1. 準(zhǔn)備數(shù)據(jù)

PUT h1/doc/1
{
  "name": "rose",
  "gender": "female",
  "age": 18,
  "tags": ["白", "漂亮", "高"]
}

PUT h1/doc/2
{
  "name": "lila",
  "gender": "female",
  "age": 18,
  "tags": ["黑", "漂亮", "高"]
}

PUT h1/doc/3
{
  "name": "john",
  "gender": "male",
  "age": 18,
  "tags": ["黑", "帥", "高"]
}

運(yùn)行結(jié)果：

{
  "_index" : "h1",
  "_type" : "doc",
  "_id" : "1",
  "_version" : 1,
  "result" : "created",
  "_shards" : {
    "total" : 2,
    "successful" : 1,
    "failed" : 0
  },
  "_seq_no" : 0,
  "_primary_term" : 1
}

2. match 查詢

2.1 match 按條件查詢

# 查詢性別是男性的結(jié)果
GET h1/doc/_search
{
  "query": {
    "match": {
      "gender": "male"
    }
  }
}

查詢結(jié)果：

{
  "took" : 59,
  "timed_out" : false,
  "_shards" : {
    "total" : 5,
    "successful" : 5,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : 1,
    "max_score" : 0.2876821,
    "hits" : [
      {
        "_index" : "h1",		# 索引
        "_type" : "doc",		# 文檔類型
        "_id" : "3",			# 文檔唯一 id
        "_score" : 0.2876821,	# 打分機(jī)制打出來的分?jǐn)?shù)
        "_source" : {			# 查詢結(jié)果
          "name" : "john",
          "gender" : "male",
          "age" : 18,
          "tags" : [
            "黑",
            "帥",
            "高"
          ]
        }
      }
    ]
  }
}

2.2 match_all 查詢?nèi)?/h3>

# 查詢 h1 中所有文檔
GET h1/doc/_search
{
  "query": {
    "match_all": {}
  }
}

match_all的值為空，表示沒有查詢條件，那就是查詢?nèi)俊＞拖?code>select * from table_name 一樣。

查詢結(jié)果：

{
  "took" : 2,
  "timed_out" : false,
  "_shards" : {
    "total" : 5,
    "successful" : 5,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : 3,
    "max_score" : 1.0,
    "hits" : [
      {
        "_index" : "h1",
        "_type" : "doc",
        "_id" : "2",
        "_score" : 1.0,
        "_source" : {
          "name" : "lila",
          "gender" : "female",
          "age" : 18,
          "tags" : [
            "黑",
            "漂亮",
            "高"
          ]
        }
      },
      {
        "_index" : "h1",
        "_type" : "doc",
        "_id" : "1",
        "_score" : 1.0,
        "_source" : {
          "name" : "rose",
          "gender" : "female",
          "age" : 18,
          "tags" : [
            "白",
            "漂亮",
            "高"
          ]
        }
      },
      {
        "_index" : "h1",
        "_type" : "doc",
        "_id" : "3",
        "_score" : 1.0,
        "_source" : {
          "name" : "john",
          "gender" : "male",
          "age" : 18,
          "tags" : [
            "黑",
            "帥",
            "高"
          ]
        }
      }
    ]
  }
}

2.3 match_phrase 短語查詢

match 查詢時(shí)散列映射，包含了我們希望搜索的字段和字符串，即只要文檔中有我們希望的那個(gè)關(guān)鍵字，但也會(huì)帶來一些問題。

es 會(huì)將文檔中的內(nèi)容進(jìn)行拆分，對于英文來說可能沒有太大的影響，但是中文短語就不太適用，一旦拆分就會(huì)失去原有的含義，比如以下：

1、準(zhǔn)備數(shù)據(jù)：

PUT t1/doc/1
{
  "title": "中國是世界上人口最多的國家"
}

PUT t1/doc/2
{
  "title": "美國是世界上軍事實(shí)力最強(qiáng)大的國家"
}

PUT t1/doc/3
{
  "title": "北京是中國的首都"
}

2、先使用 match 查詢含有中國的文檔：

GET t1/doc/_search
{
  "query": {
    "match": {
      "title": "中國"
    }
  }
}

查詢結(jié)果：

{
  "took" : 5,
  "timed_out" : false,
  "_shards" : {
    "total" : 5,
    "successful" : 5,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : 3,
    "max_score" : 0.68324494,
    "hits" : [
      {
        "_index" : "t1",
        "_type" : "doc",
        "_id" : "1",
        "_score" : 0.68324494,
        "_source" : {
          "title" : "中國是世界上人口最多的國家"
        }
      },
      {
        "_index" : "t1",
        "_type" : "doc",
        "_id" : "3",
        "_score" : 0.5753642,
        "_source" : {
          "title" : "北京是中國的首都"
        }
      },
      {
        "_index" : "t1",
        "_type" : "doc",
        "_id" : "2",
        "_score" : 0.39556286,
        "_source" : {
          "title" : "美國是世界上軍事實(shí)力最強(qiáng)大的國家"
        }
      }
    ]
  }
}

