学习笔记-微服务基础（黑马程序员）

框架

spring cloud
spring cloud alibaba

Eureka

eureka-server
- 注册中心
eureka-client
- 客户端
- 每30s发送心跳
- 服务
  - 服务消费者
  - 服务提供者

server

依赖

<dependency><groupId>org.springframework.cloud</groupId><artifactId>spring-cloud-starter-netflix-eureka-server</artifactId>
</dependency>

启动类

添加注解
- @EnableEurekaServer

配置文件

application.yml

server:port: 10086       # 端口号
spring:application:      name: eurekaserver  # eureka服务名称
eureka:client:service-url:  # eureka的地址，需要将自己注册到eureka中defaultZone: http://127.0.0.1:10086/eureka

client

依赖

<dependency><groupId>org.springframework.cloud</groupId><artifactId>spring-cloud-starter-netflix-eureka-client</artifactId>
</dependency>

配置文件

application.yml

spring:application:name: userservice  # 需要注册的服务名称
eureka:client:service-url:       # 本服务地址，需要注册到eureka中defaultZone: http://127.0.0.1:10086/eureka

服务拉取和负载均衡

添加注解
- @LoadBlanced

@Bean
@LoadBlanced // 负载均衡
public RestTemplate restTemplate(){return new RestTemplate();
}

修改url

// restTemplate请求
String url = "http://userservice/xxx";

Ribbon负载均衡

自定义负载均衡策略

1、定义新的IRule,将轮询策略（默认）变成随机策略

@Bean
public IRule randomRule(){return new RandomRule();
}

2、配置文件方式

userservice: # 给某个微服务配置负载均衡规则，这里是userservice服务ribbon:NFLoadBalancerRuleClassName: com.netflix.loadbalancer.RandomRule # 负载均衡规则

饥饿加载

默认懒加载
- 第一次访问时才会去创建LoadBalanceClient
开启饥饿加载

ribbon:eager-load:enabled: trueclients: userservice

Nacos

依赖

父工程

<dependencyManagement><dependencies><!--springcloud--><!--mysql--><!--mybatis plus--><dependency><groupId>com.alibaba.cloud</groupId><artifactId>spring-cloud-alibaba-dependencies</artifactId><version>2.2.6.RELEASE</version><type>pom</type><scope>import</scope></dependency></dependencies>
</dependencyManagement>

客户端

<dependency><groupId>com.alibaba.cloud</groupId><artifactId>spring-cloud-starter-alibaba-nacos-discovery</artifactId>
</dependency>

spring:cloud:nacos:server-addr: localhost:8848

配置集群

优先选择本地集群

添加集群

spring:cloud:nacos:server-addr: localhost:8848discovery:cluster-name: xx # 集群名称

修改负载均衡规则

userservice:ribbon:NFLoadBalancerRuleClassName: com.alibaba.cloud.nacos.ribbon.NacosRule # 负载均衡规则

配置权重

nacos控制台->实例列表->编辑->修改权重

环境隔离

Namespace
- Group
  - service/data

配置namespace

需要新建namespace
修改配置

spring:cloud:nacos:server-addr: localhost:8848discovery:cluster-name: xxnamespace: xxxx # 命名空间，填ID

永久实例

临时实例
- 果实例宕机超过一定时间，会从服务列表剔除
非临时实例/永久实例
- 实例宕机，不会从服务列表剔除

spring:cloud:nacos:discovery:ephemeral: false # 设置为非临时实例

配置管理

data id
- xxx-dev.yaml
group
- default_group
配置内容
- 需要热更新的配置有必要放到nacos管理
- 基本不会变更的一些配置保存在微服务本地

依赖

<!--nacos配置管理依赖-->
<dependency><groupId>com.alibaba.cloud</groupId><artifactId>spring-cloud-starter-alibaba-nacos-config</artifactId>
</dependency>

bootstrao.yaml

spring:application:name: userservice # 服务名称profiles:active: dev #开发环境 cloud:nacos:server-addr: localhost:8848 # Nacos地址config:file-extension: yaml # 文件后缀名

配置热更新

方式一
- 添加注解
  - @RefreshScope
方式二
- @ConfigurationProperties代替@Value


@Component
@Data
@ConfigurationProperties(prefix = "xx")
public class Xxxx {private String xx;
}

配置共享

创建[servename].yaml
- 多环境共享
配置文件组成
- [spring.application.name]-[spring.profiles.active].yaml
  - 运行环境
- [spring.application.name].yaml
  - 公共

配置优先级

[spring.application.name]-[spring.profiles.active].yaml
[spring.application.name].yaml
本地配置

feign

使用

依赖

<dependency><groupId>org.springframework.cloud</groupId><artifactId>spring-cloud-starter-openfeign</artifactId>
</dependency>

