Java项目【仿牛客网5-6】

Dear 丶 2024-03-16 09:28 27阅读 0赞

## 仿牛客网第五章 ##

> Kafaka消息队列框架、不用框架也可以解决消息队列问题，利用阻塞队列产生消息系统
> 
> 阻塞队列比较简单、理解了阻塞队列，可以更加直观的理解Kafaka底层逻辑

## 一、阻塞队列 ##

> Java自带的API

*  BlockingQueue【接口】
    
     *  解决线程通信的问题。
     *  阻塞方法：put、take。
 *  生产者消费者模式
    
     *  生产者：产生数据的线程。
     *  消费者：使用数据的线程。
 *  实现类
    
     *  ArrayBlockingQueue
     *  LinkedBlockingQueue
     *  PriorityBlockingQueue、SynchronousQueue、DelayQueue等。

[![img][]][img 1]

**面试常问：写一个生产者消费者实现**

public class Test {
 
 public static void main(String[] args) {
 
 BlockingQueue<String> queue = new LinkedBlockingDeque<>(10);
 Producer p = new Producer(queue);
 Consumer c = new Consumer(queue);
 new Thread(p,"producer").start();
 new Thread(c,"consumer").start();
 }
 }
 class Consumer implements Runnable {
 
 private BlockingQueue<String> queue;
 public Consumer(BlockingQueue<String> queue) {
 
 this.queue = queue;
 }
 @Override
 public void run() {
 
 try {
 
 while(true){
 
 Thread.sleep(20);
 System.out.println("消费者消费了：" + queue.take());
 }
 }catch (InterruptedException e) {
 
 e.printStackTrace();
 }
 }
 }
 class Producer implements Runnable{
 
 private BlockingQueue<String> queue;
 public Producer(BlockingQueue<String> queue){
 
 this.queue = queue;
 }
 @Override
 public void run() {
 
 try {
 
 for (int i = 0; i < 5; i++) {
 
 String tmp = "a product " + i + " from:" + Thread.currentThread().getName();
 System.out.println("生产者生产了：" + tmp);
 queue.put(tmp);
 Thread.sleep(20);
 }
 }catch (InterruptedException e) {
 
 e.printStackTrace();
 }
 }
 }

## 二、Kafka入门 ##

> Kafka 性能最好的消息队列服务器，能够处理TB级异步消息函数
> 
> 服务器自动给某些用户发消息，系统消息
> 
> **数据量大、频率高**

*  Kafka简介
    
     *  Kafka是一个分布式的流媒体平台。
     *  应用：消息系统、日志收集、用户行为追踪、流式处理。
 *  Kafka特点
    
     *  高吞吐量、消息持久化、高可靠性、高扩展性。
        
        > **将消息存在硬盘上**、而不是简单的存在内存里，容量大：可持久化存储、可存储海量数据
        > 
        > 对硬盘读取的效率取决于读取硬盘的方式，若**对硬盘进行顺序读取**，而不是随机存取，性能甚至由于内存读取 性能高
        > 
        > **分布式的集群部署**==》高可靠性、高扩展性
        
        目前最为流行、性能最好的消息队列框架
 *  Kafka术语
    
     *  Broker、Zookeeper
     *  Topic、Partition、Offset
     *  Leader Replica 、Follower Replica

> 消息队列实现的方式：①点对点的方式 ②发布订阅模式

**Kafka术语解释**

*  Broker：Kafka的服务器
 *  Zookeeper：管理集群【不是kafaka组件、是一个单独的软件，Kafaka内置Zookeeper】
 *  Topic：点对点模式中每个消费者拿到的消息都不同，发布订阅模式中消费者可能拿到同一份消息。Kafka采用**发布订阅模式**，生产者把消息发布到的空间（位置）就叫Topic【类似于文件夹】
 *  Partition：是对Topic位置的分区，如下图：【一个主题可以分为多个分区】  
    [![img][img 2]][img_img 2]
 *  Offset：就是消息在分区中的索引  
    [![img][img 3]][img_img 3]
 *  Leader Replica：主副本，可以处理请求
 *  Follower Replica：从副本，只是用作备份

Kafka相关链接：[官网][Link 1]

### windows下更改配置 ###

1.config目录下zookeeper.properties修改

[![img][img 4]][img_img 4]

2.server.properties

[![img][img 5]][img_img 5]

### window下使用Kafka ###

1.启动Zookeeper

[![img][img 6]][img_img 6]

