数据格式

Elasticsearch是面向文档型数据库，一条数据就是一个文档。
image.png
Elasticsearch 6.X中，一个index只能包含一个type，7.X中，Type概念已经被删除了

倒排索引

  • 正排索引

id content
——————-
1001 my name is zhangsan
1002 my name is lisi
通过id查询很快，但是如果需要查询content里的”name”，就需要模糊查询，每条都要遍历

  • 倒排索引

keyword id
—————-
name 1001, 1002
zhang 1001

索引操作

创建索引

对比关系型数据库，创建索引等同于创建数据库
在Postman中，向ES服务器发PUT请求：http://127.0.0.1:9200/shopping

  1. {
  2.     "acknowledged": true,
  3.     "shards_acknowledged": true,
  4.     "index": "shopping"
  5. }

查询索引

GET请求 URL不变

  1. {
  2.     "shopping": {
  3.         "aliases": {},
  4.         "mappings": {},
  5.         "settings": {
  6.             "index": {
  7.                 "routing": {
  8.                     "allocation": {
  9.                         "include": {
  10.                             "_tier_preference": "data_content"
  11.                         }
  12.                     }
  13.                 },
  14.                 "number_of_shards": "1",
  15.                 "provided_name": "shopping",
  16.                 "creation_date": "1650513030284",
  17.                 "number_of_replicas": "1",
  18.                 "uuid": "__fkgO0_R1ebjRJdflgxew",
  19.                 "version": {
  20.                     "created": "8010299"
  21.                 }
  22.             }
  23.         }
  24.     }
  25. }

如果要查询所有索引
[http://localhost:9200/_cat/indices?v](http://localhost:9200/_cat/indices?v)

  1. health status index    uuid                   pri rep docs.count docs.deleted store.size pri.store.size
  2. yellow open   shopping __fkgO0_R1ebjRJdflgxew   1   1          0            0       225b           225b

删除索引

DELETE``http://127.0.0.1:9200/shopping

  1. {
  2.     "acknowledged": true
  3. }

文档操作

创建数据

索引创建好后，创建文档，并添加数据。这里的文档可以类比为关系型数据库中的表数据，添加的数据格式为JSON格式。
POST``http://127.0.0.1/shopping/_doc 必须要有body, _doc表示文档数据 ，也可以使用_create

  1. {
  2.     "title":"小米手机",
  3.     "category":"Xiaomi",
  4.     "images":"xxx.jpg",
  5.     "price":299
  6. }
  1. {
  2.     "_index": "shopping",
  3.     "_id": "hBXsSoAB2uyBztVe--TH",
  4.     "_version": 1,
  5.     "result": "created",
  6.     "_shards": {
  7.         "total": 2,
  8.         "successful": 1,
  9.         "failed": 0
  10.     },
  11.     "_seq_no": 0,
  12.     "_primary_term": 1
  13. }

如果在uri中加入id，就不会自动生成随机的id了
[http://127.0.0.1/shopping/_doc](http://127.0.0.1/shopping/_doc)/1001

查询数据

GET``[http://localhost:9200/shopping/_doc/1001](http://localhost:9200/shopping/_doc/1001)

  1. {
  2.     "_index": "shopping",
  3.     "_id": "1001",
  4.     "_version": 1,
  5.     "_seq_no": 1,
  6.     "_primary_term": 1,
  7.     "found": true,
  8.     "_source": {
  9.         "title": "小米手机",
  10.         "category": "Xiaomi",
  11.         "images": "xxx.jpg",
  12.         "price": 299
  13.     }
  14. }

如果要获取索引下的所有数据
GET``[http://localhost:9200/shopping/](http://localhost:9200/shopping/_doc/1001)_search

