[C++][第三方库][Elasticsearch]详细讲解
目录
1.介绍
Elasticsearch,简称ES,它是个开源分布式搜索引擎- 特点:分布式,零配置,自动发现,索引自动分片,索引副本机制,
restful风格接口,多数据源,自动搜索负载等 - 它可以近乎实时的存储、检索数据;本身扩展性很好,可以扩展到上百台服务器,处理
PB级别的数据 ES也使用Java开发并使用Lucene作为其核心来实现所有索引和搜索的功能,但是它的目的是通过简单的RESTfulAPI来隐藏Lucene的复杂性,从而让全文搜索变得简单
- 特点:分布式,零配置,自动发现,索引自动分片,索引副本机制,
Elasticsearch是**面向文档**(document oriented)的- 这意味着它可以存储整个对象或文档(
document) - 然而它不仅仅是存储,还会索引(
index)每个文档的内容使之可以被搜索- 可以对文档(而非成行成列的数据)进行索引、搜索、排序、过滤
- 这意味着它可以存储整个对象或文档(
2.安装
1.ES
- 如果启动ES的时候出现报错:
解决方法:
# 调整ES虚拟内存,虚拟内存默认最大映射数为65530,无法满足ES系统要求, 需要调整为262144以上 sudo sysctl -w vm.max_map_count=262144 # 增加虚拟机内存配置 sudo vim /etc/elasticsearch/jvm.options # 新增如下内容 -Xms512m -Xmx512m Job for elasticsearch.service failed because the control process exited with error code. See "systemctl status elasticsearch.service" and "journalctl -xeu elasticsearch.service" for details. 设置外网访问:默认只能在本机进行访问,修改后浏览器访问IP:PORT
vim /etc/elasticsearch/elasticsearch.yml # 新增配置 network.host: 0.0.0.0 http.port: 9200 cluster.initial_master_nodes: ["node-1"]验证ES是否安装成功:
curl -X GET "http://localhost:9200/"查看ES服务的状态:
sudo systemctl status elasticsearch.service 安装ik分词器插件:
sudo /usr/share/elasticsearch/bin/elasticsearch-plugin install\ https://get.infini.cloud/elasticsearch/analysis-ik/7.17.21 启动ES:
sudo systemctl start elasticsearch 安装ES:
sudoapt-getinstallelasticsearch=7.17.21 更新软件包列表:
sudoapt update 添加镜像源仓库:
echo"deb https://artifacts.elastic.co/packages/7.x/apt stable main"\|sudotee /etc/apt/sources.list.d/elasticsearch.list 添加仓库密钥:上边的添加方式会导致一个apt-key的警告,如果不想报警告使用下边这个
# 1.wget -qO - https://artifacts.elastic.co/GPG-KEY-elasticsearch |sudo apt-key add - # 2.curl -s https://artifacts.elastic.co/GPG-KEY-elasticsearch |\sudo gpg --no-default-keyring \ --keyring gnupg-ring:/etc/apt/trusted.gpg.d/icsearch.gpg --import 2.Kibana
- 配置Kibana(可选):根据需要配置
Kibana,配置文件通常位于/etc/kibana/kibana.yml,可能需要设置如服务器地址、端口、Elasticsearch URL等 - 访问Kibana:
http://<ip>:5601
设置开机自启(可选):
sudo systemctl enable kibana 启动Kibana:
sudo systemctl start kibana 安装Kibana:
sudoaptinstall kibana 3.ES核心概念
1.索引(index)
- 一个索引就是一个拥有几分相似特征的文档的集合
- 例如:
- 有一个客户数据的索引,一个产品目录的索引,还有一个订单数据的索引
- 一个索引由一个名字来标识(必须全部是小写字母的),并且当要对应于这个索引中的文档进行索引、搜索、更新和删除的时候,都要使用到这个名字
- 例如:
- 在一个集群中,可以定义任意多的索引
- 索引类似于数据库中库的概念
- 数据库中的库,表示了一组数据的集合
- ES中的索引,是一组相似特征数据的集合
2.类型(Type)
- 在一个索引中,可以定义一种或多种类型
- 一个类型是索引的一个逻辑上的分类/分区,其语义完全由用户来定
- 通常,会为具有一组共同字段的文档定义一个类型
- 例如:
- 运营一个博客平台并且将所有的数据存储到一个索引中
- 在这个索引中,可以为用户数据定义一个类型,为博客数据定义另一个类型,为评论数据定义另一个类型
- 例如:
- [类型]类似于数据库中表的概念,在索引的概念下,又对数据集合进行了一层细分
- 现在[类型]几乎已经弃用
3.字段(Field)
- 字段相当于是数据库表的字段,对文档数据根据不同属性进行的分类标识 -> 数据类型
![[Pasted image 20240918180030.png]]
4.映射(mapping)
- 映射是在处理数据的方式和规则方面做一些限制
- 某个字段的数据类型、默认值、分析器、是否被索引等等,这些都是映射里面可以设置的
- 映射类似于告诉ES哪些字段需要分词,做出索引映射,能够进行数据检索
- 其它就是处理ES里面数据的一些使用规则设置也叫做映射
- 某个字段的数据类型、默认值、分析器、是否被索引等等,这些都是映射里面可以设置的
- 按着最优规则处理数据对性能提高很大,因此才需要建立映射,并且需要思考如何建立映射才能对性能更好
- 具体规则:
enabled:是否仅作存储,不做搜索和分析- 取值:
true(默认)/false
- 取值:
index:是否构建倒排索引(决定了是否分词,是否被索引)- 取值:
true(默认)/false
- 取值:
index_optiondynamic:控制mapping的自动更新- 取值:
true(默认)/false
- 取值:
doc_value:是否开启doc_value,用户聚合和排序分析,分词字段不能使用- 取值:
true(默认)/false
- 取值:
fielddata:是否为text类型启动fielddata,实现排序和聚合分析- 针对分词字段,参与排序或聚合时能提高性能
store:是否单独设置此字段的是否存储而从_source字段中分离- 取值:
true/false(默认)
- 取值:
coerce:是否开启自动数据类型转换功能,如字符串转整形,浮点转整形- 取值:
true(默认)/false
- 取值:
analyzer:指定分词器,默认分词器是standard analyzer- 示例:
