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02结构化搜索_在案例中实战使用term filter来搜索数据

Dongguo丶 发布时间：2021-11-16 22:31:20 ，浏览量：1

根据用户ID、是否隐藏、帖子ID、发帖日期来搜索帖子

（1）插入一些测试帖子数据 
POST /forum/article/_bulk
{ "index": { "_id": 1 }}
{ "articleID" : "XHDK-A-1293-#fJ3", "userID" : 1, "hidden": false, "postDate": "2017-01-01" }
{ "index": { "_id": 2 }}
{ "articleID" : "KDKE-B-9947-#kL5", "userID" : 1, "hidden": false, "postDate": "2017-01-02" }
{ "index": { "_id": 3 }}
{ "articleID" : "JODL-X-1937-#pV7", "userID" : 2, "hidden": false, "postDate": "2017-01-01" }
{ "index": { "_id": 4 }}
{ "articleID" : "QQPX-R-3956-#aD8", "userID" : 2, "hidden": true, "postDate": "2017-01-02" }

相应结果

{
  "took": 162,
  "errors": false,
  "items": [
    {
      "index": {
        "_index": "forum",
        "_type": "article",
        "_id": "1",
        "_version": 1,
        "result": "created",
        "_shards": {
          "total": 2,
          "successful": 1,
          "failed": 0
        },
        "created": true,
        "status": 201
      }
    },
    {
      "index": {
        "_index": "forum",
        "_type": "article",
        "_id": "2",
        "_version": 1,
        "result": "created",
        "_shards": {
          "total": 2,
          "successful": 1,
          "failed": 0
        },
        "created": true,
        "status": 201
      }
    },
    {
      "index": {
        "_index": "forum",
        "_type": "article",
        "_id": "3",
        "_version": 1,
        "result": "created",
        "_shards": {
          "total": 2,
          "successful": 1,
          "failed": 0
        },
        "created": true,
        "status": 201
      }
    },
    {
      "index": {
        "_index": "forum",
        "_type": "article",
        "_id": "4",
        "_version": 1,
        "result": "created",
        "_shards": {
          "total": 2,
          "successful": 1,
          "failed": 0
        },
        "created": true,
        "status": 201
      }
    }
  ]
}

初步来说，就先搞4个字段，因为整个es是支持json document格式的，所以说扩展性和灵活性非常之好。如果后续随着业务需求的增加，要在document中增加更多的field，那么我们可以很方便的随时添加field。但是如果是在关系型数据库中，比如mysql，我们建立了一个表，现在要给表中新增一些column，那就很坑爹了，必须用复杂的修改表结构的语法去执行。而且可能对系统代码还有一定的影响。

查看mapping

GET /forum/_mapping/article

响应结果

{
  "forum": {
    "mappings": {
      "article": {
        "properties": {
          "articleID": {
            "type": "text",
            "fields": {
              "keyword": {
                "type": "keyword",
                "ignore_above": 256
              }
            }
          },
          "hidden": {
            "type": "boolean"
          },
          "postDate": {
            "type": "date"
          },
          "userID": {
            "type": "long"
          }
        }
      }
    }
  }
}

现在使用的是es 5.6.0版本，type=text，默认会设置两个field，一个是field本身，比如articleID，就是分词的；还有一个的话，就是field.keyword，articleID.keyword，默认不分词，会最多保留256个字符

可以查看下两者的区别

articleID

GET /forum/_analyze
{
  "field": "articleID",
  "text": "XHDK-A-1293-#fJ3"
}

相应结果

{
  "tokens": [
    {
      "token": "xhdk",
      "start_offset": 0,
      "end_offset": 4,
      "type": "",
      "position": 0
    },
    {
      "token": "a",
      "start_offset": 5,
      "end_offset": 6,
      "type": "",
      "position": 1
    },
    {
      "token": "1293",
      "start_offset": 7,
      "end_offset": 11,
      "type": "",
      "position": 2
    },
    {
      "token": "fj3",
      "start_offset": 13,
      "end_offset": 16,
      "type": "",
      "position": 3
    }
  ]
}

articleID.keyword

GET /forum/_analyze
{
  "field": "articleID.keyword",
  "text": "XHDK-A-1293-#fJ3"
}

相应结果

{
  "tokens": [
    {
      "token": "XHDK-A-1293-#fJ3",
      "start_offset": 0,
      "end_offset": 16,
      "type": "word",
      "position": 0
    }
  ]
}
（2）根据用户ID搜索帖子 
GET /forum/article/_search
{
    "query" : {
        "constant_score" : { 
            "filter" : {
                "term" : { 
                    "userID" : 1
                }
            }
        }
    }
}