2.启动Kafka

[![img][img 7]][img_img 7]

启动完成后就会出现我们设置的文件夹

[![img][img 8]][img_img 8]

3.创建主题

[![img][img 9]][img_img 9]

查看所有主题判断是否创建成功

[![img][img 10]][img_img 10]

4.往主题上发送消息

[![img][img 11]][img_img 11]

发两条消息

[![img][img 12]][img_img 12]

5.消费者接收消息

[![img][img 13]][img_img 13]

## 三、Spring整合Kafka ##

*  引入依赖
    
     *  spring-kafka
 *  配置Kafka
    
     *  配置server、consumer
 *  访问Kafka
    
     *  生产者  
        kafkaTemplate.send(topic, data);
     *  消费者  
        @KafkaListener(topics = \{“test”\})  
        public void handleMessage(ConsumerRecord record) \{\}

[![img][img 14]][img_img 14]

### 导包 ###

<dependency>
 <groupId>org.springframework.kafka</groupId>
 <artifactId>spring-kafka</artifactId>
 <version>2.5.0.RELEASE</version>
 </dependency>

### application.properties中配置 ###

[![img][img 15]][img_img 15]

### 测试一波 ###

@SpringBootTest
    @ContextConfiguration(classes = CommunityApplication.class)
    public class KafkaTest {
        
        @Autowired
        KafkaProducer kafkaProducer;
        @Autowired
        KafkaConsumer kafkaConsumer;
        @Test
        public void testKafka(){
        
            kafkaProducer.sendMessage("test","hello world");
            kafkaProducer.sendMessage("test","I love java");
            try {
        
                Thread.sleep(1000*10);
            } catch (InterruptedException e) {
        
                e.printStackTrace();
            }
        }
    }
    @Component
    class KafkaProducer{
        
        @Autowired
        private KafkaTemplate kafkaTemplate;
        public void sendMessage(String topic,String content){
        
            kafkaTemplate.send(topic,content);
        }
    }
    @Component
    class KafkaConsumer{
        
        @KafkaListener(topics = {
        "test"})
        public void handleMessage(ConsumerRecord record){
        
            System.out.println(record.value());
        }
    }

**生产者主动发消息，消费者被动接收消息**

## 四、发送系统通知 ##

> 频繁操作、保证性能==》Kafaka消息队列
> 
> 可以定义三种不同的主题、一旦事件发生，将消息包装到队列中。消费者继续处理该业务的后续过程、生产者可以继续别的业务
> 
> 生产者和消费者处理业务是并发的，可以同时处理事务【异步】

在Kafaka的基础上，以事件进行封装

*  触发事件
    
     *  评论后，发布通知
     *  点赞后，发布通知
     *  关注后，发布通知
 *  处理事件
    
     *  封装事件对象
     *  开发事件的生产者
     *  开发事件的消费者

[![img][img 16]][img_img 16]

### 封装事件对象 ###

public class Event {
 
 //张三给李四点赞---userId是张三，entityUserId是李四
 private String topic;
 private int userId;
 private int entityType;
 private int entityId;
 private int entityUserId;
 //额外的数据放在Map中，具备一定的扩展性
 private Map<String,Object> data = new HashMap<>();
 
 public String getTopic() {
 
 return topic;
 }
 public Event setTopic(String topic) {
 
 //改造，set主题之后，返回当前对象，方便set其它数据
 //因为参数很多，最好不用参数构造器
 this.topic = topic;
 return this;
 }
 public int getUserId() {
 
 return userId;
 }
 public Event setUserId(int userId) {
 
 this.userId = userId;
 return this;
 }
 public int getEntityType() {
 
 return entityType;
 }
 public Event setEntityType(int entityType) {
 
 this.entityType = entityType;
 return this;
 }
 public int getEntityId() {
 
 return entityId;
 }
 public Event setEntityId(int entityId) {
 
 this.entityId = entityId;
 return this;
 }
 public int getEntityUserId() {
 
 return entityUserId;
 }
 public Event setEntityUserId(int entityUserId) {
 
 this.entityUserId = entityUserId;
 return this;
 }
 public Map<String, Object> getData() {
 
 return data;
 }
 public Event setData(String key,String object) {
 
 this.data.put(key,object);
 return this;
 }
 }

*  注意set方法的修改是为了可以类似sb.append(" ").append(“1”);的操作
 *  注意setData方法的修改

### 开发事件的生产者 ###

新建event包

@Component
    public class EventProducer {
        
        @Autowired
        private KafkaTemplate kafkaTemplate;
        //处理事件,本质就是发送消息
        public  void fireEvent(Event event){
        