Application添加注解

@EnableFeignClients

客户端

@FeignClient("xxxservice")
public interface XxxClient {}

自定义配置

区分全局和单个服务
- feign.client.config.xxservice.loggerLevel
  - xxservice服务
- feign.client.config.default.loggerLevel
  - 全局
feign.Logger.Level
- 修改日志级别
  - NONE
  - BASIC
  - HEADERS
  - FULL
feign.codec.Decoder
- 响应结果的解析器
  - http远程调用的结果做解析
  - 解析json字符串为java对象
feign.codec.Encoder
- 请求参数编码
  - 将请求参数编码
  - 便于通过http请求发送
feign.Contract
- 支持的注解格式
  - 默认是SpringMVC的注解
feign.Retryer
- 失败重试机制

使用优化

日志级别尽量用basic
HttpClient或OKHttp代替URLConnection
- Feign底层发起http请求
  - URLConnection
    - 默认实现，不支持连接池
  - Apache HttpClient
    - 支持连接池
  - OKHttp
    - 支持连接池

替换为httpclient

依赖

<dependency><groupId>io.github.openfeign</groupId><artifactId>feign-httpclient</artifactId>
</dependency>

配置文件

feign:client:config:default: # default全局的配置loggerLevel: BASIC # 日志级别，BASIC就是基本的请求和响应信息httpclient:enabled: true # 开启feign对HttpClient的支持max-connections: 200 # 最大的连接数max-connections-per-route: 50 # 每个路径的最大连接数

最佳实践

将Feign的Client抽取为独立模块
并且把接口有关的POJO、默认的Feign配置都放到这个模块中
在服务生产者、消费者中引入该模块
指定扫描接口
- @EnableFeignClients(clients = {XXXClient.class})
- @EnableFeignClients(basePackages = “xxx.clients”)

gateway

功能
- 身份认证和权限校验
- 服务路由、负载均衡
- 请求限流

搭建

依赖

<!--网关-->
<dependency><groupId>org.springframework.cloud</groupId><artifactId>spring-cloud-starter-gateway</artifactId>
</dependency>
<!--nacos服务发现依赖-->
<dependency><groupId>com.alibaba.cloud</groupId><artifactId>spring-cloud-starter-alibaba-nacos-discovery</artifactId>
</dependency>

启动类


@SpringBootApplication
public class GatewayApplication {public static void main(String[] args) {SpringApplication.run(GatewayApplication.class, args);}
}

路由规则

server:port: 10010 # 网关端口
spring:application:name: gateway # 服务名称cloud:nacos:server-addr: localhost:8848 # nacos地址gateway:routes: # 网关路由配置- id: user-service # 路由id，自定义，只要唯一即可# uri: http://127.0.0.1:8081 # 路由的目标地址 http就是固定地址uri: lb://userservice # 路由的目标地址 lb就是负载均衡，后面跟服务名称predicates: # 路由断言，也就是判断请求是否符合路由规则的条件- Path=/user/** # 这个是按照路径匹配，只要以/user/开头就符合要求

断言工厂

断言Path=/xx/**
- org.springframework.cloud.gateway.handler.predicate.PathRoutePredicateFactory处理
其他
- 时间断言
  - After
  - Before
  - Between
- 请求
  - Cookie
  - Header
  - Host
  - Method
  - Path
  - Query
  - RemoteAddr
- 权重
  - Weight

过滤工厂

种类
- AddRequestHeader
  - 给当前请求添加一个请求头
- RemoveRequestHeader
  - 移除请求中的一个请求头
- AddResponseHeader
  - 给响应结果中添加一个响应头
- RemoveResponseHeader
  - 从响应结果中移除有一个响应头
- RequestRateLimiter
  - 限制请求的流量
局部添加

spring:cloud:gateway:routes:- id: user-service uri: lb://userservice predicates: - Path=/user/** filters: # 过滤器- AddRequestHeader=xx, xxxxx # 添加请求头

全局添加

spring:cloud:gateway:routes:- id: user-service uri: lb://userservice predicates: - Path=/user/**default-filters: # 默认过滤项- AddRequestHeader=xx, xxxxx

自定义全局过滤器


@Order(-1)
@Component
public class AuthorizeFilter implements GlobalFilter {@Overridepublic Mono<Void> filter(ServerWebExchange exchange, GatewayFilterChain chain) {// 1.获取请求参数MultiValueMap<String, String> params = exchange.getRequest().getQueryParams();// 2.获取authorization参数String auth = params.getFirst("authorization");// 3.校验if ("admin".equals(auth)) {// 放行return chain.filter(exchange);}// 4.拦截// 4.1.禁止访问，设置状态码exchange.getResponse().setStatusCode(HttpStatus.FORBIDDEN);// 4.2.结束处理return exchange.getResponse().setComplete();}
}

过滤器顺序

过滤器必须指定一个order值
order值越小，优先级越高，执行顺序越靠前
order值一样时，会按照 defaultFilter > 路由过滤器 > GlobalFilter的顺序执行

