ES基本查詢語句教程

本文轉載自查看原文 2020-05-27 08:02 57673 大數據（HBase/Hadoop/ES）

前言

es是什么？
es是基於Apache Lucene的開源分布式（全文）搜索引擎，，提供簡單的RESTful API來隱藏Lucene的復雜性。
es除了全文搜索引擎之外，還可以這樣描述它：
1、分布式的實時文件存儲，每個字段都被索引並可被搜索
2、分布式的實時分析搜索引擎
3、可以擴展到成百上千台服務器，處理PB級結構化或非結構化數據。
ES的數據組織類比

Relational DB	Elasticsearch
數據庫（database）	索引（indices）
表（tables）	types
行（rows）	documents
字段（columns）	fields

mac安裝ES

- 1、更新brew ```brew update``` - 2、安裝java1.8版本 ```brew cask install homebrew/cask-versions/java8``` - 3、安裝ES ```brew install elasticsearch``` - 4、啟動本地ES ```brew services start elasticsearch``` - 5、本地訪問9200端口查看ES安裝 ```http://localhost:9200``` - 6、安裝kibana ```Kibana是ES的一個配套工具，可以讓用戶在網頁中與ES進行交互``` ```brew install kibana``` - 7、本地啟動kibana ```brew services start kibana``` - 8、本地訪問5601端口進入kibana交互界面 ```http://localhost:5601```

一、 ES簡單的增刪改查

1、創建一篇文檔（有則修改，無則創建)

PUT test/doc/2
{
  "name":"wangfei",
  "age":27,
  "desc":"熱天還不讓后人不認同"
}

PUT test/doc/1
{
  "name":"wangjifei",
  "age":27,
  "desc":"薩芬我反胃為范圍額"
}

PUT test/doc/3
{
  "name":"wangyang",
  "age":30,
  "desc":"點在我心內的幾首歌"
}

2、查詢指定索引信息

GET test

3、查詢指定文檔信息

GET test/doc/1
GET test/doc/2

4、查詢對應索引下所有數據

GET test/doc/_search
或
GET test/doc/_search
{
  "query": {
    "match_all": {}
  }
}

5、刪除指定文檔

DELETE test/doc/3

6、刪除索引

DELETE test

7、修改指定文檔方式

修改時，不指定的屬性會自動覆蓋，只保留指定的屬性(不正確的修改指定文檔方式)

PUT test/doc/1
{
  "name":"王計飛"
}

使用POST命令，在id后面跟_update，要修改的內容放到doc文檔（屬性）中(正確的修改指定文檔方式)

POST test/doc/1/_update
{
  "doc":{
    "desc":"生活就像 茫茫海上"
  }
}

二、ES查詢的兩種方式

1、查詢字符串搜索

GET test/doc/_search?q=name:wangfei

2、結構化查詢(單字段查詢,不能多字段組合查詢)

GET test/doc/_search
{
  "query":{
    "match":{
      "name":"wang"
    }
  }
}

三、match系列之操作

1、match系列之match_all (查詢全部)

GET test/doc/_search
{
  "query":{
    "match_all": {
    }
  }
}

2、match系列之match_phrase（短語查詢）

准備數據

PUT test1/doc/1
{
  "title": "中國是世界上人口最多的國家"
}
PUT test1/doc/2
{
  "title": "美國是世界上軍事實力最強大的國家"
}
PUT test1/doc/3
{
  "title": "北京是中國的首都"
}

查詢語句

GET test1/doc/_search { "query":{ "match":{ "title":"中國" } } } >>>輸出結果 { "took" : 241, "timed_out" : false, "_shards" : { "total" : 5, "successful" : 5, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : 3, "max_score" : 0.68324494, "hits" : [ { "_index" : "test1", "_type" : "doc", "_id" : "1", "_score" : 0.68324494, "_source" : { "title" : "中國是世界上人口最多的國家" } }, { "_index" : "test1", "_type" : "doc", "_id" : "3", "_score" : 0.5753642, "_source" : { "title" : "北京是中國的首都" } }, { "_index" : "test1", "_type" : "doc", "_id" : "2", "_score" : 0.39556286, "_source" : { "title" : "美國是世界上軍事實力最強大的國家" } } ] } }

通過觀察結果可以發現，雖然如期的返回了中國的文檔。但是卻把和美國的文檔也返回了，這並不是我們想要的。是怎么回事呢？因為這是elasticsearch在內部對文檔做分詞的時候，對於中文來說，就是一個字一個字分的，所以，我們搜中國，中和國都符合條件，返回，而美國的國也符合。而我們認為中國是個短語，是一個有具體含義的詞。所以elasticsearch在處理中文分詞方面比較弱勢。后面會講針對中文的插件。但目前我們還有辦法解決，那就是使用短語查詢用match_phrase

GET test1/doc/_search { "query":{ "match_phrase": { "title": "中國" } } } >>>查詢結果 { "took" : 10, "timed_out" : false, "_shards" : { "total" : 5, "successful" : 5, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : 2, "max_score" : 0.5753642, "hits" : [ { "_index" : "test1", "_type" : "doc", "_id" : "1", "_score" : 0.5753642, "_source" : { "title" : "中國是世界上人口最多的國家" } }, { "_index" : "test1", "_type" : "doc", "_id" : "3", "_score" : 0.5753642, "_source" : { "title" : "北京是中國的首都" } } ] } }

我們搜索中國和世界這兩個指定詞組時，但又不清楚兩個詞組之間有多少別的詞間隔。那么在搜的時候就要留有一些余地。這時就要用到了slop了。相當於正則中的中國.*?世界。這個間隔默認為0

GET test1/doc/_search { "query":{ "match_phrase": { "title": { "query": "中國世界", "slop":2 } } } } >>>查詢結果 { "took" : 23, "timed_out" : false, "_shards" : { "total" : 5, "successful" : 5, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : 1, "max_score" : 0.7445889, "hits" : [ { "_index" : "test1", "_type" : "doc", "_id" : "1", "_score" : 0.7445889, "_source" : { "title" : "中國是世界上人口最多的國家" } } ] } }

3、match系列之match_phrase_prefix（最左前綴查詢）智能搜索--以什么開頭

數據准備

PUT test2/doc/1
{
  "title": "prefix1",
  "desc": "beautiful girl you are beautiful so"
}

PUT test2/doc/2
{
  "title": "beautiful",
  "desc": "I like basking on the beach"
}