  1. {
  2.     "took": 746,
  3.     "timed_out": false,
  4.     "_shards": {
  5.         "total": 1,
  6.         "successful": 1,
  7.         "skipped": 0,
  8.         "failed": 0
  9.     },
  10.     "hits": {
  11.         "total": {
  12.             "value": 2,
  13.             "relation": "eq"
  14.         },
  15.         "max_score": 1.0,
  16.         "hits": [
  17.             {
  18.                 "_index": "shopping",
  19.                 "_id": "hBXsSoAB2uyBztVe--TH",
  20.                 "_score": 1.0,
  21.                 "_source": {
  22.                     "title": "小米手机",
  23.                     "category": "Xiaomi",
  24.                     "images": "xxx.jpg",
  25.                     "price": 299
  26.                 }
  27.             },
  28.             {
  29.                 "_index": "shopping",
  30.                 "_id": "1001",
  31.                 "_score": 1.0,
  32.                 "_source": {
  33.                     "title": "小米手机",
  34.                     "category": "Xiaomi",
  35.                     "images": "xxx.jpg",
  36.                     "price": 299
  37.                 }
  38.             }
  39.         ]
  40.     }
  41. }

全量数据更新

PUT``ht[tp://localhost:9200/shopping/](http://localhost:9200/shopping/_doc/1001)_doc/1001

  1. {
  2.     "title":"小米手机",
  3.     "category":"Xiaomi",
  4.     "images":"xxx.jpg",
  5.     "price":199
  6. }
  1. {
  2.     "_index": "shopping",
  3.     "_id": "1001",
  4.     "_version": 2,
  5.     "result": "updated",
  6.     "_shards": {
  7.         "total": 2,
  8.         "successful": 1,
  9.         "failed": 0
  10.     },
  11.     "_seq_no": 2,
  12.     "_primary_term": 1
  13. }

局部数据更新

POST``http://127.0.0.1:9200/shopping/_update/1001

  1. {
  2.     "doc": {
  3.         "title": "华为手机"
  4.     }
  5. }
  1. {
  2.     "_index": "shopping",
  3.     "_id": "1001",
  4.     "_version": 2,
  5.     "result": "noop",
  6.     "_shards": {
  7.         "total": 0,
  8.         "successful": 0,
  9.         "failed": 0
  10.     },
  11.     "_seq_no": 2,
  12.     "_primary_term": 1
  13. }

删除数据

DELETE``http://127.0.0.1:9200/shopping/_doc/1001

条件查询

通过路径加参数查询

GET``http://127.0.0.1/shopping/_search?q=category:Xiaomi

通过请求体查询

GET``[http://127.0.0.1/shopping/_search](http://127.0.0.1/shopping/_search)

  1. {
  2.     "query" : {
  3.         "match" : {
  4.             "category" : "Xiaomi"
  5.         }
  6.     } 
  7. }
  1. {
  2.     "query" : {
  3.         "match_all" : {
  4.         }
  5.     } 
  6. }

分页查询&查询排序

GET``[http://127.0.0.1/shopping/_search](http://127.0.0.1/shopping/_search)

  • from 从哪一条数据开始 第一条数据为0
  • size 每页几条数据
  • _source 指定查询返回的字段
  • sort 排序 order: asc desc

从起始位置0开始（第一条数据），每页2条数据，只保留title数据, 按照价格降序排序

  1. {
  2.     "query" : {
  3.         "match_all" : {
  4.         }
  5.     },
  6.     "from": 0,
  7.     "size": 2,
  8.     "_source" : ["title"],
  9.     "sort" : {
  10.       "price" : {
  11.           "order" : "desc"
  12.       }
  13.     }
  14. }
  1. {
  2.     "took": 2,
  3.     "timed_out": false,
  4.     "_shards": {
  5.         "total": 1,
  6.         "successful": 1,
  7.         "skipped": 0,
  8.         "failed": 0
  9.     },
  10.     "hits": {
  11.         "total": {
  12.             "value": 3,
  13.             "relation": "eq"
  14.         },
  15.         "max_score": 1.0,
  16.         "hits": [
  17.             {
  18.                 "_index": "shopping",
  19.                 "_id": "hBXsSoAB2uyBztVe--TH",
  20.                 "_score": 1.0,
  21.                 "_source": {
  22.                     "title": "小米手机",
  23.                     "category": "Xiaomi",
  24.                     "images": "xxx.jpg",
  25.                     "price": 299
  26.                 }
  27.             },
  28.             {
  29.                 "_index": "shopping",
  30.                 "_id": "1001",
  31.                 "_score": 1.0,
  32.                 "_source": {
  33.                     "title": "小米手机",
  34.                     "category": "Xiaomi",
  35.                     "images": "xxx.jpg",
  36.                     "price": 199
  37.                 }
  38.             }
  39.         ]
  40.     }
  41. }

