message" : "avatar is offer"
            }
        }
    }
}

返回结果

{
  "took": 13,
  "timed_out": false,
  "_shards": {
    "total": 5,
    "successful": 5,
    "skipped" : 0,
    "failed": 0
  },
  "hits": {
    "total": 1,
    "max_score": 0.5753642,
    "hits": [
      { 
        "_index": "my-index",
        "_type": "_doc",
        "_id": "1",
        "_score": 0.5753642,
        "_source": {
          "query": {
            "match": {
              "message": "avatar"
            }
          }
        },
        "fields" : {
          "_percolator_document_slot" : [0] 
        }
      }
    ]
  }
}
  1. id 为 1 的查询与我们的文档匹配。
  2. _percolator_document_slot 字段指示哪个文档与此查询匹配。
参数含义
field（必填项） 保存索引查询的过滤器类型的字段。
name（可选项）如果指定了多个渗透查询，则用于 _percolator_document_slot 字段的后缀。这是一个可选参数。
document正在渗透的文档的来源。
documents与文档参数类似，但通过 json 数组接受多个文档。

Percolating 关闭算分以提升性能​

GET /my-index/_search
{
    "query" : {
        "constant_score": {
            "filter": {
                "percolate" : {
                    "field" : "query",
                    "document" : {
                        "message" : "avatar is offer"
                    }
                }
            }
        }
    }
}

如果不需要计算分数，则应该将Percolating Query 包装在 Constant Score Query 或 Bool 查询的 filter 子句中，以获取查询性能的提升。

反向查找多个文档​

percolate 查询可以使用索引的 percolator 查询同时匹配多个文档。在单个请求中渗透多个文档可以提高性能，因为查询只需要解析和匹配一次而不是多次。每个匹配的过滤器查询返回的 _percolator_document_slot 字段在同时过滤多个文档时很重要。它指示哪些文档与特定的过滤器查询匹配。这些数字与渗透查询中指定的文档数组中的slot相关

GET /my-index/_search
{
    "query" : {
        "percolate" : {
            "field" : "query",
            "documents" : [ 
                {
                    "message" : "avatar is offer"
                },
                {
                    "message" : "offer movies"
                },
                {
                    "message" : "Sparta is offer"
                }
            ]
        }
    }
}

返回

{
  "took": 13,
  "timed_out": false,
  "_shards": {
    "total": 5,
    "successful": 5,
    "skipped" : 0,
    "failed": 0
  },
  "hits": {
    "total": 1,
    "max_score": 1.5606477,
    "hits": [
      {
        "_index": "my-index",
        "_type": "_doc",
        "_id": "1",
        "_score": 1.5606477,
        "_source": {
          "query": {
            "match": {
              "message": "bonsai tree"
            }
          }
        },
        "fields" : {
          "_percolator_document_slot" : [0, 1, 3] 
        }
      }
    ]
  }
}

反向查找已存在的文档​

PUT /my-index/_doc/2
{
  "message" : "A new bonsai tree in the office"
}

percolate 基于已存在的索引构建新搜索请求：

GET /my-index/_search
{
    "query" : {
        "percolate" : {
            "field": "query",
            "index" : "my-index",
            "type" : "_doc",
            "id" : "2",
            "version" : 1 
        }
    }
}

版本是可选的，但在某些情况下很有用。我们可以确保我们正在尝试渗透我们刚刚索引的文档。在我们建立索引后可能会进行更改，如果是这种情况，搜索请求将因版本冲突错误而失败

反向查找与高亮​

PUT /my-index/_doc/3?refresh
{
    "query" : {
        "match" : {
            "message" : "brown fox"
        }
    }
}

PUT /my-index/_doc/4?refresh
{
    "query" : {
        "match" : {
            "message" : "lazy dog"
        }
    }
}

执行高亮查询：

GET /my-index/_search
{
    "query" : {
        "percolate" : {
            "field": "query",
            "document" : {
                "message" : "The quick brown fox jumps over the lazy dog"
            }
        }
    },
    "highlight": {
      "fields": {
        "message": {}
      }
    }
}