搜索特定英文開頭的數據

查詢語句

GET test2/doc/_search { "query": { "match_phrase_prefix": { "desc": "bea" } } } >>>查詢結果（） { "took" : 5, "timed_out" : false, "_shards" : { "total" : 5, "successful" : 5, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : 2, "max_score" : 0.39556286, "hits" : [ { "_index" : "test2", "_type" : "doc", "_id" : "1", "_score" : 0.39556286, "_source" : { "title" : "prefix1", "desc" : "beautiful girl you are beautiful so" } }, { "_index" : "test2", "_type" : "doc", "_id" : "2", "_score" : 0.2876821, "_source" : { "title" : "beautiful", "desc" : "I like basking on the beach" } } ] } } 查詢短語 GET test2/doc/_search { "query": { "match_phrase_prefix": { "desc": "you are bea" } } } >>>查詢結果 { "took" : 28, "timed_out" : false, "_shards" : { "total" : 5, "successful" : 5, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : 1, "max_score" : 0.8630463, "hits" : [ { "_index" : "test2", "_type" : "doc", "_id" : "1", "_score" : 0.8630463, "_source" : { "title" : "prefix1", "desc" : "beautiful girl you are beautiful so" } } ] } }

max_expansions 參數理解前綴查詢會非常的影響性能，要對結果集進行限制，就加上這個參數。

GET test2/doc/_search
{
  "query": {
    "match_phrase_prefix": {
      "desc": {
        "query": "bea",
        "max_expansions":1
      }
    }
  }
}

4、match系列之multi_match（多字段查詢)

multi_match是要在多個字段中查詢同一個關鍵字除此之外，mulit_match甚至可以當做match_phrase和match_phrase_prefix使用，只需要指定type類型即可

GET test2/doc/_search { "query": { "multi_match": { "query": "beautiful", "fields": ["title","desc"] } } } >>查詢結果 { "took" : 43, "timed_out" : false, "_shards" : { "total" : 5, "successful" : 5, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : 2, "max_score" : 0.39556286, "hits" : [ { "_index" : "test2", "_type" : "doc", "_id" : "1", "_score" : 0.39556286, "_source" : { "title" : "prefix1", "desc" : "beautiful girl you are beautiful so" } }, { "_index" : "test2", "_type" : "doc", "_id" : "2", "_score" : 0.2876821, "_source" : { "title" : "beautiful", "desc" : "I like basking on the beach" } } ] } }

當設置屬性 type:phrase 時等同於短語查詢

GET test1/doc/_search { "query": { "multi_match": { "query": "中國", "fields": ["title"], "type": "phrase" } } } >>>查詢結果 { "took" : 47, "timed_out" : false, "_shards" : { "total" : 5, "successful" : 5, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : 2, "max_score" : 0.5753642, "hits" : [ { "_index" : "test1", "_type" : "doc", "_id" : "1", "_score" : 0.5753642, "_source" : { "title" : "中國是世界上人口最多的國家" } }, { "_index" : "test1", "_type" : "doc", "_id" : "3", "_score" : 0.5753642, "_source" : { "title" : "北京是中國的首都" } } ] } }

當設置屬性 type:phrase_prefix時等同於最左前綴查詢

GET test2/doc/_search { "query": { "multi_match": { "query": "bea", "fields": ["desc"], "type": "phrase_prefix" } } } >>查詢結果 { "took" : 5, "timed_out" : false, "_shards" : { "total" : 5, "successful" : 5, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : 2, "max_score" : 0.5753642, "hits" : [ { "_index" : "test1", "_type" : "doc", "_id" : "1", "_score" : 0.5753642, "_source" : { "title" : "中國是世界上人口最多的國家" } }, { "_index" : "test1", "_type" : "doc", "_id" : "3", "_score" : 0.5753642, "_source" : { "title" : "北京是中國的首都" } } ] } }

match 查詢相關總結

1、match：返回所有匹配的分詞。

2、match_all：查詢全部。

3、match_phrase：短語查詢，在match的基礎上進一步查詢詞組，可以指定slop分詞間隔。

4、match_phrase_prefix：前綴查詢，根據短語中最后一個詞組做前綴匹配，可以應用於搜索提示，但注意和max_expanions搭配。其實默認是50.......

5、multi_match：多字段查詢，使用相當的靈活，可以完成match_phrase和match_phrase_prefix的工作。

四、ES的排序查詢

es 6.8.4版本中，需要分詞的字段不可以直接排序，比如：text類型，如果想要對這類字段進行排序，需要特別設置：對字段索引兩次，一次索引分詞（用於搜索）一次索引不分詞（用於排序），es默認生成的text類型字段就是通過這樣的方法實現可排序的。

text類型字段排序問題
倒敘排序

GET test/doc/_search { "query": { "match_all": {} }, "sort": [ { "age": { "order": "desc" } } ] } >>排序結果 { "took" : 152, "timed_out" : false, "_shards" : { "total" : 5, "successful" : 5, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : 3, "max_score" : null, "hits" : [ { "_index" : "test", "_type" : "doc", "_id" : "3", "_score" : null, "_source" : { "name" : "wangyang", "age" : 30, "desc" : "點在我心內的幾首歌" }, "sort" : [ 30 ] }, { "_index" : "test", "_type" : "doc", "_id" : "2", "_score" : null, "_source" : { "name" : "wangfei", "age" : 27, "desc" : "熱天還不讓后人不認同" }, "sort" : [ 27 ] }, { "_index" : "test", "_type" : "doc", "_id" : "1", "_score" : null, "_source" : { "name" : "wangjifei", "age" : 27, "desc" : "生活就像 茫茫海上" }, "sort" : [ 27 ] } ] } }

升序排序

GET test/doc/_search
{
  "query": {
    "match_all": {}
  },
  "sort": [
    {
      "age": {
        "order": "asc"
      }
    }
  ]
}

五、ES的分頁查詢

from：從哪開始查 size：返回幾條結果

GET test/doc/_search { "query": { "match_phrase_prefix": { "name": "wang" } }, "from": 0, "size": 1 } >>查詢結果 { "took" : 3, "timed_out" : false, "_shards" : { "total" : 5, "successful" : 5, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : 3, "max_score" : 0.2876821, "hits" : [ { "_index" : "test", "_type" : "doc", "_id" : "2", "_score" : 0.2876821, "_source" : { "name" : "wangfei", "age" : 27, "desc" : "熱天還不讓后人不認同" } } ] } }

六、ES的bool查詢 (must、should)

must (must字段對應的是個列表，也就是說可以有多個並列的查詢條件，一個文檔滿足各個子條件后才最終返回)

#### 單條件查詢 GET test/doc/_search { "query": { "bool": { "must": [ { "match": { "name": "wangfei" } } ] } } } >>查詢結果 { "took" : 4, "timed_out" : false, "_shards" : { "total" : 5, "successful" : 5, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : 1, "max_score" : 0.2876821, "hits" : [ { "_index" : "test", "_type" : "doc", "_id" : "2", "_score" : 0.2876821, "_source" : { "name" : "wangfei", "age" : 27, "desc" : "熱天還不讓后人不認同" } } ] } }

