ES基础入门

男娘i 2024-04-20 07:22 4阅读 0赞

## ES ##

### 一、简介 ###

#### 1、Elastic Stack ####

ES技术栈：

*  ElasticSearch：存数据+搜索；QL；
 *  Kibana：Web可视化平台，分析。
 *  LogStash：日志收集，Log4j:产生日志；log.info(xxx)
 *  。。。。

![image-20220930095909877][]

使用场景：

*  metrics：指标监控
 *  …

#### 2、基本概念 ####

*  Index（索引）
    
     *  动词：保存（插入）
     *  名词：类似MySQL数据库，给数据
 *  Type（类型）
    
     *  已废弃，以前类似MySQL的表
     *  现在用索引对数据分类
 *  Document（文档）
    
     *  真正要保存的一个JSON数据
     *      {
                    
                name:"tcx"
            }
     *

### 二、入门实战 ###

{
        
      "name" : "DESKTOP-1TSVGKG",
      "cluster_name" : "elasticsearch",
      "cluster_uuid" : "PFpgHGhaTZiajHD4xvRPkg",
      "version" : {
        
        "number" : "7.14.0",
        "build_flavor" : "default",
        "build_type" : "zip",
        "build_hash" : "dd5a0a2acaa2045ff9624f3729fc8a6f40835aa1",
        "build_date" : "2021-07-29T20:49:32.864135063Z",
        "build_snapshot" : false,
        "lucene_version" : "8.9.0",
        "minimum_wire_compatibility_version" : "6.8.0",
        "minimum_index_compatibility_version" : "6.0.0-beta1"
      },
      "tagline" : "You Know, for Search"
    }

#### 1、索引CRUD ####

1.创建索引

put http://localhost:9200/person
    
    {
        
        "acknowledged": true, #响应结果
        "shards_acknowledged": true,  #分片
        "index": "person"   #索引名称
    }

2.删除索引

delete http://localhost:9200/person
    
    {
        
        "acknowledged": true
    }

3.修改索引

# 在修改时，需要先删掉索引
    put http://localhost:9200/person
    
    {
        
        "settings": {
        
            "index": {
        
                "number_of_shards":"3"
            }
        }
    }

4.查询索引

get http://localhost:9200/person
    
    {
        
        "person": {
        
            "aliases": {
        },
            "mappings": {
        },
            "settings": {
        
                "index": {
        
                    "routing": {
        
                        "allocation": {
        
                            "include": {
        
                                "_tier_preference": "data_content"
                            }
                        }
                    },
                    "number_of_shards": "3",
                    "provided_name": "person",
                    "creation_date": "1664357188860",
                    "number_of_replicas": "1",
                    "uuid": "GOyDifOJTQi8yBzKHk5zNQ",
                    "version": {
        
                        "created": "7140099"
                    }
                }
            }
        }
    }

#### 2、文档CRUD ####

##### 1、保存-POST（非幂等性） #####

POST /person/_doc
    {
        
      "id":"1",
      "name":"田",
      "age":"19"
    }
    
    # 结果
    {
        
      "_index" : "person", //保存到的索引
      "_type" : "_doc", //
      "_id" : "BcKKg4MBcNCrjSmlWbAK",  //刚才那条数据的唯一id
      "_version" : 1,  //版本号
      "result" : "created", //创建了数据
      "_shards" : {
          //分片工作
        "total" : 2,
        "successful" : 1,
        "failed" : 0
      },
      "_seq_no" : 0,  //乐观锁机制
      "_primary_term" : 1  //乐观锁机制
    }

> 以上是：非**幂等**操作
> 
>  *  幂等：同一个操作执行无数遍的结果都是一样的
>     
>      *  select
>      *  insert: 幂等
>  *  非幂等：
>     
>      *  insert: 自增主键就是非幂等