响应结果

{
  "took": 18,
  "timed_out": false,
  "_shards": {
    "total": 5,
    "successful": 5,
    "skipped": 0,
    "failed": 0
  },
  "hits": {
    "total": 2,
    "max_score": 1,
    "hits": [
      {
        "_index": "forum",
        "_type": "article",
        "_id": "2",
        "_score": 1,
        "_source": {
          "articleID": "KDKE-B-9947-#kL5",
          "userID": 1,
          "hidden": false,
          "postDate": "2017-01-02"
        }
      },
      {
        "_index": "forum",
        "_type": "article",
        "_id": "1",
        "_score": 1,
        "_source": {
          "articleID": "XHDK-A-1293-#fJ3",
          "userID": 1,
          "hidden": false,
          "postDate": "2017-01-01"
        }
      }
    ]
  }
}

term filter/query：对搜索文本不分词，直接拿去倒排索引中匹配，你输入的是什么，就去匹配什么 比如说，如果对搜索文本进行分词的话，“helle world” --> “hello”和“world”，两个词分别去倒排索引中匹配 term：“hello world” --> “hello world”，直接去倒排索引中匹配“hello world”

constant_score :不关心相关度分数

（3）搜索没有隐藏的帖子 
GET /forum/article/_search
{
    "query" : {
        "constant_score" : { 
            "filter" : {
                "term" : { 
                    "hidden" : false
                }
            }
        }
    }
}

响应结果

{
  "took": 3,
  "timed_out": false,
  "_shards": {
    "total": 5,
    "successful": 5,
    "skipped": 0,
    "failed": 0
  },
  "hits": {
    "total": 3,
    "max_score": 1,
    "hits": [
      {
        "_index": "forum",
        "_type": "article",
        "_id": "2",
        "_score": 1,
        "_source": {
          "articleID": "KDKE-B-9947-#kL5",
          "userID": 1,
          "hidden": false,
          "postDate": "2017-01-02"
        }
      },
      {
        "_index": "forum",
        "_type": "article",
        "_id": "1",
        "_score": 1,
        "_source": {
          "articleID": "XHDK-A-1293-#fJ3",
          "userID": 1,
          "hidden": false,
          "postDate": "2017-01-01"
        }
      },
      {
        "_index": "forum",
        "_type": "article",
        "_id": "3",
        "_score": 1,
        "_source": {
          "articleID": "JODL-X-1937-#pV7",
          "userID": 2,
          "hidden": false,
          "postDate": "2017-01-01"
        }
      }
    ]
  }
}
（4）根据发帖日期搜索帖子 
GET /forum/article/_search
{
    "query" : {
        "constant_score" : { 
            "filter" : {
                "term" : { 
                    "postDate" : "2017-01-01"
                }
            }
        }
    }
}

响应结果

{
  "took": 21,
  "timed_out": false,
  "_shards": {
    "total": 5,
    "successful": 5,
    "skipped": 0,
    "failed": 0
  },
  "hits": {
    "total": 2,
    "max_score": 1,
    "hits": [
      {
        "_index": "forum",
        "_type": "article",
        "_id": "1",
        "_score": 1,
        "_source": {
          "articleID": "XHDK-A-1293-#fJ3",
          "userID": 1,
          "hidden": false,
          "postDate": "2017-01-01"
        }
      },
      {
        "_index": "forum",
        "_type": "article",
        "_id": "3",
        "_score": 1,
        "_source": {
          "articleID": "JODL-X-1937-#pV7",
          "userID": 2,
          "hidden": false,
          "postDate": "2017-01-01"
        }
      }
    ]
  }
}
（5）根据帖子ID搜索帖子 
GET /forum/article/_search
{
    "query" : {
        "constant_score" : { 
            "filter" : {
                "term" : { 
                    "articleID" : "XHDK-A-1293-#fJ3"
                }
            }
        }
    }
}

响应结果

{
  "took": 0,
  "timed_out": false,
  "_shards": {
    "total": 5,
    "successful": 5,
    "skipped": 0,
    "failed": 0
  },
  "hits": {
    "total": 0,
    "max_score": null,
    "hits": []
  }
}

为什么什么都没搜到呢？

（6）查看分词 
GET /forum/_analyze
{
  "field": "articleID",
  "text": "XHDK-A-1293-#fJ3"
}

响应结果

{
  "tokens": [
    {
      "token": "xhdk",
      "start_offset": 0,
      "end_offset": 4,
      "type": "",
      "position": 0
    },
    {
      "token": "a",
      "start_offset": 5,
      "end_offset": 6,
      "type": "",
      "position": 1
    },
    {
      "token": "1293",
      "start_offset": 7,
      "end_offset": 11,
      "type": "",
      "position": 2
    },
    {
      "token": "fj3",
      "start_offset": 13,
      "end_offset": 16,
      "type": "",
      "position": 3
    }
  ]
}

默认是analyzed的text类型的field，建立倒排索引的时候，就会对所有的articleID分词，分词以后，原本的articleID就没有了，只有分词后的各个word存在于倒排索引中。

articleID建立索引的时候，XHDK-A-1293-#fJ3 --> xhdk，a，1293，fj3

但是term，是不对搜索文本分词的，XHDK-A-1293-#fJ3 --> XHDK-A-1293-#fJ3；

所以什么都没搜到。

可以使用articleID.keyword，是不分词的

GET /forum/article/_search
{
    "query" : {
        "constant_score" : { 
            "filter" : {
                "term" : { 
                    "articleID.keyword" : "XHDK-A-1293-#fJ3"
                }
            }
        }
    }
}