跨域

spring:cloud:gateway:# 。。。globalcors: # 全局的跨域处理add-to-simple-url-handler-mapping: true # 解决options请求被拦截问题corsConfigurations:'[/**]':allowedOrigins: # 允许哪些网站的跨域请求 - "http://localhost:8090"allowedMethods: # 允许的跨域ajax的请求方式- "GET"- "POST"- "DELETE"- "PUT"- "OPTIONS"allowedHeaders: "*" # 允许在请求中携带的头信息allowCredentials: true # 是否允许携带cookiemaxAge: 360000 # 这次跨域检测的有效期

docker

架构
- 镜像
  - image
- 容器
  - container
dockerhub
- 镜像托管平台
docker
- client
  - 向Docker服务端发送指令
- server
  - Docker守护进程
镜像名称
命令
- systemctl start docker
- systemctl stop docker
- systemctl restart docker
- docker -v
- docker --help
镜像命令
- docker pull 镜像
- docker push 镜像
- docker rmi 镜像
- docker images
- docker save -o xxx 镜像
- docker load -i xxx
容器命令
- docker run --name 容器名 -p 宿主机port:容器内port -d 镜像
  - d：后运行
- docker pause
- docker unpause
- docker start
- docker stop
- docker logs -f 容器名
  - f:持续
- docker ps
- docker exec -it 容器名 bash
  - it:进去当前容器创建标准输入输出终端
  - bash:进入后执行命令
- docker rm -f 容器名

数据卷

volume
- 虚拟目录，指向宿主机文件系统中的某个目录
命令
- docker volume create
- docker volume inspect
- docker volume ls
- docker volume prune
- docker volume rm
挂载
- docker run -name mn -v xxxx:/xx/xx -p xx:xx xxx
- 宿主机目录可直接挂载

dockerfile

镜像结构
- 入口：镜像应用启动命令
- 层layer
- 基础镜像
dockerfile
- 指令
  - FROM
  - ENV
  - COPY
  - RUN
  - EXPOSE
  - ENTRYPOINT

dockercompose

功能
- 快速的部署分布式应用，无需手动一个个创建和运行

MQ

MQ
- RabbitMQ
- ActiveMQ
- RocketMQ
- Kafka

RabbitMQ

publisher：生产者
consumer：消费者
exchange个：交换机，负责消息路由
queue：队列，存储消息
virtualHost：虚拟主机，隔离不同租户的exchange、queue、消息的隔离

消息模型

基本消息队列
工作消息队列
发布订阅
- 广播
- 路由
- 主题

demo

 ConnectionFactory factory = new ConnectionFactory();
// 1.1.设置连接参数，分别是：主机名、端口号、vhost、用户名、密码
factory.setHost("192.168.150.101");
factory.setPort(5672);
factory.setVirtualHost("/");
factory.setUsername("itcast");
factory.setPassword("123321");
// 1.2.建立连接
Connection connection = factory.newConnection();// 2.创建通道Channel
Channel channel = connection.createChannel();// 3.创建队列
String queueName = "simple.queue";
channel.queueDeclare(queueName, false, false, false, null);// 4.发送消息
String message = "hello, rabbitmq!";
channel.basicPublish("", queueName, null, message.getBytes());
System.out.println("发送消息成功：【" + message + "】");// 5.关闭通道和连接
channel.close();
connection.close();

 // 1.建立连接
ConnectionFactory factory = new ConnectionFactory();
// 1.1.设置连接参数，分别是：主机名、端口号、vhost、用户名、密码
factory.setHost("192.168.150.101");
factory.setPort(5672);
factory.setVirtualHost("/");
factory.setUsername("itcast");
factory.setPassword("123321");
// 1.2.建立连接
Connection connection = factory.newConnection();// 2.创建通道Channel
Channel channel = connection.createChannel();// 3.创建队列
String queueName = "simple.queue";
channel.queueDeclare(queueName, false, false, false, null);// 4.订阅消息
channel.basicConsume(queueName, true, new DefaultConsumer(channel){@Overridepublic void handleDelivery(String consumerTag, Envelope envelope,AMQP.BasicProperties properties, byte[] body) throws IOException {// 5.处理消息String message = new String(body);System.out.println("接收到消息：【" + message + "】");}
});
System.out.println("等待接收消息。。。。");

SpringAMQP

父工程依赖

<!--AMQP依赖，包含RabbitMQ-->
<dependency><groupId>org.springframework.boot</groupId><artifactId>spring-boot-starter-amqp</artifactId>
</dependency>

消息发送

spring:rabbitmq:host: localhost # 主机名port: 5672 # 端口virtual-host: / # 虚拟主机username: xxx # 用户名password: xxx # 密码

@Autowired
private RabbitTemplate rabbitTemplate;@Test
public void testSimpleQueue() {// 队列名称String queueName = "simple.queue";// 消息String message = "hello, spring amqp!";// 发送消息rabbitTemplate.convertAndSend(queueName, message);
}