##### 2、保存-PUT（幂等性） #####

保存更新 二合一

PUT /person/_doc/1
    {
        
      "id":"1",
      "name":"田",
      "age":"19"
    }
    
    
    PUT /person/_doc/1
    {
        
      "id":"1",
      "name":"田",
      "age":"19",
      "note":"做个小笔记"
    }
    
    # 也可以任意扩展/缩减字段；（会覆盖）

##### 3、POST-增量字段更新 #####

POST person/_doc/1/_update
    {
        
      "doc":{
        
        "name":"张三"
      }
    }

##### 4、查询 #####

# 查看所有
    GET /person/_search
    
    # 根据ID查询
    GET /person/_doc/ID号

##### 5、乐观锁 #####

> CAS

### 三、进阶检索 ###

#  DSL 查询条件以Json
    POST person/_search
    {
        
      "query": {
        
        "match_all": {
        }
      }
    }

#### 1、导入基本数据 ####

POST /student/_doc/1001
    {
        
      "name":"李白",
      "age":"18"
    }
    
    POST /student/_doc/1002
    {
        
      "name":"诗仙",
      "age":"19"
    }
    
    POST /student/_doc/1003
    {
        
      "name":"杜甫",
      "age":"20"
    }
    
    
    
    POST /student/_doc/1004
    {
        
      "name":"诗圣",
      "age":"21"
    }
    
    POST /student/_doc/1005
    {
        
      "name":"诗圣 厉害",
      "age":"21"
    }

#### 2、查询所有文档 ####

POST /student/_search
    {
        
      "query": {
        
        "match_all": {
        }
      }  
    }
    
    
    POST /student/_search
    {
        
      "query": {
        
        "match_all": {
        }
      }  
    }
    
    
    {
        
      "took" : 1,
      "timed_out" : false,
      "_shards" : {
        
        "total" : 1,
        "successful" : 1,
        "skipped" : 0,
        "failed" : 0
      },
      "hits" : {
        
        "total" : {
        
          "value" : 4,
          "relation" : "eq"
        },
        "max_score" : 1.0,
        "hits" : [
          {
        
            "_index" : "student",
            "_type" : "_doc",
            "_id" : "1001",
            "_score" : 1.0,
            "_source" : {
        
              "name" : "李白",
              "age" : "18"
            }
          },
          {
        
            "_index" : "student",
            "_type" : "_doc",
            "_id" : "1002",
            "_score" : 1.0,
            "_source" : {
        
              "name" : "诗仙",
              "age" : "19"
            }
          },
          {
        
            "_index" : "student",
            "_type" : "_doc",
            "_id" : "1003",
            "_score" : 1.0,
            "_source" : {
        
              "name" : "杜甫",
              "age" : "20"
            }
          },
          {
        
            "_index" : "student",
            "_type" : "_doc",
            "_id" : "1004",
            "_score" : 1.0,
            "_source" : {
        
              "name" : "诗圣",
              "age" : "21"
            }
          }
        ]
      }
    }

#### 3、match-全文索引精确查询 ####

POST /student/_search
    {
        
      "query": {
        
        "match": {
        
          "name.keyword": "诗圣"
        }
      }
    }

**multi\_match-多个字段查询**

POST /student/_search
    {
        
      "query": {
        
        "multi_match": {
        
          "query": "诗圣",
          "fields": ["name"]
        }
      }
    }

#### 4、term-精确查询 ####

POST /student/_search
    {
        
      "query": {
        
        "term": {
        
          "name": {
        
            "value": "shixian"
          }
        }
      }
    }

#### 5、terms-查询 ####

# 查询age是20，18的
    POST /student/_search
    {
        
      "query": {
        
        "terms": {
        
          "age": [
            "20",
            "18"
          ]
        }
      }
    }

#### 6、多个字段查询 ####

#### 7、查询部分字段 ####

POST /student/_search
    {
        
      "query": {
        
        "match": {
        
          "name": "诗圣"
        }
      },
      "_source": ["name"]  
    }

#### 8、区间查询 ####

POST /student/_search
    {
        
      "query": {
        
        "range": {
        
          "age": {
        
            "gte": 18,
            "lte": 20
          }
        }
      }
    }

#### 9、复合查询 ####

# must 
    
    POST /student/_search
    {
        
      "query": {
        
        "bool": {
        
          "must": [
            {
        
              "range": {
        
                "age": {
        
                  "gte": 18,
                  "lte": 20
                }
              }
            },{
        
