elasticsearch 禁用词频评分

Question

我想更改 elasticsearch 中的评分系统，以摆脱对一个术语的多次出现进行计数。例如，我想要：

“得克萨斯州得克萨斯州得克萨斯州”

和

“德州”

同分出来。我发现 elasticsearch 说这个映射会禁用词频计数，但我的搜索结果不一样：

"mappings":{
"business": {   
   "properties" : {
       "name" : {
          "type" : "string",
          "index_options" : "docs",
          "norms" : { "enabled": false}}
        }
    }
}

}

任何帮助将不胜感激，我找不到很多这方面的信息。

我正在添加我的搜索代码以及使用 explain 时返回的内容。

我的搜索码：

Settings settings = ImmutableSettings.settingsBuilder().put("cluster.name", "escluster").build();
    Client client = new TransportClient(settings)
    .addTransportAddress(new InetSocketTransportAddress("127.0.0.1", 9300));

    SearchRequest request =  Requests.searchRequest("businesses")
            .source(SearchSourceBuilder.searchSource().query(QueryBuilders.boolQuery()
            .should(QueryBuilders.matchQuery("name", "Texas")
            .minimumShouldMatch("1")))).searchType(SearchType.DFS_QUERY_THEN_FETCH);
    
    ExplainRequest request2 = client.prepareIndex("businesses", "business")

当我用 explain 搜索时，我得到：

  "took" : 14,
  "timed_out" : false,
  "_shards" : {
    "total" : 3,
    "successful" : 3,
    "failed" : 0
  },
  "hits" : {
    "total" : 2,
    "max_score" : 1.0,
    "hits" : [ {
      "_shard" : 1,
      "_node" : "BTqBPVDET5Kr83r-CYPqfA",
      "_index" : "businesses",
      "_type" : "business",
      "_id" : "AU9U5KBks4zEorv9YI4n",
      "_score" : 1.0,
      "_source":{
"name" : "texas"
}
,
      "_explanation" : {
        "value" : 1.0,
        "description" : "weight(_all:texas in 0) [PerFieldSimilarity], result of:",
        "details" : [ {
          "value" : 1.0,
          "description" : "fieldWeight in 0, product of:",
          "details" : [ {
            "value" : 1.0,
            "description" : "tf(freq=1.0), with freq of:",
            "details" : [ {
              "value" : 1.0,
              "description" : "termFreq=1.0"
            } ]
          }, {
            "value" : 1.0,
            "description" : "idf(docFreq=2, maxDocs=3)"
          }, {
            "value" : 1.0,
            "description" : "fieldNorm(doc=0)"
          } ]
        } ]
      }
    }, {
      "_shard" : 1,
      "_node" : "BTqBPVDET5Kr83r-CYPqfA",
      "_index" : "businesses",
      "_type" : "business",
      "_id" : "AU9U5K6Ks4zEorv9YI4o",
      "_score" : 0.8660254,
      "_source":{
"name" : "texas texas texas"
}
,
      "_explanation" : {
        "value" : 0.8660254,
        "description" : "weight(_all:texas in 0) [PerFieldSimilarity], result of:",
        "details" : [ {
          "value" : 0.8660254,
          "description" : "fieldWeight in 0, product of:",
          "details" : [ {
            "value" : 1.7320508,
            "description" : "tf(freq=3.0), with freq of:",
            "details" : [ {
              "value" : 3.0,
              "description" : "termFreq=3.0"
            } ]
          }, {
            "value" : 1.0,
            "description" : "idf(docFreq=2, maxDocs=3)"
          }, {
            "value" : 0.5,
            "description" : "fieldNorm(doc=0)"
          } ]
        } ]
      }
    } ]
  }

看来还在考虑frequency和doc frequency。有任何想法吗？对不起，格式不好我不知道为什么它看起来如此怪诞。

我的代码来自浏览器搜索http://localhost:9200/businesses/business/_search?pretty=true&qname=texas 是：

    {
  "took" : 2,
  "timed_out" : false,
  "_shards" : {
    "total" : 3,
    "successful" : 3,
    "failed" : 0
  },
  "hits" : {
    "total" : 4,
    "max_score" : 1.0,
    "hits" : [ {
      "_index" : "businesses",
      "_type" : "business",
      "_id" : "AU9YcCKjKvtg8NgyozGK",
      "_score" : 1.0,
      "_source":{"business" : {
"name" : "texas texas texas texas" }
}
    }, {
      "_index" : "businesses",
      "_type" : "business",
      "_id" : "AU9YateBKvtg8Ngyoy-p",
      "_score" : 1.0,
      "_source":{
"name" : "texas" }