消息接收

spring:rabbitmq:host: localhost # 主机名port: 5672 # 端口virtual-host: / # 虚拟主机username: xxx # 用户名password: xxx # 密码

@RabbitListener(queues = "simple.queue")
public void listenSimpleQueueMessage(String msg) throws InterruptedException {System.out.println("spring 消费者接收到消息：【" + msg + "】");
}

WorkQueue

让多个消费者绑定到一个队列，共同消费队列中的消息

消息发送

public void testWorkQueue() throws InterruptedException {// 队列名称String queueName = "simple.queue";// 消息String message = "hello, message_";for (int i = 0; i < 50; i++) {// 发送消息rabbitTemplate.convertAndSend(queueName, message + i);Thread.sleep(20);}
}

消息接收

@RabbitListener(queues = "simple.queue")
public void listenWorkQueue1(String msg) throws InterruptedException {System.out.println("消费者1接收到消息：【" + msg + "】" + LocalTime.now());Thread.sleep(20);
}@RabbitListener(queues = "simple.queue")
public void listenWorkQueue2(String msg) throws InterruptedException {System.err.println("消费者2........接收到消息：【" + msg + "】" + LocalTime.now());Thread.sleep(200);
}

取消消息预取

spring:rabbitmq:listener:simple:prefetch: 1 # 每次只能获取一条消息，处理完成才能获取下一个消息

发布订阅

fanout exchange

广播,将消息交给所有绑定到交换机的队列

声明队列和交换机

@Configuration
public class FanoutConfig {/*** 声明交换机* @return Fanout类型交换机*/@Beanpublic FanoutExchange fanoutExchange(){return new FanoutExchange("itcast.fanout");}/*** 第1个队列*/@Beanpublic Queue fanoutQueue1(){return new Queue("fanout.queue1");}/*** 绑定队列和交换机*/@Beanpublic Binding bindingQueue1(Queue fanoutQueue1, FanoutExchange fanoutExchange){return BindingBuilder.bind(fanoutQueue1).to(fanoutExchange);}/*** 第2个队列*/@Beanpublic Queue fanoutQueue2(){return new Queue("fanout.queue2");}/*** 绑定队列和交换机*/@Beanpublic Binding bindingQueue2(Queue fanoutQueue2, FanoutExchange fanoutExchange){return BindingBuilder.bind(fanoutQueue2).to(fanoutExchange);}
}

发布

 // 队列名称
String exchangeName = "itcast.fanout";
// 消息
String message = "hello, everyone!";
rabbitTemplate.convertAndSend(exchangeName, "", message);

@RabbitListener(queues = "fanout.queue1")
public void listenFanoutQueue1(String msg) {System.out.println("消费者1接收到Fanout消息：【" + msg + "】");
}@RabbitListener(queues = "fanout.queue2")
public void listenFanoutQueue2(String msg) {System.out.println("消费者2接收到Fanout消息：【" + msg + "】");
}

Direct

定向，把消息交给符合指定routing key 的队列

基于注解声明队列和交换机

@RabbitListener(bindings = @QueueBinding(value = @Queue(name = "direct.queue1"),exchange = @Exchange(name = "itcast.direct", type = ExchangeTypes.DIRECT),key = {"red", "blue"}
))
public void listenDirectQueue1(String msg){System.out.println("消费者接收到direct.queue1的消息：【" + msg + "】");
}@RabbitListener(bindings = @QueueBinding(value = @Queue(name = "direct.queue2"),exchange = @Exchange(name = "itcast.direct", type = ExchangeTypes.DIRECT),key = {"red", "yellow"}
))
public void listenDirectQueue2(String msg){System.out.println("消费者接收到direct.queue2的消息：【" + msg + "】");
}

发布

@Test
public void testSendDirectExchange() {// 交换机名称String exchangeName = "itcast.direct";// 消息String message = "xxx";// 发送消息rabbitTemplate.convertAndSend(exchangeName, "red", message);
}

Topic

通配符，把消息交给符合routing pattern（路由模式）的队列

发布

@Test
public void testSendTopicExchange() {// 交换机名称String exchangeName = "itcast.topic";// 消息String message = "xxx";// 发送消息rabbitTemplate.convertAndSend(exchangeName, "china.news", message);
}

@RabbitListener(bindings = @QueueBinding(value = @Queue(name = "topic.queue1"),exchange = @Exchange(name = "itcast.topic", type = ExchangeTypes.TOPIC),key = "china.#"
))
public void listenTopicQueue1(String msg){System.out.println("消费者接收到topic.queue1的消息：【" + msg + "】");
}@RabbitListener(bindings = @QueueBinding(value = @Queue(name = "topic.queue2"),exchange = @Exchange(name = "itcast.topic", type = ExchangeTypes.TOPIC),key = "#.news"
))
public void listenTopicQueue2(String msg){System.out.println("消费者接收到topic.queue2的消息：【" + msg + "】");
}