            //将事件发送到指定的主题
            kafkaTemplate.send(event.getTopic(), JSONObject.toJSONString(event));
        }
    }

### 开发事件的消费者 ###

@Component
 public class EventConsumer implements CommunityContant {
 
 //记日志
 private static final Logger logger = LoggerFactory.getLogger(EventConsumer.class);
 //消息最终是要往message表中插入数据的
 @Autowired
 private MessageService messageService;
 @KafkaListener(topics = {
 TOPIC_LIKE,TOPIC_COMMENT,TOPIC_FOLLOW})
 public void handleCommentMessage(ConsumerRecord record){
 
 if(record==null||record.value()==null){
 
 logger.error("消息的内容为空");
 return;
 }
 //将JSON字符串 解析为对象
 Event event = JSONObject.parseObject(record.value().toString(),Event.class);
 if(event==null){
 
 logger.error("消息格式错误");
 return;
 }
 //发送站内通知，主要是构造message对象
 Message message = new Message();
 //User表中id为1代表系统用户
 message.setFromId(SYSTEM_ID);
 message.setToId(event.getEntityUserId());
 message.setConversationId(event.getTopic());//存的是主题
 message.setCreateTime(new Date());
 //为啥不直接把Event转成json存在content里边？
 Map<String,Object> content = new HashMap<>();
 content.put("userId",event.getUserId());
 content.put("entityType",event.getEntityType());
 content.put("entityId",event.getEntityId());
 if(!event.getData().isEmpty()){
 
 for(Map.Entry<String,Object> entry:event.getData().entrySet()){
 
 content.put(entry.getKey(),entry.getValue());
 }
 }
 message.setContent(JSONObject.toJSONString(content));
 messageService.addMessage(message);
 }
 }

### 处理评论事件–CommentController ###

增加如下代码 重构了set方法，返回当前对象this

[![img][img 17]][img_img 17]

### 处理点赞事件–LikeController ###

增加如下代码

[![img][img 18]][img_img 18]

**因为重构了方法我们处理下js传参**

discuss-detail页面

[![img][img 19]][img_img 19][![img][img 20]][img_img 20]

### 处理关注事件–FollowController ###

follow方法

[![img][img 21]][img_img 21]

### 一些小bug ###

1.Kafka报错： Topic(s) \[xxx\] is/are not present and missingTopicsFatal is true

*  报错原因： 消费监听接口监听的主题不存在时，默认会报错
 *  解决方法： 配置文件中将listener的属性missingTopicsFatal设置为false

spring.kafka.listener.missing-topics-fatal=false

2.以前写的AOP记录日志报错

[![img][img 22]][img_img 22][![img][img 23]][img_img 23]

因为消费者里也调了service方法所以上图红框有可能取不到request

解决方法

[![img][img 24]][img_img 24]

### 测试一波 ###

发现message表中已经有数据了

[![img][img 25]][img_img 25]

## 五、显示系统通知 ##

*  通知列表
    
     *  显示评论、点赞、关注三种类型的通知
 *  通知详情
    
     *  分页显示某一类主题所包含的通知
 *  未读消息
    
     *  在页面头部显示所有的未读消息数量

[![img][img 26]][img_img 26]

### 列表页写MessageMapper ###

因为消息存到了message表里

[![img][img 27]][img_img 27]

[![img][img 28]][img_img 28][![img][img 29]][img_img 29]

### 列表页service层 ###

MessageService类中

[![img][img 30]][img_img 30]

### 列表页MessageController ###

@RequestMapping(path="/notice/list",method = RequestMethod.GET)
 public String getNoticeList(Model model){
 
 User user = hostHolder.getUser();
 //查询评论类通知
 Message message = messageService.findLatestNotice(user.getId(),TOPIC_COMMENT);
 Map<String,Object> messageVo = new HashMap<>();
 if(message!=null){
 
