Elasticsearch排序字段异常

Question

尝试根据某些字段对列表进行排序。 firstName 和 lastName 但我注意到一些不稳定的结果。

我正在运行一个简单的查询

//Return all the employees from a specific company ordering by lastName asc | desc

GET employee-index-sorting
{
  "query": {
    "bool": {
      "filter": {
        "term": {
          "companyId": 3179
        }
      }
    }
  },
  "sort": [
    {
      "lastName.keyword": { <-- Should this be keyword? or not_analyzed
        "order": "desc"
      }
    }
  ]
}

在结果中，为什么 van der Mescht 和 van Breda 会排在 Zwane 和 Zwezwe 之前？

我怀疑我的映射有问题

{
        "_index": "employee-index",
        "_type": "_doc",
        "_id": "637467",
        "_score": null,
        "_source": {
          "companyId": 3179,
          "firstName": "Name",
          "lastName": "van der Mescht",
        },
        "sort": [
          "van der Mescht"
        ]
      },
      {
        "_index": "employee-index",
        "_type": "_doc",
        "_id": "678335",
        "_score": null,
        "_source": {
          "companyId": 3179,
          "firstName": "Name3",
          "lastName": "van Breda",
        },
        "sort": [
          "van Breda"
        ]
      },
      {
        "_index": "employee-index",
        "_type": "_doc",
        "_id": "113896",
        "_score": null,
        "_source": {
          "companyId": 3179,
          "firstName": "Name2",
          "lastName": "Zwezwe",
        },
        "sort": [
          "Zwezwe"
        ]
      },
      {
        "_index": "employee-index",
        "_type": "_doc",
        "_id": "639639",
        "_score": null,
        "_source": {
          "companyId": 3179,
          "firstName": "Name1",
          "lastName": "Zwane",
        },
        "sort": [
          "Zwane"
        ]
      }

映射

张贴整个 map ，因为我不确定它是否还有其他问题。

我应该如何更改 lastName 和 firstName 属性以允许对它们进行排序？

PUT employee-index-sorting
{
  "settings": {
    "index": {
      "analysis": {
        "filter": {},
        "analyzer": {
          "keyword_analyzer": {
            "filter": [
              "lowercase",
              "asciifolding",
              "trim"
            ],
            "char_filter": [],
            "type": "custom",
            "tokenizer": "keyword"
          },
          "edge_ngram_analyzer": {
            "filter": [
              "lowercase"
            ],
            "tokenizer": "edge_ngram_tokenizer"
          },
          "edge_ngram_search_analyzer": {
            "tokenizer": "lowercase"
          }
        },
        "tokenizer": {
          "edge_ngram_tokenizer": {
            "type": "edge_ngram",
            "min_gram": 2,
            "max_gram": 5,
            "token_chars": [
              "letter"
            ]
          }
        }
      }
    }
  },
  "mappings": {
    "_doc": {
      "properties": {
        "employeeId": {
          "type": "keyword"
        },
        "companyGroupId": {
          "type": "keyword"
        },
        "companyId": {
          "type": "keyword"
        },
        "number": {
          "type": "text",
          "fields": {
            "keyword": {
              "type": "keyword",
              "ignore_above": 256
            }
          }
        },
        "preferredName": {
          "type": "text",
          "index": false
        },
        "firstName": {
          "type": "text",
          "fields": {
            "keyword": {
              "type": "keyword",
              "ignore_above": 256
            }
          }
        },
        "middleName": {
          "type": "text",
          "index": false
        },
        "lastName": {
          "type": "text",
          "fields": {
            "keyword": {
              "type": "keyword",
              "ignore_above": 256
            }
          }
        },
        "fullName": {
          "type": "text",
          "fields": {
            "keywordstring": {
              "type": "text",
              "analyzer": "keyword_analyzer"
            },
            "edgengram": {
              "type": "text",
              "analyzer": "edge_ngram_analyzer",
              "search_analyzer": "edge_ngram_search_analyzer"
            }
          },
          "analyzer": "standard"
        },
        "terminationDate": {
          "type": "date"
        },
        "companyName": {
          "type": "text",
          "fields": {
            "keyword": {
              "type": "keyword",
              "ignore_above": 256
            }
          }
        },
        "email": {
          "type": "text",
          "fields": {
            "keyword": {
              "type": "keyword",
              "ignore_above": 256
            }
          }
        },
        "idNumber": {
          "type": "text"
        },
        "description": {
          "type": "text",
          "index": false
        },
        "jobNumber": {
          "type": "keyword"
        },
        "frequencyId": {
          "type": "long"
        },
        "frequencyCode": {
          "type": "text",
          "fields": {
            "keyword": {
              "type": "keyword",
              "ignore_above": 256
            }
          }
        },
        "frequencyAccess": {
          "type": "boolean"
        }
      }
    }
  }
}

Answer 1

要进行排序，您需要使用 lastName.keyword，这是正确的，无需更改那里的任何内容。

之所以 van der Mescht 和 van Breda 在 Zwane 和 Zwezwe 之前是因为对字符串进行排序发生在字典级别，即基本上使用 ASCII table大写字符出现在小写字符之前，因此单词按相同顺序排序。但是由于您在 desc 模式下进行排序，所以情况恰恰相反:

• z...
• ...
• 范德梅施特
• ...
• 范布雷达
• ...
• 一个...
• ...
• 茨韦兹韦
• ...
• Zwane
• ...
• Z...
• ...
• 一个...

要解决此问题，您只需添加一个 normalizer到您的 lastName.keyword 字段，即将您的映射更改为此，它将起作用:

{
  "settings": {
    "index": {
      "analysis": {
        "filter": {},
        "analyzer": { 
          ...
        },
        "tokenizer": {
          ...
        },
        "normalizer": {             <-- add this
          "lowersort": {
            "type": "custom",
            "filter": [
              "lowercase"
            ]
          }
        }
      }
    }
  },
  "mappings": {
    "_doc": {
      "properties": {
        ...
        "lastName": {
          "type": "text",
          "fields": {
            "keyword": {
              "type": "keyword",
              "normalizer": "lowersort",   <-- add this
              "ignore_above": 256
            }
          }
        },
        ...
      }
    }
  }
}