消息序列化

依赖

<dependency><groupId>com.fasterxml.jackson.dataformat</groupId><artifactId>jackson-dataformat-xml</artifactId><version>2.9.10</version>
</dependency>

配置bean

@Bean
public MessageConverter jsonMessageConverter(){return new Jackson2JsonMessageConverter();
}

发送对象

// 准备消息
Map<String,Object> msg = new HashMap<>();
msg.put("name", "Jack");
msg.put("age", 21);
// 发送消息
rabbitTemplate.convertAndSend("simple.queue","", msg);

接收

@RabbitListener(queues = "simple.queue")
public void listenSimpleQueueMessage(Map<String,Object> msg) throws InterruptedException {System.out.println("spring 消费者接收到消息：【" + msg + "】");
}

elasticsearch

包含
- elasticsearch
- kibana 可视化界面
- ik分词器
  - ik_smart
    - 智能切分，粗粒度
  - ik_max_word
    - 最细切分，细粒度
  - 可以配置扩展词和停用词条

开源搜索引擎

倒排索引
- 文档（Document）
- 词条（Term）
索引（Index）
- 相同类型的文档的集合
- 索引当做是数据库中的表
映射（mapping）
- 索引中文档的字段约束信息
- 类似表的结构约束
文档（Document）
- 类似数据库中的行（Row）
字段（Field）
- 类似数据库中的列（Column）
DSL
- JSON风格的请求语句，用来操作elasticsearch，实现CRUD

索引库操作

mapping
- type
  - 字符串：text,keyword
  - 数值：long,integer,short,byte,double,float
  - 布尔：boolean
  - 日期：date
  - 对象：object
- index
  - 是否创建索引
  - 默认 true
- analyzer
  - 使用哪种分词器
- properties
  - 字段的子字段
创建索引库

PUT /索引库名称
{"mappings":{"properties":{"字段1":{"type":"text","analyzer":"ik_smart"},"字段2":{"type":"keyword","index":"false"},"字段3":{"properties":{"子字段1":{"type":"keyword"}}}}}
}