#### 多條件組合查詢 GET test/doc/_search { "query": { "bool": { "must": [ { "match": { "name": "wanggfei" } },{ "match": { "age": 25 } } ] } } } >>查詢結果 { "took" : 21, "timed_out" : false, "_shards" : { "total" : 5, "successful" : 5, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : 0, "max_score" : null, "hits" : [ ] } }

should (只要符合其中一個條件就返回)

GET test/doc/_search { "query": { "bool": { "should": [ { "match": { "name": "wangjifei" } },{ "match": { "age": 27 } } ] } } } >>查詢結果 { "took" : 34, "timed_out" : false, "_shards" : { "total" : 5, "successful" : 5, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : 2, "max_score" : 1.287682, "hits" : [ { "_index" : "test", "_type" : "doc", "_id" : "1", "_score" : 1.287682, "_source" : { "name" : "wangjifei", "age" : 27, "desc" : "生活就像 茫茫海上" } }, { "_index" : "test", "_type" : "doc", "_id" : "2", "_score" : 1.0, "_source" : { "name" : "wangfei", "age" : 27, "desc" : "熱天還不讓后人不認同" } } ] } }

must_not 顧名思義

GET test/doc/_search { "query": { "bool": { "must_not": [ { "match": { "name": "wangjifei" } },{ "match": { "age": 27 } } ] } } } >>查詢結果 { "took" : 13, "timed_out" : false, "_shards" : { "total" : 5, "successful" : 5, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : 1, "max_score" : 1.0, "hits" : [ { "_index" : "test", "_type" : "doc", "_id" : "3", "_score" : 1.0, "_source" : { "name" : "wangyang", "age" : 30, "desc" : "點在我心內的幾首歌" } } ] } }

filter(條件過濾查詢，過濾條件的范圍用range表示gt表示大於、lt表示小於、gte表示大於等於、lte表示小於等於)

GET test/doc/_search { "query": { "bool": { "must": [ { "match": { "name": "wangjifei" } } ], "filter": { "range": { "age": { "gte": 10, "lt": 27 } } } } } } >>查詢結果 { "took" : 33, "timed_out" : false, "_shards" : { "total" : 5, "successful" : 5, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : 0, "max_score" : null, "hits" : [ ] } }

bool查詢總結

must：與關系，相當於關系型數據庫中的 and。

should：或關系，相當於關系型數據庫中的 or。

must_not：非關系，相當於關系型數據庫中的 not。

filter：過濾條件。

range：條件篩選范圍。

gt：大於，相當於關系型數據庫中的 >。

gte：大於等於，相當於關系型數據庫中的 >=。

lt：小於，相當於關系型數據庫中的 <。

lte：小於等於，相當於關系型數據庫中的 <=。

七、ES之查詢結果過濾

####准備數據

PUT test3/doc/1
{
  "name":"顧老二",
  "age":30,
  "from": "gu",
  "desc": "皮膚黑、武器長、性格直",
  "tags": ["黑", "長", "直"]
}

現在，在所有的結果中，我只需要查看name和age兩個屬性,提高查詢效率

GET test3/doc/_search { "query": { "match": { "name": "顧" } }, "_source": ["name","age"] } >>查詢結果 { "took" : 58, "timed_out" : false, "_shards" : { "total" : 5, "successful" : 5, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : 1, "max_score" : 0.2876821, "hits" : [ { "_index" : "test3", "_type" : "doc", "_id" : "1", "_score" : 0.2876821, "_source" : { "name" : "顧老二", "age" : 30 } } ] } }

八、ES之查詢結果高亮顯示

ES的默認高亮顯示

GET test3/doc/_search { "query": { "match": { "name": "顧老二" } }, "highlight": { "fields": { "name": {} } } } >>查詢結果 { "took" : 216, "timed_out" : false, "_shards" : { "total" : 5, "successful" : 5, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : 1, "max_score" : 0.8630463, "hits" : [ { "_index" : "test3", "_type" : "doc", "_id" : "1", "_score" : 0.8630463, "_source" : { "name" : "顧老二", "age" : 30, "from" : "gu", "desc" : "皮膚黑、武器長、性格直", "tags" : [ "黑", "長", "直" ] }, "highlight" : { "name" : [ "<em>顧</em><em>老</em><em>二</em>" ] } } ] } }

ES自定義高亮顯示（在highlight中，pre_tags用來實現我們的自定義標簽的前半部分，在這里，我們也可以為自定義的標簽添加屬性和樣式。post_tags實現標簽的后半部分，組成一個完整的標簽。至於標簽中的內容，則還是交給fields來完成）

GET test3/doc/_search { "query": { "match": { "desc": "性格直" } }, "highlight": { "pre_tags": "<b class='key' style='color:red'>", "post_tags": "</b>", "fields": { "desc": {} } } } >>查詢結果 { "took" : 6, "timed_out" : false, "_shards" : { "total" : 5, "successful" : 5, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : 1, "max_score" : 0.8630463, "hits" : [ { "_index" : "test3", "_type" : "doc", "_id" : "1", "_score" : 0.8630463, "_source" : { "name" : "顧老二", "age" : 30, "from" : "gu", "desc" : "皮膚黑、武器長、性格直", "tags" : [ "黑", "長", "直" ] }, "highlight" : { "desc" : [ "皮膚黑、武器長、<b class='key' style='color:red'>性</b><b class='key' style='color:red'>格</b><b class='key' style='color:red'>直</b>" ] } } ] } }

十、ES之精確查詢與模糊查詢

term查詢查找包含文檔精確的倒排索引指定的詞條。也就是精確查找。

term和match的區別是：match是經過analyer的，也就是說，文檔首先被分析器給處理了。根據不同的分析器，分析的結果也稍顯不同，然后再根據分詞結果進行匹配。term則不經過分詞，它是直接去倒排索引中查找了精確的值了。

#### 准備數據
PUT w1
{
  "mappings": {
    "doc": {
      "properties":{
        "t1":{
          "type": "text"
        },
        "t2": {
          "type": "keyword"
        }
      }
    }
  }
}

PUT w1/doc/1
{
  "t1": "hi single dog",
  "t2": "hi single dog"
}

對比兩者的不同 (結果就不展示出來了，只展示結果的文字敘述)