多条件查询

GET``[http://127.0.0.1/shopping/_search](http://127.0.0.1/shopping/_search)

  • bool

  • must

    1. {
    2. "query":{
    3.   "bool":{
    4.     "must":[
    5.       {
    6.         "match":{
    7.           "category":"Xiaomi"
    8.         }
    9.       },
    10.       {
    11.         "match":{
    12.           "price":199
    13.         }
    14.       }
    15.     ]
    16.   }
    17. }
    18. }

  • should

    1. {
    2. "query":{
    3.   "bool":{
    4.     "should":[
    5.       {
    6.         "match":{
    7.           "category":"Xiaomi"
    8.         }
    9.       },
    10.       {
    11.         "match":{
    12.           "category":"Huawei"
    13.         }
    14.       }
    15.     ]
    16.   }
    17. }
    18. }

    范围查询

    GET``[http://127.0.0.1/shopping/_search](http://127.0.0.1/shopping/_search)

  • filter

  • range
  • gt&lt 大于 小于
    1. {
    2. "query":{
    3.   "bool":{
    4.       "filter":{
    5.           "range":{
    6.               "price":{
    7.                   "gt":199,
    8.                   "lt":300
    9.               }
    10.           }
    11.       }
    12.   }
    13. }
    14. }

    全文检索

    当保存文档数据时 ES会对文档数据进行拆解，保存到倒排索引中。当通过ES进行查询，也会通过倒排索引进行匹配。因此，即使只查询”category”:”Xiao”也会查到
    1. {
    2.   "query" : {
    3.       "match" : {
    4.           "title" : "小米"
    5.       }
    6.   } 
    7. }
    如果查询”title”=”小华” 会既查到小米也查到华为的数据

    完全匹配

    1. {
    2.   "query" : {
    3.       "match_phrase" : {
    4.           "title" : "小"
    5.       }
    6.   } 
    7. }
    这样就查不到了

    高亮查询

    1. {
    2.   "query" : {
    3.       "match_phrase" : {
    4.           "title" : "小"
    5.       }
    6.   },
    7.   "highlight" : {
    8.       "fields" : {
    9.           "category" : {}
    10. }

    聚合操作

    1. {
    2.   "aggs" : { // 聚合操作
    3.       "price_group" : {  // 名称 随意起的
    4.           "terms" : {  //
    5.               "field" : "price" // 分组字段
    6.           }
    7.       }
    8.   },
    9.   "size":0
    10. }
    size:0过滤掉了查询的原始数据
    1. {
    2.   "aggs" : { // 聚合操作
    3.       "price_avg" : {  // 名称 随意起的
    4.           "avg" : {  //
    5.               "field" : "price" // 分组字段
    6.           }
    7.       }
    8.   },
    9.   "size":0
    10. }

    映射关系

    其实就是表的结构信息
  1. 先创建user索引
  2. 创建user的映射关系

PUT``[http://localhost:9200/user/_mapping](http://localhost:9200/user/_mapping)

  1. {
  2.     "properties" : {
  3.         "name" : {
  4.             "type" : "text",
  5.             "index" : true
  6.         },
  7.         "sex" : {
  8.             "type" : "keyword",
  9.             "index" : true
  10.         },
  11.         "tel" : {
  12.             "type" : "keyword",
  13.             "index" : false
  14.         }         
  15.     }
  16. }
  1. 插入数据

PUT``[http://localhost:9200/user/_create/001](http://localhost:9200/user/_create/001)

  1. {
  2.     "name" : "汤姆",
  3.     "sex" : "男的",
  4.     "tel" : "12345"
  5. }
  1. 查询

GET``[http://localhost:9200/user/_search](http://localhost:9200/user/_search)

  1. {
  2.     "query" : {
  3.         "match" : {
  4.             "name" : "汤"
  5.         }
  6.     }
  7. }
  1. {
  2.     "query" : {
  3.         "match" : {
  4.             "sex" : "男"
  5.         }
  6.     }
  7. }

因为sex字段是”keyword”类型，而name是”text”类型

  1. {
  2.     "query" : {
  3.         "match" : {
  4.             "tel" : "12345"
  5.         }
  6.     }
  7. }

因为字段的index设置为了false