查询

GET /索引库名称

删除

DELETE /索引库名称

添加新字段

PUT /索引库名称/_mapping
{"properties":{"新字段名":{"type":"integer"}}
}

文档操作

新增

POST /索引库名称/_doc/文档id
{"字段1":"值1","字段2":"值2","字段3":"值3","字段4":{"子字段1":"值"}
}

查询

GET /索引库名称/_doc/id

删除

DELETE /索引库名称/_doc/id

修改文档
全量修改

PUT /索引库名称/_doc/文档id
{"字段1":"值1","字段2":"值2","字段3":"值3","字段4":{"子字段1":"值"}
}

局部修改

POST /索引库名称/_update/文档id
{"doc":{"字段1":"新值"}
}
``## RestClient
- 依赖
```xml
<dependency><groupId>org.elasticsearch.client</groupId><artifactId>elasticsearch-rest-high-level-client</artifactId>
</dependency>

覆盖elasticsearch版本

<properties><java.version>1.8</java.version><elasticsearch.version>7.12.1</elasticsearch.version>
</properties>

RestHighLevelClient

RestHighLevelClient client = new RestHighLevelClient(RestClient.builder(HttpHost.create("http://xx.xx.xx.xx:9200")
));
// 关闭
// client.close()

索引库操作

创建索引库

 // 1.创建Request对象
CreateIndexRequest request = new CreateIndexRequest("hotel");
// 2.准备请求的参数：DSL语句 
// MAPPING_TEMPLATE 创建索引库语句
request.source(MAPPING_TEMPLATE, XContentType.JSON);
// 3.发送请求
client.indices().create(request, RequestOptions.DEFAULT);

删除索引库

// 1.创建Request对象
DeleteIndexRequest request = new DeleteIndexRequest("hotel");
// 2.发送请求
client.indices().delete(request, RequestOptions.DEFAULT);

判断索引库是否存在

// 1.创建Request对象
GetIndexRequest request = new GetIndexRequest("hotel");
// 2.发送请求
boolean exists = client.indices().exists(request, RequestOptions.DEFAULT);
// 3.输出
System.err.println(exists?"存在":"不存在");

文档操作

新增

// 1.根据id查询酒店数据
Hotel hotel = hotelService.getById(id);
// 2.转换为文档类型
HotelDoc hotelDoc = new HotelDoc(hotel);
// 3.将HotelDoc转json
String json = JSON.toJSONString(hotelDoc);// 1.准备Request对象
IndexRequest request = new IndexRequest("hotel").id(hotelDoc.getId().toString());
// 2.准备Json文档
request.source(json, XContentType.JSON);
// 3.发送请求
client.index(request, RequestOptions.DEFAULT);

查询

// 1.准备Request
GetRequest request = new GetRequest("hotel", id);
// 2.发送请求，得到响应
GetResponse response = client.get(request, RequestOptions.DEFAULT);
// 3.解析响应结果
String json = response.getSourceAsString();HotelDoc hotelDoc = JSON.parseObject(json, HotelDoc.class);
System.out.println(hotelDoc);

删除

// 1.准备Request
DeleteRequest request = new DeleteRequest("hotel", id);
// 2.发送请求
client.delete(request, RequestOptions.DEFAULT);

修改

// 1.准备Request
UpdateRequest request = new UpdateRequest("hotel", id);
// 2.准备请求参数
request.doc("price", "xxx","starName", "xxx"
);
// 3.发送请求
client.update(request, RequestOptions.DEFAULT);

批量导入

// 批量查询酒店数据
List<Hotel> hotels = hotelService.list();// 1.创建Request
BulkRequest request = new BulkRequest();
// 2.准备参数，添加多个新增的Request
for (Hotel hotel : hotels) {// 2.1.转换为文档类型HotelDocHotelDoc hotelDoc = new HotelDoc(hotel);// 2.2.创建新增文档的Request对象request.add(new IndexRequest("hotel").id(hotelDoc.getId().toString()).source(JSON.toJSONString(hotelDoc), XContentType.JSON));
}
// 3.发送请求
client.bulk(request, RequestOptions.DEFAULT);

DSL查询

DSL查询分类
- 查询所有
  - match_all
- 全文检索（full text）查询
  - match
  - multi_match
- 精确查询
  - ids
  - range
  - term
- 地理（geo）查询
  - geo_distance
  - geo_bounding_box
- 复合（compound）查询
  - bool
  - function_score

查询所有

GET /indexName/_search
{"query": {"查询类型": {"查询条件": "条件值"}}
}

全文检索

GET /indexName/_search
{"query": {"match": {"FIELD": "TEXT"}}
}

GET /indexName/_search
{"query": {"multi_match": {"query": "TEXT","fields": ["FIELD1", " FIELD12"]}}
}

精确查询

// term查询
GET /indexName/_search
{"query": {"term": {"FIELD": {"value": "VALUE"}}}
}

// range查询
GET /indexName/_search
{"query": {"range": {"FIELD": {"gte": xxx, // 这里的gte代表大于等于，gt则代表大于"lte": xxx // lte代表小于等于，lt则代表小于}}}
}

地理坐标查询

// geo_bounding_box查询
GET /indexName/_search
{"query": {"geo_bounding_box": {"FIELD": {"top_left": { // 左上点"lat": xxx,"lon": xxx},"bottom_right": { // 右下点"lat": xxx,"lon": xxx}}}}
}

// geo_distance 查询
GET /indexName/_search
{"query": {"geo_distance": {"distance": "15km", // 半径"FIELD": "xxx,xxx" // 圆心}}
}

复合查询

GET /hotel/_search
{"query":{"function_score":{"query":{"match":{"all":"xx"}},         // 原始查询"functions":[                           //算分函数{"filter":{"term":{"id":"xx"}},  // 过滤条件"weight":10                     // 算分权重}],"boost_mode":"multiply"                 // 加权模式}}
}

GET /hotel/_search