    }, {
      "_index" : "businesses",
      "_type" : "business",
      "_id" : "AU9YavVnKvtg8Ngyoy-4",
      "_score" : 1.0,
      "_source":{
"name" : "texas texas texas" }

    }, {
      "_index" : "businesses",
      "_type" : "business",
      "_id" : "AU9Yb7NgKvtg8NgyozFf",
      "_score" : 1.0,
      "_source":{"business" : {
"name" : "texas texas texas" }
}
    } ]
  }
}

它找到了我在其中的所有 4 个对象，并且它们的分数都相同。当我运行我的 java API 使用解释搜索时，我得到：

    {
  "took" : 2,
  "timed_out" : false,
  "_shards" : {
    "total" : 3,
    "successful" : 3,
    "failed" : 0
  },
  "hits" : {
    "total" : 2,
    "max_score" : 1.287682,
    "hits" : [ {
      "_shard" : 1,
      "_node" : "BTqBPVDET5Kr83r-CYPqfA",
      "_index" : "businesses",
      "_type" : "business",
      "_id" : "AU9YateBKvtg8Ngyoy-p",
      "_score" : 1.287682,
      "_source":{
"name" : "texas" }
,
      "_explanation" : {
        "value" : 1.287682,
        "description" : "weight(name:texas in 0) [PerFieldSimilarity], result of:",
        "details" : [ {
          "value" : 1.287682,
          "description" : "fieldWeight in 0, product of:",
          "details" : [ {
            "value" : 1.0,
            "description" : "tf(freq=1.0), with freq of:",
            "details" : [ {
              "value" : 1.0,
              "description" : "termFreq=1.0"
            } ]
          }, {
            "value" : 1.287682,
            "description" : "idf(docFreq=2, maxDocs=4)"
          }, {
            "value" : 1.0,
            "description" : "fieldNorm(doc=0)"
          } ]
        } ]
      }
    }, {
      "_shard" : 1,
      "_node" : "BTqBPVDET5Kr83r-CYPqfA",
      "_index" : "businesses",
      "_type" : "business",
      "_id" : "AU9YavVnKvtg8Ngyoy-4",
      "_score" : 1.1151654,
      "_source":{
"name" : "texas texas texas" }
,
      "_explanation" : {
        "value" : 1.1151654,
        "description" : "weight(name:texas in 0) [PerFieldSimilarity], result of:",
        "details" : [ {
          "value" : 1.1151654,
          "description" : "fieldWeight in 0, product of:",
          "details" : [ {
            "value" : 1.7320508,
            "description" : "tf(freq=3.0), with freq of:",
            "details" : [ {
              "value" : 3.0,
              "description" : "termFreq=3.0"
            } ]
          }, {
            "value" : 1.287682,
            "description" : "idf(docFreq=2, maxDocs=4)"
          }, {
            "value" : 0.5,
            "description" : "fieldNorm(doc=0)"
          } ]
        } ]
      }
    } ]
  }
}

Answer 1

在映射

中初始设置字段后，似乎无法覆盖该字段的index options

示例：

put test
put test/business/_mapping
{

      "properties": {
         "name": {
            "type": "string",
           "index_options": "freqs",
            "norms": {
               "enabled": false
            }
         }
      }

}
put test/business/_mapping
{

      "properties": {
         "name": {
            "type": "string",
            "index_options": "docs",
            "norms": {
               "enabled": false
            }
         }
      }

}
get  test/business/_mapping

   {
   "test": {
      "mappings": {
         "business": {
            "properties": {
               "name": {
                  "type": "string",
                  "norms": {
                     "enabled": false
                  },
                  "index_options": "freqs"
               }
            }
         }
      }
   }
}

您必须重新创建索引才能获取新映射

Answer 2

您的字段类型必须是文本

您必须重新索引 elasticsearch - 创建一个新索引

"mappings": {
    "properties": {
      "text": {
        "type": "text",
        "index_options": "docs"
      }
    }
  }

https://www.elastic.co/guide/en/elasticsearch/reference/current/index-options.html

elasticsearch 禁用词频评分

elasticsearch disable term frequency scoring

java

elasticsearch

frequency

scoring