              "match": {
        
                "name": "诗圣"
              }
            }
          ]
        }
      }
    }

> must和filter执行的结果是一样的，但是must会有分数，filter没有分数

#### 10、过滤查询 ####

POST /student/_search
    {
        
      "query": {
        
        "bool": {
        
          "filter": [
            {
        
              "range": {
        
                "age": {
        
                  "gte": 18,
                  "lte": 20
                }
              }
            },{
        
              "match": {
        
                "name": "诗圣"
              }
            }
          ]
        }
      }
    }

>  *  模糊匹配用match
>  *  精确查询用term
>  *  多条件组合是bool
>  *  must,filter相配合
>  *  should非强制要求

#### 11、判断文档是否存在 ####

#判断文档是否存在
    HEAD /student/_doc/1001

#### 12、exists查询 ####

POST /student/_search
    {
        
      "query": {
        
        "exists": {
        
          "field": "hello"
        }
      }
    }
    
    # 找到有hello属性的文档
    {
        
      "took" : 739,
      "timed_out" : false,
      "_shards" : {
        
        "total" : 1,
        "successful" : 1,
        "skipped" : 0,
        "failed" : 0
      },
      "hits" : {
        
        "total" : {
        
          "value" : 1,
          "relation" : "eq"
        },
        "max_score" : 1.0,
        "hits" : [
          {
        
            "_index" : "student",
            "_type" : "_doc",
            "_id" : "1006",
            "_score" : 1.0,
            "_source" : {
        
              "name" : "白居易",
              "hello" : "word"
            }
          }
        ]
      }
    }

#### 13、批量 ####

#批量查询ID
    
    POST student/_doc/_mget
    {
        
      "ids":["1001","1002"]
    }

![image-20221008112207118][]

![image-20221008112346329][]

### 四、其他功能 ###

1、排序

POST student/_search
    {
        
      "query": {
        
        "match_all": {
        
          
        }
      },
      "sort": [
        {
        
          "age": {
        
            "order": "asc"
          }
        }
      ]
    }

2、高亮

#高亮
    GET student/_search
    {
        
      "query": {
        
        "match": {
        
          "age": "21"
        }
      },
     "highlight": {
        
        "fields": {
        
          "age": {
        
            "pre_tags": "<span style='color:res'>",
            "post_tags": "</span>"
          }
        }
      }
    }

3、\_source-部分字段

POST /student/_search
    {
        
      "query": {
        
        "match": {
        
          "name": "诗圣"
        }
      },
      "_source": ["name"]  
    }

4、分页

#分页
    
    POST student/_search
    {
        
      "query": {
        
        "match_all": {
        
        
        }
      },
      "from": 0,
      "size": 2
    }

聚合

![image-20221008115217531][]

### 五、映射与分词 ###

#### 1、Mapping ####

*  ES里面保存是JSON
 *  第一次保存了以后，每个索引的数据模型就确定好了，es在第一次保存一个json文档的时候就自动确定了。
 *  在自动确定阶段，所有文本数据都会被确定为text,默认就可以全文检索，这个文本值在存储的时候分词，利用倒排索引存储
 *  Mappings第一次**已经确定好的属性就不能修改了**，**但是未知的属性随便添加**

> 自定义的数据类型(text,keyword)，一定告诉es，这个属性的精确类型

#### 2、分词 ####

*  分词发生在text字段
 *  保存text类型的数据
    
     *  把这个值先分词（英文：空格为分割 中文：词库 比较麻烦）
     *  存储利用倒排索引，会记录这些单词都在哪些文档出现
 *  检索
    
     *  搜索“我是中国人”
     *  把要搜索的”我是中国人“分词（利用词库对比）
        
         *  中国人： 看那些文档里有
         *  中国 看那些文档里有
         *  我 看那些文档里有
         *  是 看那些文档里有