{"query": {"bool": {"must": [                                     // 与{"term": {"city": "xx" }}],"should": [                                   // 或{"term": {"brand": "xx" }},{"term": {"brand": "xx" }}],"must_not": [                                 // 非{ "range": { "price": { "lte": x } }}],"filter": [                                   // 必须匹配{ "range": {"score": { "gte": xx } }}]}}
}

排序

普通字段排序

GET /indexName/_search
{"query": {"match_all": {}},"sort": [{"FIELD": "desc"  // 排序字段、排序方式ASC、DESC}]
}

地理坐标排序

GET /indexName/_search
{"query": {"match_all": {}},"sort": [{"_geo_distance" : {"FIELD" : "纬度，经度", // 文档中geo_point类型的字段名、目标坐标点"order" : "asc", // 排序方式"unit" : "km" // 排序的距离单位}}]
}

分页

GET /hotel/_search
{"query": {"match_all": {}},"from": 0, // 分页开始的位置，默认为0"size": 10, // 期望获取的文档总数"sort": [{"price": "asc"}]
}

GET /hotel/_search
{"query": {"match_all": {}},"from": 990, // 分页开始的位置，默认为0"size": 10, // 期望获取的文档总数"sort": [{"price": "asc"}]
}

高亮

GET /hotel/_search
{"query": {"match_all": {}},"from": 0, // 分页开始的位置，默认为0"size": 10, // 期望获取的文档总数"sort": [{"price": "asc"}],"highlight":{"fields":{"name":{                  // 高亮字段"require_field_match":"false","pre_tags":"<em>","post_tags":"</em>"}}}
}

RestClient

handleResponse

private void handleResponse(SearchResponse response) {// 4.解析响应SearchHits searchHits = response.getHits();// 4.1.获取总条数long total = searchHits.getTotalHits().value;System.out.println("共搜索到" + total + "条数据");// 4.2.文档数组SearchHit[] hits = searchHits.getHits();// 4.3.遍历for (SearchHit hit : hits) {// 获取文档sourceString json = hit.getSourceAsString();// 反序列化HotelDoc hotelDoc = JSON.parseObject(json, HotelDoc.class);System.out.println("hotelDoc = " + hotelDoc);}
}

match_all

// 1.准备Request
SearchRequest request = new SearchRequest("hotel");
// 2.准备DSL
request.source().query(QueryBuilders.matchAllQuery());
// 3.发送请求
SearchResponse response = client.search(request, RequestOptions.DEFAULT);// 4.解析响应
handleResponse(response);

match

// 1.准备Request
SearchRequest request = new SearchRequest("hotel");
// 2.准备DSL
request.source().query(QueryBuilders.matchQuery("all", "如家"));
// 3.发送请求
SearchResponse response = client.search(request, RequestOptions.DEFAULT);
// 4.解析响应
handleResponse(response);

term

// 2.准备DSL
request.source().query(QueryBuilders.termQuery("city", "xxx"));

range

// 2.准备DSL
request.source().query(QueryBuilders.rangeQuery("price").gte(100).lte(150));

bool

// 1.准备Request
SearchRequest request = new SearchRequest("hotel");
// 2.准备DSL
// 2.1.准备BooleanQuery
BoolQueryBuilder boolQuery = QueryBuilders.boolQuery();
// 2.2.添加term
boolQuery.must(QueryBuilders.termQuery("city", "杭州"));
// 2.3.添加range
boolQuery.filter(QueryBuilders.rangeQuery("price").lte(250));request.source().query(boolQuery);
// 3.发送请求
SearchResponse response = client.search(request, RequestOptions.DEFAULT);
// 4.解析响应
handleResponse(response);

排序分页


// 页码，每页大小
int page = 1, size = 5;// 1.准备Request
SearchRequest request = new SearchRequest("hotel");
// 2.准备DSL
// 2.1.query
request.source().query(QueryBuilders.matchAllQuery());
// 2.2.排序 sort
request.source().sort("price", SortOrder.ASC);
// 2.3.分页 from、size
request.source().from((page - 1) * size).size(5);
// 3.发送请求
SearchResponse response = client.search(request, RequestOptions.DEFAULT);
// 4.解析响应
handleResponse(response);

高亮

// 1.准备Request
SearchRequest request = new SearchRequest("hotel");
// 2.准备DSL
// 2.1.query
request.source().query(QueryBuilders.matchQuery("all", "如家"));
// 2.2.高亮
request.source().highlighter(new HighlightBuilder().field("name").requireFieldMatch(false));
// 3.发送请求
SearchResponse response = client.search(request, RequestOptions.DEFAULT);
// 4.解析响应
SearchHits searchHits = response.getHits();
// 4.1.获取总条数
long total = searchHits.getTotalHits().value;
System.out.println("共搜索到" + total + "条数据");
// 4.2.文档数组
SearchHit[] hits = searchHits.getHits();
// 4.3.遍历
for (SearchHit hit : hits) {// 获取文档sourceString json = hit.getSourceAsString();// 反序列化HotelDoc hotelDoc = JSON.parseObject(json, HotelDoc.class);// 获取高亮结果Map<String, HighlightField> highlightFields = hit.getHighlightFields();if (!CollectionUtils.isEmpty(highlightFields)) {// 根据字段名获取高亮结果HighlightField highlightField = highlightFields.get("name");if (highlightField != null) {// 获取高亮值String name = highlightField.getFragments()[0].string();// 覆盖非高亮结果hotelDoc.setName(name);}}System.out.println("hotelDoc = " + hotelDoc);
}

数据聚合

种类
- 桶（Bucket）聚合
  - TermAggregation,文档字段值分组