# t1類型為text，會經過分詞，match查詢時條件也會經過分詞，所以下面兩種查詢都能查到結果 GET w1/doc/_search { "query": { "match": { "t1": "hi single dog" } } } GET w1/doc/_search { "query": { "match": { "t1": "hi" } } } # t2類型為keyword類型，不會經過分詞，match查詢時條件會經過分詞，所以只能當值為"hi single dog"時能查詢到 GET w1/doc/_search { "query": { "match": { "t2": "hi" } } } GET w1/doc/_search { "query": { "match": { "t2": "hi single dog" } } } # t1類型為text，會經過分詞，term查詢時條件不會經過分詞，所以只有當值為"hi"時能查詢到 GET w1/doc/_search { "query": { "term": { "t1": "hi single dog" } } } GET w1/doc/_search { "query": { "term": { "t1": "hi" } } } # t2類型為keyword類型，不會經過分詞，term查詢時條件不會經過分詞，所以只能當值為"hi single dog"時能查詢到 GET w1/doc/_search { "query": { "term": { "t2": "hi single dog" } } } GET w1/doc/_search { "query": { "term": { "t2": "hi" } } }

查找多個精確值（terms）

#### 第一個查詢方式
GET test/doc/_search
{
  "query": {
    "bool": {
      "should": [
        {
          "term": {
            "age":27
          }
        },{
          "term":{
            "age":28
          }
        }
      ]
    }
  }
}


# 第二個查詢方式
GET test/doc/_search
{
  "query": {
    "terms": {
      "age": [
        "27",
        "28"
      ]
    }
  }
}

>>>兩種方式的查詢結果都是一下結果 
{
  "took" : 10,
  "timed_out" : false,
  "_shards" : {
    "total" : 5,
    "successful" : 5,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : 2,
    "max_score" : 1.0,
    "hits" : [
      {
        "_index" : "test",
        "_type" : "doc",
        "_id" : "2",
        "_score" : 1.0,
        "_source" : {
          "name" : "wangfei",
          "age" : 27,
          "desc" : "熱天還不讓后人不認同"
        }
      },
      {
        "_index" : "test",
        "_type" : "doc",
        "_id" : "1",
        "_score" : 1.0,
        "_source" : {
          "name" : "wangjifei",
          "age" : 27,
          "desc" : "生活就像 茫茫海上"
        }
      }
    ]
  }
}

十一、ES的聚合查詢avg、max、min、sum

####  數據准備

PUT zhifou/doc/1
{
  "name":"顧老二",
  "age":30,
  "from": "gu",
  "desc": "皮膚黑、武器長、性格直",
  "tags": ["黑", "長", "直"]
}

PUT zhifou/doc/2
{
  "name":"大娘子",
  "age":18,
  "from":"sheng",
  "desc":"膚白貌美，嬌憨可愛",
  "tags":["白", "富","美"]
}

PUT zhifou/doc/3
{
  "name":"龍套偏房",
  "age":22,
  "from":"gu",
  "desc":"mmp，沒怎么看，不知道怎么形容",
  "tags":["造數據", "真","難"]
}


PUT zhifou/doc/4
{
  "name":"石頭",
  "age":29,
  "from":"gu",
  "desc":"粗中有細，狐假虎威",
  "tags":["粗", "大","猛"]
}

PUT zhifou/doc/5
{
  "name":"魏行首",
  "age":25,
  "from":"廣雲台",
  "desc":"仿佛兮若輕雲之蔽月,飄飄兮若流風之回雪,mmp，最后竟然沒有嫁給顧老二！",
  "tags":["閉月","羞花"]
}

GET zhifou/doc/_search
{
  "query": {
    "match_all": {}
  }
}

需求1、查詢from是gu的人的平均年齡。

GET zhifou/doc/_search { "query": { "match": { "from": "gu" } }, "aggs": { "my_avg": { "avg": { "field": "age" } } }, "_source": ["name", "age"] } >>>查詢結果 { "took" : 83, "timed_out" : false, "_shards" : { "total" : 5, "successful" : 5, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : 3, "max_score" : 0.6931472, "hits" : [ { "_index" : "zhifou", "_type" : "doc", "_id" : "4", "_score" : 0.6931472, "_source" : { "name" : "石頭", "age" : 29 } }, { "_index" : "zhifou", "_type" : "doc", "_id" : "1", "_score" : 0.2876821, "_source" : { "name" : "顧老二", "age" : 30 } }, { "_index" : "zhifou", "_type" : "doc", "_id" : "3", "_score" : 0.2876821, "_source" : { "name" : "龍套偏房", "age" : 22 } } ] }, "aggregations" : { "my_avg" : { "value" : 27.0 } } }

上例中，首先匹配查詢from是gu的數據。在此基礎上做查詢平均值的操作，這里就用到了聚合函數，其語法被封裝在aggs中，而my_avg則是為查詢結果起個別名，封裝了計算出的平均值。那么，要以什么屬性作為條件呢？是age年齡，查年齡的什么呢？是avg，查平均年齡。

如果只想看輸出的值，而不關心輸出的文檔的話可以通過size=0來控制

GET zhifou/doc/_search { "query": { "match": { "from": "gu" } }, "aggs":{ "my_avg":{ "avg": { "field": "age" } } }, "size":0, "_source":["name","age"] } >>>查詢結果 { "took" : 35, "timed_out" : false, "_shards" : { "total" : 5, "successful" : 5, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : 3, "max_score" : 0.0, "hits" : [ ] }, "aggregations" : { "my_avg" : { "value" : 27.0 } } }

需求2、查詢年齡的最大值

GET zhifou/doc/_search { "query": { "match_all": {} }, "aggs": { "my_max": { "max": { "field": "age" } } }, "size": 0, "_source": ["name","age","from"] } >>>查詢結果 { "took" : 10, "timed_out" : false, "_shards" : { "total" : 5, "successful" : 5, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : 5, "max_score" : 0.0, "hits" : [ ] }, "aggregations" : { "my_max" : { "value" : 30.0 } } }

需求3、查詢年齡的最小值

GET zhifou/doc/_search { "query": { "match_all": {} }, "aggs": { "my_min": { "min": { "field": "age" } } }, "size": 0, "_source": ["name","age","from"] } >>>查詢結果 { "took" : 2, "timed_out" : false, "_shards" : { "total" : 5, "successful" : 5, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : 5, "max_score" : 0.0, "hits" : [ ] }, "aggregations" : { "my_min" : { "value" : 18.0 } } }

需求4、查詢符合條件的年齡之和

GET zhifou/doc/_search { "query": { "match": { "from": "gu" } }, "aggs": { "my_sum": { "sum": { "field": "age" } } }, "size": 0, "_source": ["name","age","from"] } >>>查詢結果 { "took" : 4, "timed_out" : false, "_shards" : { "total" : 5, "successful" : 5, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : 3, "max_score" : 0.0, "hits" : [ ] }, "aggregations" : { "my_sum" : { "value" : 81.0 } } }