GET /_analyze
    {
        
      "analyzer": "standard",
      "text":"Offer收割机"
    }

> 必须使用中文分词器
> 
> ik分词器

##### 2.1安装ik分词器 #####

下载当前对应版本；

没下载到对应版本的话，可以在ik分词器解压后，在`plugin-descriptor.properties`文件中，修改成对应的ES版本

GET /_analyze
    {
        
      "analyzer": "ik_smart",
      "text":"Offer收割机"
    }

PUT world
    {
        
      "mappings": {
        
        "properties": {
        
          "name":{
        
            "type": "keyword"
          },
          "song":{
        
            "type": "text",
            "analyzer": "ik_smart"
          }
        }
      }
    }

#### 3 Nested嵌入式 ####

PUT /test_nested
    {
        
      "mappings": {
        
        "properties": {
        
          "user":{
        
            "type": "nested"
          }
        }
      }
    }

### 六、Springboot整合ES ###

#### 6.1 引依赖 ####

<dependency>
        <groupId>org.elasticsearch.client</groupId>
        <artifactId>elasticsearch-rest-high-level-client</artifactId>
        <version>7.14.0</version>
    </dependency>
    <dependency>
        <groupId>org.elasticsearch</groupId>
        <artifactId>elasticsearch</artifactId>
        <version>7.14.0</version>
    </dependency>
    
    <dependency>
        <groupId>org.elasticsearch.client</groupId>
        <artifactId>elasticsearch-rest-client</artifactId>
        <version>7.14.0</version>
        <exclusions>
            <exclusion>
                <artifactId>commons-logging</artifactId>
                <groupId>commons-logging</groupId>
            </exclusion>
        </exclusions>
    </dependency>

#### 6.2 写配置文件 ####

spring.elasticsearch.rest.uris[0]=http://localhost:9200

#### 6.3 写测试代码 ####

##### 6.3.1 索引操作 #####

@Resource
        RestHighLevelClient restHighLevelClient;
    
    
        @Test
        public void contextLoads() {
        
            System.out.println("restHighLevelClient = " + restHighLevelClient);
        }
    
        @Test
        public void createIndex() throws IOException {
        
            CreateIndexRequest request = new CreateIndexRequest("google");
            request.settings(Settings.builder()
                    .put("index.number_of_shards","1")
                    .put("index.number_of_replicas","1")
                    .build()
            );
            CreateIndexResponse response = restHighLevelClient.indices().create(request, RequestOptions.DEFAULT);
            System.out.println("response = " + response.isAcknowledged()
            );
        }
    
    
      @Test
        public void deleteIndex() throws IOException {
        
            DeleteIndexRequest request = new DeleteIndexRequest("hello");
            AcknowledgedResponse delete = restHighLevelClient.indices().delete(request, RequestOptions.DEFAULT);
            boolean b = delete.isAcknowledged();
            System.out.println(b?"删除成功":"删除失败");
        }

6.3.2 待更新 ，嘻嘻

`谢谢你的阅读`，现在学会了吧，赶快去你的朋友圈中秀一波吧😎

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写作不易，各位老板的肯定和关注都是我坚持下去的动力，欢迎来”骚扰“额😘

[image-20220930095909877]: https://image.dandelioncloud.cn/pgy_files/images/2024/04/20/04f5eaf0b7414c9db243a01a80131a80.png
[image-20221008112207118]: https://image.dandelioncloud.cn/pgy_files/images/2024/04/20/0fb219c3e8804796843d6b2f3b3f5cce.png
[image-20221008112346329]: https://image.dandelioncloud.cn/pgy_files/images/2024/04/20/599e2484342c4556b49f7c988423c84e.png
[image-20221008115217531]: https://image.dandelioncloud.cn/pgy_files/images/2024/04/20/107e909306a943d5a600f63572ddf0b7.png