”analyzer”: “ik”
- 示例:
boost:字段级别的分数加权,默认值是1.0- 示例:
”boost”: 1.25
- 示例:
data_detection:是否自动识别日期类型- 取值:
true(默认)/false
- 取值:
fields:对一个字段提供多种索引模式,同一个字段的值,一个分词一个不分词
"fields":{"raw":{"type":"text","index":"not_analyzed"}}不分词字段统一建议使用doc_value
fielddata":{"format":"disabled"}5.文档(document)
- 一个文档是一个可被索引的基础信息单元
- 例如:某一个客户的文档,某一个产品的一个文档或者某个订单的一个文档
- 文档以JSON格式来表示,而JSON是一个到处存在的互联网数据交互格式
- 在一个
index/type里面,可以存储任意多的文档 - 一个文档必须被索引或者赋予一个索引的
type
Elasticsearch与传统关系性数据库相比:
| DB | Database | Table | Row | Column |
|---|---|---|---|---|
| ES | Index | Type | Document | Field |
4.Kibana访问ES进行测试
- 新增数据:
查询所有数据:
POST/user/_doc/_search {"query":{"match_all":{}}}删除索引:
DELETE/user 查看并搜索数据:
GET/user/_doc/_search?pretty {"query":{"bool":{"must_not":[{"terms":{"user_id.keyword":["USER4b862aaa-2df8654a-7eb4bb65e3507f66","USER14eeeaa5-442771b9-0262e455e4663d1d","USER484a6734-03a124f0-996c169dd05c1869"]}}],"should":[{"match":{"user_id":"昵称"}},{"match":{"nickname":"昵称"}},{"match":{"phone":"昵称"}}]}}}便于阅读:
[{"index":{"_id":"1"},"user":{"user_id":"USER4b862aaa-2df8654a-7eb4bb65e3507f66","nickname":"昵称1","phone":"手机号1","description":"签名1","avatar_id":"头像1"}},{"index":{"_id":"2"},"user":{"user_id":"USER14eeeaa5-442771b9-0262e455e4663d1d","nickname":"昵称2","phone":"手机号2","description":"签名2","avatar_id":"头像2"}},{"index":{"_id":"3"},"user":{"user_id":"USER484a6734-03a124f0-996c169dd05c1869","nickname":"昵称3","phone":"手机号3","description":"签名3","avatar_id":"头像3"}},{"index":{"_id":"4"},"user":{"user_id":"USER186ade83-4460d4a6-8c08068f83127b5d","nickname":"昵称4","phone":"手机号4","description":"签名4","avatar_id":"头像4"}},{"index":{"_id":"5"},"user":{"user_id":"USER6f19d074-c33891cf-23bf5a8357189a19","nickname":"昵称5","phone":"手机号5","description":"签名5","avatar_id":"头像5"}},{"index":{"_id":"6"},"user":{"user_id":"USER97605c64-9833ebb7-d045535335a59195","nickname":"昵称6","phone":"手机号6","description":"签名6","avatar_id":"头像6"}}]插入形式:
POST/user/_doc/_bulk {"index":{"_id":"1"}}{"user_id":"USER4b862aaa-2df8654a-7eb4bb65e3507f66","nickname":"昵称1","phone":"手机号1","description":"签名1","avatar_id":"头像1"}{"index":{"_id":"2"}}{"user_id":"USER14eeeaa5-442771b9-0262e455e4663d1d","nickname":"昵称2","phone":"手机号2","description":"签名2","avatar_id":"头像2"}{"index":{"_id":"3"}}{"user_id":"USER484a6734-03a124f0-996c169dd05c1869","nickname":"昵称3","phone":"手机号3","description":"签名3","avatar_id":"头像3"}{"index":{"_id":"4"}}{"user_id":"USER186ade83-4460d4a6-8c08068f83127b5d","nickname":"昵称4","phone":"手机号4","description":"签名4","avatar_id":"头像4"}{"index":{"_id":"5"}}{"user_id":"USER6f19d074-c33891cf-23bf5a8357189a19","nickname":"昵称5","phone":"手机号5","description":"签名5","avatar_id":"头像5"}{"index":{"_id":"6"}}{"user_id":"USER97605c64-9833ebb7-d045535335a59195","nickname":"昵称6","phone":"手机号6","description":"签名6","avatar_id":"头像6"}创建索引库:
POST/user/_doc {"settings":{"analysis":{"analyzer":{"ik":{"tokenizer":"ik_max_word"}}}},"mappings":{"dynamic":true,"properties":{"nickname":{"type":"text","analyzer":"ik_max_word"},"user_id":{"type":"keyword","analyzer":"standard"},"phone":{"type":"keyword","analyzer":"standard"},"description":{"type":"text","enabled":false},"avatar_id":{"type":"keyword","enabled":false}}}}5.ES客户端的安装
安装:
# 克隆代码git clone https://github.com/seznam/elasticlient # 切换目录cd elasticlient # 更新子模块git submodule update --init --recursive # 编译代码make build &&cd build cmake ..make# 安装makeinstall前置安装:依赖MicroHTTPD库
sudoapt-getinstall libmicrohttpd-dev 6.ES客户端接口介绍