十二、ES的分組查詢

需求：要查詢所有人的年齡段，並且按照15_20，2025,25~30分組，並且算出每組的平均年齡。

GET zhifou/doc/_search { "size": 0, "query": { "match_all": {} }, "aggs": { "age_group": { "range": { "field": "age", "ranges": [ { "from": 15, "to": 20 }, { "from": 20, "to": 25 }, { "from": 25, "to": 30 } ] } } } } >>>查詢結果 { "took" : 9, "timed_out" : false, "_shards" : { "total" : 5, "successful" : 5, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : 5, "max_score" : 0.0, "hits" : [ ] }, "aggregations" : { "age_group" : { "buckets" : [ { "key" : "15.0-20.0", "from" : 15.0, "to" : 20.0, "doc_count" : 1 }, { "key" : "20.0-25.0", "from" : 20.0, "to" : 25.0, "doc_count" : 1 }, { "key" : "25.0-30.0", "from" : 25.0, "to" : 30.0, "doc_count" : 2 } ] } } }

上例中，在aggs的自定義別名age_group中，使用range來做分組，field是以age為分組，分組使用ranges來做，from和to是范圍

接下來，我們就要對每個小組內的數據做平均年齡處理。

GET zhifou/doc/_search { "size": 0, "query": { "match_all": {} }, "aggs": { "age_group": { "range": { "field": "age", "ranges": [ { "from": 15, "to": 20 }, { "from": 20, "to": 25 }, { "from": 25, "to": 30 } ] }, "aggs": { "my_avg": { "avg": { "field": "age" } } } } } } >>>查詢結果 { "took" : 1, "timed_out" : false, "_shards" : { "total" : 5, "successful" : 5, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : 5, "max_score" : 0.0, "hits" : [ ] }, "aggregations" : { "age_group" : { "buckets" : [ { "key" : "15.0-20.0", "from" : 15.0, "to" : 20.0, "doc_count" : 1, "my_avg" : { "value" : 18.0 } }, { "key" : "20.0-25.0", "from" : 20.0, "to" : 25.0, "doc_count" : 1, "my_avg" : { "value" : 22.0 } }, { "key" : "25.0-30.0", "from" : 25.0, "to" : 30.0, "doc_count" : 2, "my_avg" : { "value" : 27.0 } } ] } } }

ES的聚合查詢的總結：聚合函數的使用，一定是先查出結果，然后對結果使用聚合函數做處理

avg：求平均

max：最大值

min：最小值

sum：求和

十三、ES之Mappings

GET test >>>查詢結果 { "test" : { "aliases" : { }, "mappings" : { "doc" : { "properties" : { "age" : { "type" : "long" }, "desc" : { "type" : "text", "fields" : { "keyword" : { "type" : "keyword", "ignore_above" : 256 } } }, "name" : { "type" : "text", "fields" : { "keyword" : { "type" : "keyword", "ignore_above" : 256 } } } } } }, "settings" : { "index" : { "creation_date" : "1569133097594", "number_of_shards" : "5", "number_of_replicas" : "1", "uuid" : "AztO9waYQiyHvzP6dlk4tA", "version" : { "created" : "6080299" }, "provided_name" : "test" } } } }

由返回結果可以看到，分為兩大部分：

第一部分關於t1索引類型相關的，包括該索引是否有別名aliases，然后就是mappings信息，
包括索引類型doc，各字段的詳細映射關系都收集在properties中。

另一部分是關於索引t1的settings設置。包括該索引的創建時間，主副分片的信息，UUID等等。

1. mappings 是什么？

映射就是在創建索引的時候，有更多定制的內容，更加的貼合業務場景。
用來定義一個文檔及其包含的字段如何存儲和索引的過程。

2. 字段的數據類型

簡單類型如文本（text）、關鍵字（keyword）、日期（data）、整形（long）、雙精度 （double）、布爾（boolean）或ip。 可以是支持JSON的層次結構性質的類型，如對象或嵌套。 或者一種特殊類型，如geo_point、geo_shape或completion。為了不同的目的， 以不同的方式索引相同的字段通常是有用的。例如，字符串字段可以作為全文搜索的文本字段進行索引， 也可以作為排序或聚合的關鍵字字段進行索引。或者，可以使用標准分析器、英語分析器和 法語分析器索引字符串字段。這就是多字段的目的。大多數數據類型通過fields參數支持多字段。

一個簡單的映射示例

PUT mapping_test
{
  "mappings": {
    "test1":{
      "properties":{
        "name":{"type": "text"},
        "age":{"type":"long"}
      }
    }
  }
}

我們在創建索引PUT mapping_test1的過程中，為該索引定制化類型（設計表結構），添加一個映射類型test1；指定字段或者屬性都在properties內完成。

GET mapping_test >>>查詢結果 { "mapping_test" : { "aliases" : { }, "mappings" : { "test1" : { "properties" : { "age" : { "type" : "long" }, "name" : { "type" : "text" } } } }, "settings" : { "index" : { "creation_date" : "1570794586526", "number_of_shards" : "5", "number_of_replicas" : "1", "uuid" : "P4-trriPTxq-nJj89iYXZA", "version" : { "created" : "6080299" }, "provided_name" : "mapping_test" } } } }

返回的結果中你肯定很熟悉！映射類型是test1，具體的屬性都被封裝在properties中。

3. ES mappings之dynamic的三種狀態

一般的，mapping則又可以分為動態映射（dynamic mapping）和靜態（顯示）映射（explicit mapping）和精確（嚴格）映射（strict mappings），具體由dynamic屬性控制。默認為動態映射

##### 默認為動態映射 PUT test4 { "mappings": { "doc":{ "properties": { "name": { "type": "text" }, "age": { "type": "long" } } } } } GET test4/_mapping >>>查詢結果 { "test4" : { "mappings" : { "doc" : { "properties" : { "age" : { "type" : "long" }, "name" : { "type" : "text" }, "sex" : { "type" : "text", "fields" : { "keyword" : { "type" : "keyword", "ignore_above" : 256 } } } } } } } } #####添加數據 PUT test4/doc/1 { "name":"wangjifei", "age":"18", "sex":"不詳" } #####查看數據 GET test4/doc/_search { "query": { "match_all": {} } } >>>查詢結果 { "took" : 8, "timed_out" : false, "_shards" : { "total" : 5, "successful" : 5, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : 1, "max_score" : 1.0, "hits" : [ { "_index" : "test4", "_type" : "doc", "_id" : "1", "_score" : 1.0, "_source" : { "name" : "wangjifei", "age" : "18", "sex" : "不詳" } } ] } }

