Node.js 弹性搜索多匹配查询可以'；不要忽略特殊字符_Node.js_<img Src="//i.stack.imgur.com/RUiNP.png" Height="16" Width="18" Alt="" Class="sponsor Tag Img">elasticsearch_Graphql

Node.js 弹性搜索多匹配查询可以'；不要忽略特殊字符

node.js graphql

Node.js 弹性搜索多匹配查询可以'；不要忽略特殊字符,node.js,elasticsearch,graphql,Node.js,elasticsearch,Graphql,我有一个名称字段值为“abc_name”，所以当我搜索“abc_”时，我会得到正确的结果，但当我搜索“abc_@#&-#&”时，我仍然会得到相同的结果。我希望我的查询忽略与我的查询不匹配的特殊字符我的问题是：多重匹配键入交叉字段操作员和我正在为我的字段使用search_analyzer标准我想要这个结构，否则它会影响我的其他搜索行为 "name": { "type": "text",

我有一个名称字段值为“abc_name”，所以当我搜索“abc_”时，我会得到正确的结果，但当我搜索“abc_@#&-#&”时，我仍然会得到相同的结果。我希望我的查询忽略与我的查询不匹配的特殊字符

我的问题是：

多重匹配
键入交叉字段
操作员和
我正在为我的字段使用search_analyzer标准

我想要这个结构，否则它会影响我的其他搜索行为

  "name": {
         "type": "text",
           "fields": {
           "keyword": {
                 "type": "keyword",
                    "ignore_above": 256
                     }
                       },
                     "analyzer": "autocomplete",
                 "search_analyzer": "standard"
                            }

请参阅以下适合您的用例的示例，我创建了一个适合您的用例的示例：

样本映射： 生成的令牌：

{
  "tokens" : [
    {
      "token" : "abc_name",
      "start_offset" : 0,
      "end_offset" : 8,
      "type" : "word",
      "position" : 0
    },
    {
      "token" : "asda",
      "start_offset" : 9,
      "end_offset" : 13,
      "type" : "word",
      "position" : 1
    },
    {
      "token" : "1213_adav",
      "start_offset" : 25,
      "end_offset" : 34,
      "type" : "word",
      "position" : 2
    }
  ]
}

POST some_test_index/_search
{
  "query": {
    "match": {
      "my_field": "abc_"
    }
  }
}

POST some_test_index/_search
{
  "query": {
    "match": {
      "my_field": "efg_!@#!@#"
    }
  }
}

{
  "took" : 0,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 1,
      "relation" : "eq"
    },
    "max_score" : 0.47992462,
    "hits" : [
      {
        "_index" : "some_test_index",
        "_type" : "_doc",
        "_id" : "1",
        "_score" : 0.47992462,
        "_source" : {
          "my_field" : "abc_name asda efg_!@#!@# 1213_adav"
        }
      }
    ]
  }
}

{
  "took" : 0,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 0,
      "relation" : "eq"
    },
    "max_score" : null,
    "hits" : [ ]
  }
}

请注意，令牌

efg.@#@#已被删除
我添加了edge\u ngram fitler，因为如果您使用abc\u
进行搜索，并且通过标记器生成的标记是abc\u name
，则您希望搜索成功
样本文件：
查询请求：
用例1:
{
  "tokens" : [
    {
      "token" : "abc_name",
      "start_offset" : 0,
      "end_offset" : 8,
      "type" : "word",
      "position" : 0
    },
    {
      "token" : "asda",
      "start_offset" : 9,
      "end_offset" : 13,
      "type" : "word",
      "position" : 1
    },
    {
      "token" : "1213_adav",
      "start_offset" : 25,
      "end_offset" : 34,
      "type" : "word",
      "position" : 2
    }
  ]
}

POST some_test_index/_search
{
  "query": {
    "match": {
      "my_field": "abc_"
    }
  }
}

POST some_test_index/_search
{
  "query": {
    "match": {
      "my_field": "efg_!@#!@#"
    }
  }
}

{
  "took" : 0,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 1,
      "relation" : "eq"
    },
    "max_score" : 0.47992462,
    "hits" : [
      {
        "_index" : "some_test_index",
        "_type" : "_doc",
        "_id" : "1",
        "_score" : 0.47992462,
        "_source" : {
          "my_field" : "abc_name asda efg_!@#!@# 1213_adav"
        }
      }
    ]
  }
}

{
  "took" : 0,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 0,
      "relation" : "eq"
    },
    "max_score" : null,
    "hits" : [ ]
  }
}

用例2:
{
  "tokens" : [
    {
      "token" : "abc_name",
      "start_offset" : 0,
      "end_offset" : 8,
      "type" : "word",
      "position" : 0
    },
    {
      "token" : "asda",
      "start_offset" : 9,
      "end_offset" : 13,
      "type" : "word",
      "position" : 1
    },
    {
      "token" : "1213_adav",
      "start_offset" : 25,
      "end_offset" : 34,
      "type" : "word",
      "position" : 2
    }
  ]
}

POST some_test_index/_search
{
  "query": {
    "match": {
      "my_field": "abc_"
    }
  }
}

POST some_test_index/_search
{
  "query": {
    "match": {
      "my_field": "efg_!@#!@#"
    }
  }
}