/** * Perform search on nodes until it is successful. Throws exception if all nodes * has failed to respond. * \param indexName specification of an Elasticsearch index. * \param docType specification of an Elasticsearch document type. * \param body Elasticsearch request body. * \param routing Elasticsearch routing. If empty, no routing has been used. * * \return cpr::Response if any of node responds to request. * \throws ConnectionException if all hosts in cluster failed to respond. */ cpr::Response search(const std::string &indexName,const std::string &docType,const std::string &body,const std::string &routing = std::string());/** * Get document with specified id from cluster. Throws exception if all nodes * has failed to respond. * \param indexName specification of an Elasticsearch index. * \param docType specification of an Elasticsearch document type. * \param id Id of document which should be retrieved. * \param routing Elasticsearch routing. If empty, no routing has been used. * * \return cpr::Response if any of node responds to request. * \throws ConnectionException if all hosts in cluster failed to respond. */ cpr::Response get(const std::string &indexName,const std::string &docType,const std::string &id = std::string(),const std::string &routing = std::string());/** * Index new document to cluster. Throws exception if all nodes has failed to respond. * \param indexName specification of an Elasticsearch index. * \param docType specification of an Elasticsearch document type. * \param body Elasticsearch request body. * \param id Id of document which should be indexed. If empty, id will be generated * automatically by Elasticsearch cluster. * \param routing Elasticsearch routing. If empty, no routing has been used. * * \return cpr::Response if any of node responds to request. * \throws ConnectionException if all hosts in cluster failed to respond. */ cpr::Response index(const std::string &indexName,const std::string &docType,const std::string &id,const std::string &body,const std::string &routing = std::string());/** * Delete document with specified id from cluster. Throws exception if all nodes * has failed to respond. * \param indexName specification of an Elasticsearch index. * \param docType specification of an Elasticsearch document type. * \param id Id of document which should be deleted. * \param routing Elasticsearch routing. If empty, no routing has been used. * * \return cpr::Response if any of node responds to request. * \throws ConnectionException if all hosts in cluster failed to respond. */ cpr::Response remove(const std::string &indexName,const std::string &docType,const std::string &id,const std::string &routing = std::string());7.使用
- 地址后边不要忘了相对根目录:
http://127.0.0.1:9200/ - ES客户端API使用时,要进行异常捕捉,否则操作失败会导致程序异常退出
ES客户端使用注意:
#include<iostream>#include<elasticlient/client.h>#include<cpr/cpr.h>intmain(){// 1.构造ES客户端 elasticlient::Client client({"http://127.0.0.1:9200/"});// 2.发起搜索请求try{auto resp = client.search("user","_doc","{\"query\": { \"match_all\":{} }}"); std::cout << resp.status_code << std::endl; std::cout << resp.text << std::endl;}catch(std::exception &e){ std::cout << e.what()<< std::endl;return-1;}return0;}