測試靜態映射：當elasticsearch察覺到有新增字段時，因為dynamic:false的關系，會忽略該字段，但是仍會存儲該字段。

#####創建靜態mapping PUT test5 { "mappings": { "doc":{ "dynamic":false, "properties": { "name": { "type": "text" }, "age": { "type": "long" } } } } } #####插入數據 PUT test5/doc/1 { "name":"wangjifei", "age":"18", "sex":"不詳" } ####條件查詢 GET test5/doc/_search { "query": { "match": { "sex": "不詳" } } } >>>查詢結果 { "took" : 9, "timed_out" : false, "_shards" : { "total" : 5, "successful" : 5, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : 0, "max_score" : null, "hits" : [ ] } } #####查看所有數據 GET /test5/doc/_search { "query": { "match_all": {} } } >>>查詢結果 { "took" : 1, "timed_out" : false, "_shards" : { "total" : 5, "successful" : 5, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : 1, "max_score" : 1.0, "hits" : [ { "_index" : "test5", "_type" : "doc", "_id" : "1", "_score" : 1.0, "_source" : { "name" : "wangjifei", "age" : "18", "sex" : "不詳" } } ] } }

測試嚴格映射：當elasticsearch察覺到有新增字段時，因為dynamic:strict 的關系，就會報錯，不能插入成功。

#####創建嚴格mapping PUT test6 { "mappings": { "doc":{ "dynamic":"strict", "properties": { "name": { "type": "text" }, "age": { "type": "long" } } } } } #####插入數據 PUT test6/doc/1 { "name":"wangjifei", "age":"18", "sex":"不詳" } >>>插入結果 { "error": { "root_cause": [ { "type": "strict_dynamic_mapping_exception", "reason": "mapping set to strict, dynamic introduction of [sex] within [doc] is not allowed" } ], "type": "strict_dynamic_mapping_exception", "reason": "mapping set to strict, dynamic introduction of [sex] within [doc] is not allowed" }, "status": 400 }

小結：動態映射（dynamic：true）：動態添加新的字段（或缺省）。靜態映射（dynamic：false）：忽略新的字段。在原有的映射基礎上，當有新的字段時，不會主動的添加新的映射關系，只作為查詢結果出現在查詢中。嚴格模式（dynamic：strict）：如果遇到新的字段，就拋出異常。一般靜態映射用的較多。就像HTML的img標簽一樣，src為自帶的屬性，你可以在需要的時候添加id或者class屬性。當然，如果你非常非常了解你的數據，並且未來很長一段時間不會改變，strict不失為一個好選擇。

4. ES之mappings的 index 屬性

index屬性默認為true，如果該屬性設置為false，那么，elasticsearch不會為該屬性創建索引，也就是說無法當做主查詢條件。

PUT test7 { "mappings": { "doc": { "properties": { "name": { "type": "text", "index": true }, "age": { "type": "long", "index": false } } } } } ####插入數據 PUT test7/doc/1 { "name":"wangjifei", "age":18 } ####條件查詢數據 GET test7/doc/_search { "query": { "match": { "name": "wangjifei" } } } >>>查詢結果 { "took" : 18, "timed_out" : false, "_shards" : { "total" : 5, "successful" : 5, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : 1, "max_score" : 0.2876821, "hits" : [ { "_index" : "test7", "_type" : "doc", "_id" : "1", "_score" : 0.2876821, "_source" : { "name" : "wangjifei", "age" : 18 } } ] } } #####條件查詢 GET test7/doc/_search { "query": { "match": { "age": 18 } } } >>>查詢結果 { "error": { "root_cause": [ { "type": "query_shard_exception", "reason": "failed to create query: {\n \"match\" : {\n \"age\" : {\n \"query\" : 18,\n \"operator\" : \"OR\",\n \"prefix_length\" : 0,\n \"max_expansions\" : 50,\n \"fuzzy_transpositions\" : true,\n \"lenient\" : false,\n \"zero_terms_query\" : \"NONE\",\n \"auto_generate_synonyms_phrase_query\" : true,\n \"boost\" : 1.0\n }\n }\n}", "index_uuid": "fzN9frSZRy2OzinRjeMKGA", "index": "test7" } ], "type": "search_phase_execution_exception", "reason": "all shards failed", "phase": "query", "grouped": true, "failed_shards": [ { "shard": 0, "index": "test7", "node": "INueKtviRpO1dbNWngcjJA", "reason": { "type": "query_shard_exception", "reason": "failed to create query: {\n \"match\" : {\n \"age\" : {\n \"query\" : 18,\n \"operator\" : \"OR\",\n \"prefix_length\" : 0,\n \"max_expansions\" : 50,\n \"fuzzy_transpositions\" : true,\n \"lenient\" : false,\n \"zero_terms_query\" : \"NONE\",\n \"auto_generate_synonyms_phrase_query\" : true,\n \"boost\" : 1.0\n }\n }\n}", "index_uuid": "fzN9frSZRy2OzinRjeMKGA", "index": "test7", "caused_by": { "type": "illegal_argument_exception", "reason": "Cannot search on field [age] since it is not indexed." } } } ] }, "status": 400 }

5. ES 之 mappings 的copy_to屬性

PUT test8 { "mappings": { "doc": { "dynamic":false, "properties": { "first_name":{ "type": "text", "copy_to": "full_name" }, "last_name": { "type": "text", "copy_to": "full_name" }, "full_name": { "type": "text" } } } } } #####插入數據 PUT test8/doc/1 { "first_name":"tom", "last_name":"ben" } PUT test8/doc/2 { "first_name":"john", "last_name":"smith" } #####查詢所有 GET test8/doc/_search { "query": { "match_all": {} } } >>>查詢結果 { "took" : 4, "timed_out" : false, "_shards" : { "total" : 5, "successful" : 5, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : 2, "max_score" : 1.0, "hits" : [ { "_index" : "test8", "_type" : "doc", "_id" : "2", "_score" : 1.0, "_source" : { "first_name" : "john", "last_name" : "smith" } }, { "_index" : "test8", "_type" : "doc", "_id" : "1", "_score" : 1.0, "_source" : { "first_name" : "tom", "last_name" : "ben" } } ] } } #####條件查詢 GET test8/doc/_search { "query": { "match": { "first_name": "tom" } } } >>>查詢結果 { "took" : 2, "timed_out" : false, "_shards" : { "total" : 5, "successful" : 5, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : 1, "max_score" : 0.2876821, "hits" : [ { "_index" : "test8", "_type" : "doc", "_id" : "1", "_score" : 0.2876821, "_source" : { "first_name" : "tom", "last_name" : "ben" } } ] } } ######條件查詢 GET test8/doc/_search { "query": { "match": { "full_name": "ben" } } } >>>查詢結果 { "took" : 3, "timed_out" : false, "_shards" : { "total" : 5, "successful" : 5, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : 1, "max_score" : 0.2876821, "hits" : [ { "_index" : "test8", "_type" : "doc", "_id" : "1", "_score" : 0.2876821, "_source" : { "first_name" : "tom", "last_name" : "ben" } } ] } }