發(fā)現(xiàn)三篇文檔都被返回，與我們的預(yù)期有偏差；這是因?yàn)?title 中的內(nèi)容被拆分成一個(gè)個(gè)單獨(dú)的字，而 id=2 的文檔包含了 國 字也符合，所以也被返回了。es 自帶的中文分詞處理不太好用，后面可以使用 ik 中文分詞器來處理。

3、match_phrase 查詢短語

不過可以使用 match_phrase 來匹配短語，將上面的 match 換成 match_phrase 試試：

# 短語查詢
GET t1/doc/_search
{
  "query": {
    "match_phrase": {
      "title": "中國"
    }
  }
}

查詢結(jié)果：

{
  "took" : 2,
  "timed_out" : false,
  "_shards" : {
    "total" : 5,
    "successful" : 5,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : 2,
    "max_score" : 0.5753642,
    "hits" : [
      {
        "_index" : "t1",
        "_type" : "doc",
        "_id" : "1",
        "_score" : 0.5753642,
        "_source" : {
          "title" : "中國是世界上人口最多的國家"
        }
      },
      {
        "_index" : "t1",
        "_type" : "doc",
        "_id" : "3",
        "_score" : 0.5753642,
        "_source" : {
          "title" : "北京是中國的首都"
        }
      }
    ]
  }
}

4、slop 間隔查詢

當(dāng)我們要查詢的短語，中間有別的詞時(shí)，可以使用 slop 來跳過。比如上述要查詢 中國世界，這個(gè)短語中間被 是 隔開了，這時(shí)可以使用 slop 來跳過，相當(dāng)于正則中的中國.*?世界：

# 短語查詢，查詢中國世界，加 slop 
GET t1/doc/_search
{
  "query": {
    "match_phrase": {
      "title": {
        "query": "中國世界",
        "slop": 1
      }
    }
  }
}

查詢結(jié)果：

{
  "took" : 4,
  "timed_out" : false,
  "_shards" : {
    "total" : 5,
    "successful" : 5,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : 1,
    "max_score" : 0.7445889,
    "hits" : [
      {
        "_index" : "t1",
        "_type" : "doc",
        "_id" : "1",
        "_score" : 0.7445889,
        "_source" : {
          "title" : "中國是世界上人口最多的國家"
        }
      }
    ]
  }
}

2.4 match_phrase_prefix 最左前綴查詢

場景：當(dāng)我們要查詢的詞只能想起前幾個(gè)字符時(shí)

# 最左前綴查詢，查詢名字為 rose 的文檔
GET h1/doc/_search
{
  "query": {
    "match_phrase_prefix": {
      "name": "ro"
    }
  }
}

查詢結(jié)果：

{
  "took" : 1,
  "timed_out" : false,
  "_shards" : {
    "total" : 5,
    "successful" : 5,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : 1,
    "max_score" : 0.2876821,
    "hits" : [
      {
        "_index" : "h1",
        "_type" : "doc",
        "_id" : "1",
        "_score" : 0.2876821,
        "_source" : {
          "name" : "rose",
          "gender" : "female",
          "age" : 18,
          "tags" : [
            "白",
            "漂亮",
            "高"
          ]
        }
      }
    ]
  }
}

限制結(jié)果集

最左前綴查詢很費(fèi)性能，返回的是一個(gè)很大的集合，一般很少使用，使用的時(shí)候最好對結(jié)果集進(jìn)行限制，max_expansions 參數(shù)可以設(shè)置最大的前綴擴(kuò)展數(shù)量：

# 最左前綴查詢
GET h1/doc/_search
{
  "query": {
    "match_phrase_prefix": {
      "gender": {
        "query": "fe",
        "max_expansions": 1
      }
    }
  }
}

查詢結(jié)果：

{
  "took" : 2,
  "timed_out" : false,
  "_shards" : {
    "total" : 5,
    "successful" : 5,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : 2,
    "max_score" : 0.2876821,
    "hits" : [
      {
        "_index" : "h1",
        "_type" : "doc",
        "_id" : "2",
        "_score" : 0.2876821,
        "_source" : {
          "name" : "lila",
          "gender" : "female",
          "age" : 18,
          "tags" : [
            "黑",
            "漂亮",
            "高"
          ]
        }
      },
      {
        "_index" : "h1",
        "_type" : "doc",
        "_id" : "1",
        "_score" : 0.2876821,
        "_source" : {
          "name" : "rose",
          "gender" : "female",
          "age" : 18,
          "tags" : [
            "白",
            "漂亮",
            "高"
          ]
        }
      }
    ]
  }
}