返回

{
  "took": 7,
  "timed_out": false,
  "_shards": {
    "total": 5,
    "successful": 5,
    "skipped" : 0,
    "failed": 0
  },
  "hits": {
    "total": 2,
    "max_score": 0.5753642,
    "hits": [
      {
        "_index": "my-index",
        "_type": "_doc",
        "_id": "4",
        "_score": 0.5753642,
        "_source": {
          "query": {
            "match": {
              "message": "lazy dog"
            }
          }
        },
        "highlight": {
          "message": [
            "The quick brown fox jumps over the <em>lazy</em> <em>dog</em>" 
          ]
        },
        "fields" : {
          "_percolator_document_slot" : [0]
        }
      },
      {
        "_index": "my-index",
        "_type": "_doc",
        "_id": "3",
        "_score": 0.5753642,
        "_source": {
          "query": {
            "match": {
              "message": "brown fox"
            }
          }
        },
        "highlight": {
          "message": [
            "The quick <em>brown</em> <em>fox</em> jumps over the lazy dog" 
          ]
        },
        "fields" : {
          "_percolator_document_slot" : [0]
        }
      }
    ]
  }
}

搜索请求中的查询不是高亮过滤结果，而是高亮过滤查询中定义的文档。 当同时过滤多个文档时（如下面的请求），高亮响应是不同的

GET /my-index/_search
{
    "query" : {
        "percolate" : {
            "field": "query",
            "documents" : [
                {
                    "message" : "bonsai tree"
                },
                {
                    "message" : "new tree"
                },
                {
                    "message" : "the office"
                },
                {
                    "message" : "office tree"
                }
            ]
        }
    },
    "highlight": {
      "fields": {
        "message": {}
      }
    }
}

略有不同的响应：

{
  "took": 13,
  "timed_out": false,
  "_shards": {
    "total": 5,
    "successful": 5,
    "skipped" : 0,
    "failed": 0
  },
  "hits": {
    "total": 1,
    "max_score": 1.5606477,
    "hits": [
      {
        "_index": "my-index",
        "_type": "_doc",
        "_id": "1",
        "_score": 1.5606477,
        "_source": {
          "query": {
            "match": {
              "message": "bonsai tree"
            }
          }
        },
        "fields" : {
          "_percolator_document_slot" : [0, 1, 3]
        },
        "highlight" : { 
          "0_message" : [
              "<em>bonsai</em> <em>tree</em>"
          ],
          "3_message" : [
              "office <em>tree</em>"
          ],
          "1_message" : [
              "new <em>tree</em>"
          ]
        }
      }
    ]
  }
}

指定多个反向查询​

可以在单个搜索请求中指定多个反向查询

GET /my-index/_search
{
    "query" : {
        "bool" : {
            "should" : [
                {
                    "percolate" : {
                        "field" : "query",
                        "document" : {
                            "message" : "bonsai tree"
                        },
                        "name": "query1" 
                    }
                },
                {
                    "percolate" : {
                        "field" : "query",
                        "document" : {
                            "message" : "tulip flower"
                        },
                        "name": "query2" 
                    }
                }
            ]
        }
    }
}

name 参数将用于标识哪个 percolator document slots 属于哪个 percolate 查询。

_percolator_document_slot 字段名称将以 _name 参数中指定的内容为后缀。如果未指定，则将使用 field 参数，在这种情况下会导致歧义。

上面的搜索请求返回类似这样的响应

{
  "took": 13,
  "timed_out": false,
  "_shards": {
    "total": 5,
    "successful": 5,
    "skipped" : 0,
    "failed": 0
  },
  "hits": {
    "total": 1,
    "max_score": 0.5753642,
    "hits": [
      {
        "_index": "my-index",
        "_type": "_doc",
        "_id": "1",
        "_score": 0.5753642,
        "_source": {
          "query": {
            "match": {
              "message": "bonsai tree"
            }
          }
        },
        "fields" : {
          "_percolator_document_slot_query1" : [0] 
        }
      }
    ]
  }
}
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