{
  "took" : 0,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 1,
      "relation" : "eq"
    },
    "max_score" : 0.47992462,
    "hits" : [
      {
        "_index" : "some_test_index",
        "_type" : "_doc",
        "_id" : "1",
        "_score" : 0.47992462,
        "_source" : {
          "my_field" : "abc_name asda efg_!@#!@# 1213_adav"
        }
      }
    ]
  }
}

{
  "took" : 0,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 0,
      "relation" : "eq"
    },
    "max_score" : null,
    "hits" : [ ]
  }
}

响应：
用例1的响应：
{
  "tokens" : [
    {
      "token" : "abc_name",
      "start_offset" : 0,
      "end_offset" : 8,
      "type" : "word",
      "position" : 0
    },
    {
      "token" : "asda",
      "start_offset" : 9,
      "end_offset" : 13,
      "type" : "word",
      "position" : 1
    },
    {
      "token" : "1213_adav",
      "start_offset" : 25,
      "end_offset" : 34,
      "type" : "word",
      "position" : 2
    }
  ]
}

POST some_test_index/_search
{
  "query": {
    "match": {
      "my_field": "abc_"
    }
  }
}

POST some_test_index/_search
{
  "query": {
    "match": {
      "my_field": "efg_!@#!@#"
    }
  }
}

{
  "took" : 0,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 1,
      "relation" : "eq"
    },
    "max_score" : 0.47992462,
    "hits" : [
      {
        "_index" : "some_test_index",
        "_type" : "_doc",
        "_id" : "1",
        "_score" : 0.47992462,
        "_source" : {
          "my_field" : "abc_name asda efg_!@#!@# 1213_adav"
        }
      }
    ]
  }
}

{
  "took" : 0,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 0,
      "relation" : "eq"
    },
    "max_score" : null,
    "hits" : [ ]
  }
}

用例2的响应：
{
  "tokens" : [
    {
      "token" : "abc_name",
      "start_offset" : 0,
      "end_offset" : 8,
      "type" : "word",
      "position" : 0
    },
    {
      "token" : "asda",
      "start_offset" : 9,
      "end_offset" : 13,
      "type" : "word",
      "position" : 1
    },
    {
      "token" : "1213_adav",
      "start_offset" : 25,
      "end_offset" : 34,
      "type" : "word",
      "position" : 2
    }
  ]
}

POST some_test_index/_search
{
  "query": {
    "match": {
      "my_field": "abc_"
    }
  }
}

POST some_test_index/_search
{
  "query": {
    "match": {
      "my_field": "efg_!@#!@#"
    }
  }
}

{
  "took" : 0,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 1,
      "relation" : "eq"
    },
    "max_score" : 0.47992462,
    "hits" : [
      {
        "_index" : "some_test_index",
        "_type" : "_doc",
        "_id" : "1",
        "_score" : 0.47992462,
        "_source" : {
          "my_field" : "abc_name asda efg_!@#!@# 1213_adav"
        }
      }
    ]
  }
}

{
  "took" : 0,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 0,
      "relation" : "eq"
    },
    "max_score" : null,
    "hits" : [ ]
  }
}

最新答复：
根据我创建的索引按如下方式创建映射，并告知是否有效：
PUT some_test_index
{
  "settings": {
    "analysis": {
      "analyzer": {
        "my_custom_analyzer": { 
          "type": "custom",
          "tokenizer": "punctuation",
          "filter": ["lowercase"]
        }
      },
      "tokenizer": {
        "punctuation": { 
          "type": "pattern",
          "pattern": "\\w+_+[^a-zA-Z\\d\\s_]+|\\s+"
        }
      }
    }
  },
  "mappings": {
    "properties": {
      "my_field":{
        "type": "text",
        "analyzer": "autocompete",                   <----- Assuming you have already this in setting
        "search_analyzer": "my_custom_analyzer".     <----- Note this
      }
    }
  }
}

放置一些测试索引
{
“设置”：{
“分析”：{
“分析器”：{
“我的自定义分析器”：{
“类型”：“自定义”，
“标记器”：“标点符号”，
“过滤器”：[“小写”]
}
},
“标记器”：{
“标点符号”：{
“类型”：“模式”，
“图案”：“\\w++[^a-zA-Z\\d\\s\++\\s+”
}
}
}
},
“映射”：{
“财产”：{
“我的领域”：{
“类型”：“文本”，
“analyzer”：“autocompete”，我希望我的查询忽略与我的查询不匹配的特殊字符，这是什么意思？当一些其他特殊字符（字段值中包含的字符除外）出现时，您是否希望搜索结果为空搜索查询中是否包含？是的。我希望此搜索结果为空。你能回答吗？我正在处理你的问题。你至少可以给我一些输入，但我正在使用analyzer autcomplete，因此我可以在任何字段上使用两个分析器。嘿@abhijeetSnap你能用你的映射更新问题吗？不，你不能使用两个分析器在字段上。您可以在搜索过程中使用不同的分析器，即通过search\u analyzer
，但在搜索或索引过程中，您不能在字段上指定两个分析器。请检查映射我已在上面更新，但我无法删除自动完成。我遵循了上面提到的所有步骤，还替换了analyzer autocompletee到我的_自定义_分析器，但仍然能够通过多个特殊的characters@AbhijeetSanap我已经更新了答案，但看到了您更新的评论，好吧，您正在尝试多种方法。首先，只在搜索\u analyzer
中进行更改，然后查看analyzer是否适用于您拥有的自动匹配
。如果可以的话不行，请执行此操作并在问题中发布详细信息。GET/\u设置