在Elasticsearch中,给出以下文档结构：

"workhistory": {
  "positions": [{
    "company": "Some company",
    "position": "Some Job Title",
    "start": 1356998400,
    "end": 34546576576,
    "description": "",
    "source": [
       "some source", 
       "some other source"
    ]
  },
  {
    "company": "Some other company",
    "position": "Job Title",
    "start": 1356998400,
    "end": "",
    "description": "",
    "source": [
       "some other source"
    ]
  }]
}

和这种结构的映射：

  workhistory: {
    properties: {    
      positions: {
        type: "nested", 
        include_in_parent: true, 
        properties: {                 
          company: {
            type: "multi_field",
            fields: {
              company: {type: "string"},
              original: {type : "string", analyzer : "string_lowercase"} 
            }              
          }, 
          position: {
            type: "multi_field",
            fields: {
              position: {type: "string"},
              original: {type : "string", analyzer : "string_lowercase"} 
            }              
          }                                                       
        }
      }        
    }
  }

我希望能够搜索“公司”并匹配文档,如果公司=“某些公司”等.然后我想得到tf idf _score.我还想创建一个function_score查询,以根据“source”字段数组的值来提高此匹配的分数.基本上,如果源包含“some source”,则使用x amount来提升_score.如果需要,我可以更改“source”属性的结构.

这是我到目前为止所得到的：

{
   "bool": {
      "should": [
         {
            "filtered": {
               "query": {
                  "bool": {
                     "should": [
                        {
                           "bool": {
                              "should": [
                                 {
                                    "match": {
                                       "workhistory.positions.company.original": "some company"
                                    }
                                 }
                              ]
                           }
                        }
                     ],
                     "minimum_should_match": "100%"
                  }
               },
               "filter": {
                  "and": [
                     {
                        "bool": {
                           "should": [
                              {
                                 "term": {
                                    "workhistory.positions.company.original": "some company"
                                 }
                              }
                           ]
                        }
                     }
                  ]
               }
            }
         },
         {
            "function_score": {
               "query": {
                  "bool": {
                     "should": [
                        {
                           "bool": {
                              "should": [
                                 {
                                    "match": {
                                       "workhistory.positions.company.original": "some company"
                                    }
                                 }
                              ]
                           }
                        }
                     ],
                     "minimum_should_match": "100%"
                  }
               },
               "filter": {
                  "and": [
                     {
                        "bool": {
                           "should": [
                              {
                                 "term": {
                                    "workhistory.positions.company.original": "some company"
                                 }
                              }
                           ]
                        }
                     }
                  ]
               }
            }
         }
      ]
   }
}

这里也有一些过滤器,因为我只想返回带有过滤值的文档.在这个例子中,过滤器和查询基本相同,但在这个查询的更大版本中,我有一些其他“可选”匹配来提升可选值等.函数_score现在没有做太多,因为我无法真正计算如何使用它.目标是能够调整应用程序代码中的提升次数并将其传递给搜索查询.

我正在使用Elasticsearch 1.3.4版.

最佳答案 我不确定为什么你在那里重复所有那些过滤器和查询,说实话.也许我错过了一些东西,但根据你的描述,我相信你所需要的只是一个“function_score”.从
documentation：

The function_score allows you to modify the score of documents that are retrieved by a query.

因此,您定义一个查询(例如 – 匹配公司名称),然后定义一个函数列表,这些函数应该为某个文档子集提升_score.从相同的文档：

Furthermore, several functions can be combined. In this case one can optionally choose to apply the function only if a document matches a given filter

因此,您有查找具有特定名称的公司的查询,然后您有一个函数的过滤器来操作与过滤器匹配的文档的_score.在这种情况下,您的过滤器是应该包含某些内容的“来源”.函数本身就是一个脚本：_score 2.
最后,这将是我的想法：

    {
      "query": {
        "bool": {
          "should": [
            {
              "function_score": {
                "query": {
                  "bool": {
                    "should": [
                      {
                        "bool": {
                          "should": [
                            {
                              "match": {
                                "workhistory.positions.company.original": "some company"
                              }
                            }
                          ]
                        }
                      }
                    ],
                    "minimum_should_match": "100%"
                  }
                },
                "functions": [
                  {
                    "filter": {
                      "nested": {
                        "path": "workhistory.positions",
                        "query": {
                          "bool": {
                            "should": [
                              {
                                "match": {
                                  "workhistory.positions.source": "some source"
                                }
                              }
                            ]
                          }
                        }
                      }
                    },
                    "script_score": {
                  "script": "_score + 2"
                }
              },
              {
                "filter": {
                  "nested": {
                    "path": "workhistory.positions",
                    "query": {
                      "bool": {
                        "should": [
                          {
                            "match": {
                              "workhistory.positions.source": "xxx"
                            }
                          }
                        ]
                      }
                    }
                  }
                },
                "script_score": {
                  "script": "_score + 4"
                }
              }
            ],
            "max_boost": 5,
            "score_mode": "sum",
            "boost_mode": "sum"
          }
        }
      ]
    }
  }
}