  - Date Histogram,日期阶梯分组
- 度量（Metric）聚合
  - Avg：求平均值
  - Max：求最大值
  - Min：求最小值
  - Stats：同时求max、min、avg、sum
- 管道（pipeline）聚合
  - 其它聚合的结果为基础做聚合
Bucket

GET /hotel/_search
{"size": 0,  // 设置size为0，结果中不包含文档，只包含聚合结果"aggs": { // 定义聚合"brandAgg": { //给聚合起个名字"terms": { // 聚合的类型，按照品牌值聚合，所以选择term"field": "brand", // 参与聚合的字段"size": 20 // 希望获取的聚合结果数量}}}
}

聚合排序

GET /hotel/_search
{"size": 0, "aggs": {"brandAgg": {"terms": {"field": "brand","order": {"_count": "asc" // 按照_count升序排列},"size": 20}}}
}

限定范围

GET /hotel/_search
{"query": {"range": {"price": {"lte": 200 // 只对200元以下的文档聚合}}}, "size": 0, "aggs": {"brandAgg": {"terms": {"field": "brand","size": 20}}}
}

Metric

GET /hotel/_search
{"size": 0, "aggs": {"brandAgg": { "terms": { "field": "brand", "size": 20,"order": {"scoreAgg.avg": "desc" // scoreAgg avg排序},},"aggs": { // 是brands聚合的子聚合，也就是分组后对每组分别计算"score_stats": { // 聚合名称"stats": { // 聚合类型，这里stats可以计算min、max、avg等"field": "score" // 聚合字段，这里是score}}}}}
}

RestApi

// 入口
public Map<String, List<String>> filters(RequestParams params) {try {// 1.准备RequestSearchRequest request = new SearchRequest("hotel");// 2.准备DSL// 2.1.querybuildBasicQuery(params, request);// 2.2.设置sizerequest.source().size(0);// 2.3.聚合buildAggregation(request);// 3.发出请求SearchResponse response = client.search(request, RequestOptions.DEFAULT);// 4.解析结果Map<String, List<String>> result = new HashMap<>();Aggregations aggregations = response.getAggregations();// 4.1.根据品牌名称，获取品牌结果List<String> brandList = getAggByName(aggregations, "brandAgg");result.put("品牌", brandList);// 4.2.根据品牌名称，获取品牌结果List<String> cityList = getAggByName(aggregations, "cityAgg");result.put("城市", cityList);// 4.3.根据品牌名称，获取品牌结果List<String> starList = getAggByName(aggregations, "starAgg");result.put("星级", starList);return result;} catch (IOException e) {throw new RuntimeException(e);}
}private void buildAggregation(SearchRequest request) {request.source().aggregation(AggregationBuilders.terms("brandAgg").field("brand").size(100));request.source().aggregation(AggregationBuilders.terms("cityAgg").field("city").size(100));request.source().aggregation(AggregationBuilders.terms("starAgg").field("starName").size(100));
}private List<String> getAggByName(Aggregations aggregations, String aggName) {// 4.1.根据聚合名称获取聚合结果Terms brandTerms = aggregations.get(aggName);// 4.2.获取bucketsList<? extends Terms.Bucket> buckets = brandTerms.getBuckets();// 4.3.遍历List<String> brandList = new ArrayList<>();for (Terms.Bucket bucket : buckets) {// 4.4.获取keyString key = bucket.getKeyAsString();brandList.add(key);}return brandList;
}

自动补全

分词器（analyzer）
- character filters
  - 在tokenizer之前对文本进行处理。例如删除字符、替换字符
- tokenizer
  - 将文本按照一定的规则切割成词条（term）。例如keyword，就是不分词；还有ik_smart
- tokenizer filter
  - 将tokenizer输出的词条做进一步处理。例如大小写转换、同义词处理、拼音处理等
拼音分词器
- https://github.com/medcl/elasticsearch-analysis-pinyin
自定义分词器

PUT /test
{"settings": {"analysis": {"analyzer": { // 自定义分词器"my_analyzer": {  // 分词器名称"tokenizer": "ik_max_word","filter": "py"}},"filter": { // 自定义tokenizer filter"py": { // 过滤器名称"type": "pinyin", // 过滤器类型，这里是pinyin"keep_full_pinyin": false,"keep_joined_full_pinyin": true,"keep_original": true,"limit_first_letter_length": 16,"remove_duplicated_term": true,"none_chinese_pinyin_tokenize": false}}}},"mappings": {"properties": {"name": {"type": "text","analyzer": "my_analyzer","search_analyzer": "ik_smart"}}}
}

自动补全
- 参与补全查询的字段必须是completion类型

// 自动补全查询
GET /test/_search
{"suggest": {"title_suggest": {"text": "s", // 关键字"completion": {"field": "title", // 补全查询的字段"skip_duplicates": true, // 跳过重复的"size": 10 // 获取前10条结果}}}
}

// 1.准备Request
SearchRequest request = new SearchRequest("hotel");
// 2.准备DSL
request.source().suggest(new SuggestBuilder().addSuggestion("suggestions",SuggestBuilders.completionSuggestion("suggestion").prefix(prefix).skipDuplicates(true).size(10)
));
// 3.发起请求
SearchResponse response = client.search(request, RequestOptions.DEFAULT);
// 4.解析结果
Suggest suggest = response.getSuggest();
// 4.1.根据补全查询名称，获取补全结果
CompletionSuggestion suggestions = suggest.getSuggestion("suggestions");
// 4.2.获取options
List<CompletionSuggestion.Entry.Option> options = suggestions.getOptions();
// 4.3.遍历
List<String> list = new ArrayList<>(options.size());
for (CompletionSuggestion.Entry.Option option : options) {String text = option.getText().toString();list.add(text);
}
return list;