2.5 multi_match 多字段查詢

1、準(zhǔn)備數(shù)據(jù)：

# 多字段查詢
PUT t3/doc/1
{
  "title": "maggie is beautiful girl",
  "desc": "beautiful girl you are beautiful so"
}

PUT t3/doc/2
{
  "title": "beautiful beach",
  "desc": "I like basking on the beach,and you? beautiful girl"
}

2、查詢包含 beautiful 字段的文檔：

GET t3/doc/_search
{
  "query": {
    "multi_match": {
      "query": "beautiful",				# 要查詢的詞
      "fields": ["desc", "title"]		# 要查詢的字段
    }
  }
}

還可以當(dāng)做 match_phrase和match_phrase_prefix使用，只需要指定type類型即可：

GET t3/doc/_search
{
  "query": {
    "multi_match": {
      "query": "gi",
      "fields": ["title"],
      "type": "phrase_prefix"
    }
  }
}

GET t3/doc/_search
{
  "query": {
    "multi_match": {
      "query": "girl",
      "fields": ["title"],
      "type": "phrase"
    }
  }
}

3. term 查詢

3.1 初始 es 的分析器

term 查詢用于精確查詢，但是不適用于 text 類型的字段查詢。

在此之前我們先了解 es 的分析機(jī)制，默認(rèn)的標(biāo)準(zhǔn)分析器會(huì)對文檔進(jìn)行：

• 刪除大多數(shù)的標(biāo)點(diǎn)符號
• 將文檔拆分為單個(gè)詞條，稱為 token
• 將 token 轉(zhuǎn)換為小寫

最后保存到倒排序索引上，而倒排序索引用來查詢，如 Beautiful girl 經(jīng)過分析后是這樣的：

POST _analyze
{
  "analyzer": "standard",
  "text": "Beautiful girl"
}


# 結(jié)果，轉(zhuǎn)換為小寫了
{
  "tokens" : [
    {
      "token" : "beautiful",
      "start_offset" : 0,
      "end_offset" : 9,
      "type" : "<ALPHANUM>",
      "position" : 0
    },
    {
      "token" : "girl",
      "start_offset" : 10,
      "end_offset" : 14,
      "type" : "<ALPHANUM>",
      "position" : 1
    }
  ]
}

3.2 term 查詢

1、準(zhǔn)備數(shù)據(jù)：

# 創(chuàng)建索引，自定義 mapping，后面會(huì)講到
PUT t4
{
  "mappings": {
    "doc":{
      "properties":{
        "t1":{
          "type": "text"    # 定義字段類型為 text
        }
      }
    }
  }
}

PUT t4/doc/1
{
  "t1": "Beautiful girl!"
}

PUT t4/doc/2
{
  "t1": "sexy girl!"
}

2、match 查詢：

GET t4/doc/_search
{
  "query": {
    "match": {
      "t1": "Beautiful girl!"
    }
  }
}

經(jīng)過分析后，會(huì)得到 beautiful、girl 兩個(gè) token，然后再去 t4 索引上去查詢，會(huì)返回兩篇文檔：

{
  "took" : 1,
  "timed_out" : false,
  "_shards" : {
    "total" : 5,
    "successful" : 5,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : 2,
    "max_score" : 0.5753642,
    "hits" : [
      {
        "_index" : "t4",
        "_type" : "doc",
        "_id" : "1",
        "_score" : 0.5753642,
        "_source" : {
          "title" : "Beautiful girl"
        }
      },
      {
        "_index" : "t4",
        "_type" : "doc",
        "_id" : "2",
        "_score" : 0.2876821,
        "_source" : {
          "title" : "sex girl"
        }
      }
    ]
  }
}

3、但是我們只想精確查詢包含 Beautiful girl 的文檔，這時(shí)就需要使用 term 來精確查詢：

GET t4/doc/_search
{
  "query": {
    "term": {
      "title": "beautiful"
    }
  }
}

查詢結(jié)果：

{
  "took" : 0,
  "timed_out" : false,
  "_shards" : {
    "total" : 5,
    "successful" : 5,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : 1,
    "max_score" : 0.2876821,
    "hits" : [
      {
        "_index" : "t4",
        "_type" : "doc",
        "_id" : "1",
        "_score" : 0.2876821,
        "_source" : {
          "title" : "Beautiful girl"
        }
      }
    ]
  }
}

注意：term 查詢不適用于類型是 text 的字段，可以使用 match 查詢；另外 Beautiful 經(jīng)過分析后變?yōu)?beautiful，查詢時(shí)使用 Beautiful 是查詢不到的~

3.3 查詢多個(gè)

精確查詢多個(gè)字段：文章來源地址http://www.zghlxwxcb.cn/news/detail-418513.html

GET t4/doc/_search
{
  "query": {
    "terms": {
      "title": ["beautiful", "sex"]
    }
  }
}

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