上例中，我們將first_name和last_name都復制到full_name中。並且使用full_name查詢也返回了結果

既要查詢tom還要查詢smith該怎么辦？

GET test8/doc/_search { "query": { "match": { "full_name": { "query": "tom smith", "operator": "or" } } } } >>>查詢結果 { "took" : 3, "timed_out" : false, "_shards" : { "total" : 5, "successful" : 5, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : 2, "max_score" : 0.2876821, "hits" : [ { "_index" : "test8", "_type" : "doc", "_id" : "2", "_score" : 0.2876821, "_source" : { "first_name" : "john", "last_name" : "smith" } }, { "_index" : "test8", "_type" : "doc", "_id" : "1", "_score" : 0.2876821, "_source" : { "first_name" : "tom", "last_name" : "ben" } } ] } }

operator參數為多個條件的查詢關系也可以是and

上面的查詢還可以簡寫成一下：

GET test8/doc/_search
{
  "query": {
    "match": {
      "full_name": "tom smith"
    }
  }
}

copy_to還支持將相同的屬性值復制給不同的字段。

PUT test9 { "mappings": { "doc": { "dynamic":false, "properties": { "first_name":{ "type": "text", "copy_to": ["full_name1","full_name2"] }, "last_name": { "type": "text", "copy_to": ["full_name1","full_name2"] }, "full_name1": { "type": "text" }, "full_name2":{ "type":"text" } } } } } ####插入數據 PUT test9/doc/1 { "first_name":"tom", "last_name":"ben" } PUT test9/doc/2 { "first_name":"john", "last_name":"smith" } ####條件查詢 GET test9/doc/_search { "query": { "match": { "full_name1": "tom smith" } } } >>>查詢結果 { "took" : 7, "timed_out" : false, "_shards" : { "total" : 5, "successful" : 5, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : 2, "max_score" : 0.2876821, "hits" : [ { "_index" : "test9", "_type" : "doc", "_id" : "2", "_score" : 0.2876821, "_source" : { "first_name" : "john", "last_name" : "smith" } }, { "_index" : "test9", "_type" : "doc", "_id" : "1", "_score" : 0.2876821, "_source" : { "first_name" : "tom", "last_name" : "ben" } } ] } } #####條件查詢 GET test9/doc/_search { "query": { "match": { "full_name2": "tom smith" } } } >>>查詢結果 { "took" : 7, "timed_out" : false, "_shards" : { "total" : 5, "successful" : 5, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : 2, "max_score" : 0.2876821, "hits" : [ { "_index" : "test9", "_type" : "doc", "_id" : "2", "_score" : 0.2876821, "_source" : { "first_name" : "john", "last_name" : "smith" } }, { "_index" : "test9", "_type" : "doc", "_id" : "1", "_score" : 0.2876821, "_source" : { "first_name" : "tom", "last_name" : "ben" } } ] } }

full_name1 full_name2兩個字段都可以查出來

6. ES 之mappings的對象屬性

首先先看看ES自動創建的mappings

PUT test10/doc/1 { "name":"wangjifei", "age":18, "info":{ "addr":"北京", "tel":"18500327026" } } GET test10 >>>查詢結果 { "test10" : { "aliases" : { }, "mappings" : { "doc" : { "properties" : { "age" : { "type" : "long" }, "info" : { "properties" : { "addr" : { "type" : "text", "fields" : { "keyword" : { "type" : "keyword", "ignore_above" : 256 } } }, "tel" : { "type" : "text", "fields" : { "keyword" : { "type" : "keyword", "ignore_above" : 256 } } } } }, "name" : { "type" : "text", "fields" : { "keyword" : { "type" : "keyword", "ignore_above" : 256 } } } } } }, "settings" : { "index" : { "creation_date" : "1570975011394", "number_of_shards" : "5", "number_of_replicas" : "1", "uuid" : "YvMGDHxkSri0Lgx6GGXiNw", "version" : { "created" : "6080299" }, "provided_name" : "test10" } } } }

現在如果要以info中的tel為條件怎么寫查詢語句呢？

GET test10/doc/_search { "query": { "match": { "info.tel": "18500327026" } } } >>>查詢結果 { "took" : 5, "timed_out" : false, "_shards" : { "total" : 5, "successful" : 5, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : 1, "max_score" : 0.2876821, "hits" : [ { "_index" : "test10", "_type" : "doc", "_id" : "1", "_score" : 0.2876821, "_source" : { "name" : "wangjifei", "age" : 18, "info" : { "addr" : "北京", "tel" : "18500327026" } } } ] } }

info既是一個屬性，也是一個對象，我們稱為info這類字段為對象型字段。該對象內又包含addr和tel兩個字段，如上例這種以嵌套內的字段為查詢條件的話，查詢語句可以以字段點子字段的方式來寫即可

7. ES之mappings的settings 設置

在創建一個索引的時候，我們可以在settings中指定分片信息：

PUT test11
{
  "mappings": {
    "doc": {
      "properties": {
        "name": {
          "type": "text"
        }
      }
    }
  }, 
  "settings": {
    "number_of_replicas": 1,
    "number_of_shards": 5
  }
}

number_of_shards是主分片數量（每個索引默認5個主分片），而number_of_replicas是復制分片，默認一個主分片搭配一個復制分片。

8. ES 之mappings的ignore_above參數

ignore_above參數僅針對於keyword類型有用

# 這樣設置是會報錯的 PUT test12 { "mappings": { "doc": { "properties": { "name": { "type": "text", "ignore_above":5 } } } } } >>>顯示結果 { "error": { "root_cause": [ { "type": "mapper_parsing_exception", "reason": "Mapping definition for [name] has unsupported parameters: [ignore_above : 5]" } ], "type": "mapper_parsing_exception", "reason": "Failed to parse mapping [doc]: Mapping definition for [name] has unsupported parameters: [ignore_above : 5]", "caused_by": { "type": "mapper_parsing_exception", "reason": "Mapping definition for [name] has unsupported parameters: [ignore_above : 5]" } }, "status": 400 }