响应结果

{
  "took": 0,
  "timed_out": false,
  "_shards": {
    "total": 5,
    "successful": 5,
    "skipped": 0,
    "failed": 0
  },
  "hits": {
    "total": 1,
    "max_score": 1,
    "hits": [
      {
        "_index": "forum",
        "_type": "article",
        "_id": "1",
        "_score": 1,
        "_source": {
          "articleID": "XHDK-A-1293-#fJ3",
          "userID": 1,
          "hidden": false,
          "postDate": "2017-01-01"
        }
      }
    ]
  }
}

articleID.keyword，是es最新版本内置建立的field，就是不分词的。所以一个articleID过来的时候，会建立两次索引，一次是自己本身，是要分词的，分词后放入倒排索引；另外一次是基于articleID.keyword，不分词，保留256个字符最多，直接一个字符串放入倒排索引中。

所以term filter，对text过滤，可以考虑使用内置的field.keyword来进行匹配。但是有个问题，默认就保留256个字符。

所以尽可能还是自己去手动建立索引，指定not_analyzed吧。在最新版本的es中，不需要指定not_analyzed也可以，将type=keyword即可。

（7）重建索引

将articleID设置type=keyword

1删除索引

DELETE /forum

响应结果

{
  "acknowledged": true
}

2手动创建索引

PUT /forum
{
  "mappings": {
    "article": {
      "properties": {
        "articleID": {
          "type": "keyword"
        }
      }
    }
  }
}

响应结果

{
  "acknowledged": true,
  "shards_acknowledged": true,
  "index": "forum"
}

填充数据

POST /forum/article/_bulk
{ "index": { "_id": 1 }}
{ "articleID" : "XHDK-A-1293-#fJ3", "userID" : 1, "hidden": false, "postDate": "2017-01-01" }
{ "index": { "_id": 2 }}
{ "articleID" : "KDKE-B-9947-#kL5", "userID" : 1, "hidden": false, "postDate": "2017-01-02" }
{ "index": { "_id": 3 }}
{ "articleID" : "JODL-X-1937-#pV7", "userID" : 2, "hidden": false, "postDate": "2017-01-01" }
{ "index": { "_id": 4 }}
{ "articleID" : "QQPX-R-3956-#aD8", "userID" : 2, "hidden": true, "postDate": "2017-01-02" }

响应结果

POST /forum/article/_bulk
{ "index": { "_id": 1 }}
{ "articleID" : "XHDK-A-1293-#fJ3", "userID" : 1, "hidden": false, "postDate": "2017-01-01" }
{ "index": { "_id": 2 }}
{ "articleID" : "KDKE-B-9947-#kL5", "userID" : 1, "hidden": false, "postDate": "2017-01-02" }
{ "index": { "_id": 3 }}
{ "articleID" : "JODL-X-1937-#pV7", "userID" : 2, "hidden": false, "postDate": "2017-01-01" }
{ "index": { "_id": 4 }}
{ "articleID" : "QQPX-R-3956-#aD8", "userID" : 2, "hidden": true, "postDate": "2017-01-02" }
（8）重新根据帖子ID进行搜索 
GET /forum/article/_search
{
    "query" : {
        "constant_score" : { 
            "filter" : {
                "term" : { 
                    "articleID" : "XHDK-A-1293-#fJ3"
                }
            }
        }
    }
}

响应结果

{
  "took": 0,
  "timed_out": false,
  "_shards": {
    "total": 5,
    "successful": 5,
    "skipped": 0,
    "failed": 0
  },
  "hits": {
    "total": 1,
    "max_score": 1,
    "hits": [
      {
        "_index": "forum",
        "_type": "article",
        "_id": "1",
        "_score": 1,
        "_source": {
          "articleID": "XHDK-A-1293-#fJ3",
          "userID": 1,
          "hidden": false,
          "postDate": "2017-01-01"
        }
      }
    ]
  }
}

由于重建索引手动设置了articleID的mapping 所以articleID.keyword已经不存在了

GET forum/_mapping/article

相应结果

{
  "forum": {
    "mappings": {
      "article": {
        "properties": {
          "articleID": {
            "type": "keyword"
          },
          "hidden": {
            "type": "boolean"
          },
          "postDate": {
            "type": "date"
          },
          "userID": {
            "type": "long"
          }
        }
      }
    }
  }
}
总结

（1）term filter：根据exact value进行搜索，对数字、boolean、date天然支持 （2）text需要建索引时指定为not_analyzed，才能用term query。在最新版本的es中，不需要指定not_analyzed也可以，将type=keyword即可。 （3）term filter相当于SQL中的单个where条件

select *
from forum.article
where articleID='XHDK-A-1293-#fJ3'
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