##### 正確的打開方式 PUT test12 { "mappings": { "doc": { "properties": { "name": { "type": "keyword", "ignore_above":5 } } } } } PUT test12/doc/1 { "name":"wangjifei" } ##### 這樣查詢能查出結果 GET test12/doc/_search { "query": { "match_all": {} } } >>>查詢結果 { "took" : 1, "timed_out" : false, "_shards" : { "total" : 5, "successful" : 5, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : 1, "max_score" : 1.0, "hits" : [ { "_index" : "test12", "_type" : "doc", "_id" : "1", "_score" : 1.0, "_source" : { "name" : "wangjifei" } } ] } } ######這樣查詢不能查詢出結果 GET test12/doc/_search { "query": { "match": { "name": "wangjifei" } } } >>>查詢結果 { "took" : 1, "timed_out" : false, "_shards" : { "total" : 5, "successful" : 5, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : 0, "max_score" : null, "hits" : [ ] } }

上面的例子證明超過ignore_above設定的值后會被存儲但不會建立索引

那么如果字符串的類型是text時能用ignore_above嗎，答案是能，但要特殊設置：

PUT test13 { "mappings": { "doc":{ "properties":{ "name1":{ "type":"keyword", "ignore_above":5 }, "name2":{ "type":"text", "fields":{ "keyword":{ "type":"keyword", "ignore_above": 10 } } } } } } } PUT test13/doc/1 { "name1":"wangfei", "name2":"wangjifei hello" } ##### 能查出來 GET test13/doc/_search { "query": { "match_all": {} } } >>>查詢結果 { "took" : 4, "timed_out" : false, "_shards" : { "total" : 5, "successful" : 5, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : 1, "max_score" : 1.0, "hits" : [ { "_index" : "test13", "_type" : "doc", "_id" : "1", "_score" : 1.0, "_source" : { "name1" : "wangfei", "name2" : "wangjifei hello" } } ] } } ##### 通過name1 字段查不出來，因為設置的是keyword類型 限制了5個字符的長度， ##### 存儲的值超過了最大限制 GET test13/doc/_search { "query": { "match": { "name1": "wangfei" } } } >>>查詢結果 { "took" : 2, "timed_out" : false, "_shards" : { "total" : 5, "successful" : 5, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : 0, "max_score" : null, "hits" : [ ] } } ##### 通過name2 字段能查出來，雖然限制了5個字符的長度，存儲的值超過了最大限制，但是， ##### 當字段類型設置為text之后，ignore_above參數的限制就失效了。（了解就好，意義不大） GET test13/doc/_search { "query": { "match": { "name2": "wangjifei" } } } >>>查詢結果 { "took" : 1, "timed_out" : false, "_shards" : { "total" : 5, "successful" : 5, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : 1, "max_score" : 0.2876821, "hits" : [ { "_index" : "test13", "_type" : "doc", "_id" : "1", "_score" : 0.2876821, "_source" : { "name1" : "wangfei", "name2" : "wangjifei hello" } } ] } }

參考地址：https://www.jianshu.com/p/3873a6290c65

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猜您在找 ES 常用的查詢語句介紹 python查詢es數據的語句 es查詢和更新語句示例 Es-python常用查詢語句示例 Elasticsearch（es）查詢語句語法詳解 es 查詢語句提升權重 - boost 關鍵詞的使用 es查詢 es的基本查詢 es去重查詢 RestHighLevelClient查詢es

ES基本查詢語句教程

前言

一、 ES簡單的增刪改查

1、創建一篇文檔（有則修改，無則創建)

2、查詢指定索引信息

3、 查詢指定文檔信息

4、查詢對應索引下所有數據

5、刪除指定文檔

6、刪除索引

7、修改指定文檔方式

二、ES查詢的兩種方式

1、查詢字符串搜索

2、結構化查詢(單字段查詢,不能多字段組合查詢)

三、match系列之操作

1、match系列之match_all (查詢全部)

2、match系列之match_phrase（短語查詢）

我們搜索中國和世界這兩個指定詞組時，但又不清楚兩個詞組之間有多少別的詞間隔。那么在搜的時候就要留有一些余地。這時就要用到了slop了。相當於正則中的中國.*?世界。這個間隔默認為0

3、match系列之match_phrase_prefix（最左前綴查詢）智能搜索--以什么開頭

搜索特定英文開頭的數據

max_expansions 參數理解 前綴查詢會非常的影響性能，要對結果集進行限制，就加上這個參數。

4、match系列之multi_match（多字段查詢)

四、ES的排序查詢

五、ES的分頁查詢

六、ES的bool查詢 (must、should)

七、ES之查詢結果過濾

八、ES之查詢結果高亮顯示

十、ES之精確查詢與模糊查詢

term和match的區別是：match是經過analyer的，也就是說，文檔首先被分析器給處理了。根據不同的分析器，分析的結果也稍顯不同，然后再根據分詞結果進行匹配。term則不經過分詞，它是直接去倒排索引中查找了精確的值了。

十一、ES的聚合查詢avg、max、min、sum

如果只想看輸出的值，而不關心輸出的文檔的話可以通過size=0來控制

十二、ES的分組查詢

上例中，在aggs的自定義別名age_group中，使用range來做分組，field是以age為分組，分組使用ranges來做，from和to是范圍

十三、ES之Mappings

由返回結果可以看到，分為兩大部分：

1. mappings 是什么？

2. 字段的數據類型

我們在創建索引PUT mapping_test1的過程中，為該索引定制化類型（設計表結構），添加一個映射類型test1；指定字段或者屬性都在properties內完成。

返回的結果中你肯定很熟悉！映射類型是test1，具體的屬性都被封裝在properties中。

3. ES mappings之dynamic的三種狀態

4. ES之mappings的 index 屬性

5. ES 之 mappings 的copy_to屬性

上例中，我們將first_name和last_name都復制到full_name中。並且使用full_name查詢也返回了結果

operator參數為多個條件的查詢關系也可以是and

full_name1 full_name2兩個字段都可以查出來

6. ES 之mappings的對象屬性

info既是一個屬性，也是一個對象，我們稱為info這類字段為對象型字段。該對象內又包含addr和tel兩個字段，如上例這種以嵌套內的字段為查詢條件的話，查詢語句可以以字段點子字段的方式來寫即可

7. ES之mappings的settings 設置

number_of_shards是主分片數量（每個索引默認5個主分片），而number_of_replicas是復制分片，默認一個主分片搭配一個復制分片。

8. ES 之mappings的ignore_above參數

上面的例子證明超過ignore_above設定的值后會被存儲但不會建立索引

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3、查詢指定文檔信息

max_expansions 參數理解前綴查詢會非常的影響性能，要對結果集進行限制，就加上這個參數。