 messageVo.put("message",message);
 String content = message.getContent();
 //字符串 还原成对象 //{"entityType":1,"entityId":275,"postId":275,"userId":111}
 content = HtmlUtils.htmlUnescape(content); //这步可以 反转 上方转义字符
 HashMap<String,Object> data = JSONObject.parseObject(content, HashMap.class);
 //data转存到MessageVo中，因为MessageVo存到model，被模板引用
 //谁发给我？ 希望要的是user对象，而不是userId【还需要进行一步查询】
 messageVo.put("user",userService.findUserById((Integer)data.get("userId")));
 messageVo.put("entityType",data.get("entityType"));
 messageVo.put("entityId",data.get("entityId"));
 messageVo.put("postId",data.get("postId"));
 int count = messageService.findNoticeCount(user.getId(),TOPIC_COMMENT);
 messageVo.put("count",count);
 int unread = messageService.findNoticeUnreadCount(user.getId(),TOPIC_COMMENT);
 messageVo.put("unread",unread);
 }
 model.addAttribute("commentNotice",messageVo);
 //查询点赞类通知
 message = messageService.findLatestNotice(user.getId(),TOPIC_LIKE);
 messageVo = new HashMap<>();
 if(message!=null){
 
 messageVo.put("message",message);
 String content = message.getContent();
 //{"entityType":1,"entityId":275,"postId":275,"userId":111}
 content = HtmlUtils.htmlUnescape(content); //这步可以去除上方转义字符
 HashMap<String,Object> data = JSONObject.parseObject(content, HashMap.class);
 //谁发给我？
 messageVo.put("user",userService.findUserById((Integer)data.get("userId")));
 messageVo.put("entityType",data.get("entityType"));
 messageVo.put("entityId",data.get("entityId"));
 messageVo.put("postId",data.get("postId"));
 int count = messageService.findNoticeCount(user.getId(),TOPIC_LIKE);
 messageVo.put("count",count);
 int unread = messageService.findNoticeUnreadCount(user.getId(),TOPIC_LIKE);
 messageVo.put("unread",unread);
 }
 model.addAttribute("likeNotice",messageVo);
 //查询关注类通知
 message = messageService.findLatestNotice(user.getId(),TOPIC_FOLLOW);
 messageVo = new HashMap<>();
 if(message!=null){
 
 messageVo.put("message",message);
 String content = message.getContent();
 //{"entityType":1,"entityId":275,"postId":275,"userId":111}
 content = HtmlUtils.htmlUnescape(content); //这步可以去除上方转义字符
 HashMap<String,Object> data = JSONObject.parseObject(content, HashMap.class);
 //谁关注了我？
 messageVo.put("user",userService.findUserById((Integer)data.get("userId")));
 messageVo.put("entityType",data.get("entityType"));
 messageVo.put("entityId",data.get("entityId"));
 int count = messageService.findNoticeCount(user.getId(),TOPIC_FOLLOW);
 messageVo.put("count",count);
 int unread = messageService.findNoticeUnreadCount(user.getId(),TOPIC_FOLLOW);
 messageVo.put("unread",unread);
 }
 model.addAttribute("followNotice",messageVo);
 //查询未读消息数量
 int letterUnreadCount = messageService.findLetterUnreadCount(user.getId(),null);
 int noticeUnreadCount = messageService.findNoticeUnreadCount(user.getId(),null);
 model.addAttribute("letterUnreadCount",letterUnreadCount);
 model.addAttribute("noticeUnreadCount",noticeUnreadCount);
 return "/site/notice";
 }
 }

还有一点修改时在letter页面上也得显示系统通知的数量所以在/message/list路径下增加如下代码，然后处理下letter.html的页面

[![img][img 31]][img_img 31]

### 列表页notice的页面 ###

先修改成Thymeleaf，其他填数据

[![img][img 32]][img_img 32]评论的模板填充，点赞和关注同理

[![img][img 33]][img_img 33]

测试一波

[![img][img 34]][img_img 34]

[![img][img 35]][img_img 35]

### 详情页MessageMapper ###

[![img][img 36]][img_img 36]

### 详情页MessageService ###

[![img][img 37]][img_img 37]

### 详情页MessageController ###

@RequestMapping(path = "/notice/detail/{topic}",method = RequestMethod.GET)
 public String getNoticeDetail(@PathVariable("topic") String topic,Page page,Model model){
 
 User user = hostHolder.getUser();
 //处理分页
 page.setLimit(5);
 page.setRows(messageService.findNoticeCount(user.getId(),topic));
 page.setPath("/notice/detail/"+topic);
 List<Message> noticeList = messageService.findNotices(user.getId(),topic,page.getOffset(),page.getLimit());
 List<Map<String,Object>> noticeVoList = new ArrayList<>();
 if(noticeList!=null){
 
 for(Message notice:noticeList){
 
 Map<String,Object> map = new HashMap<>();
 //通知
 map.put("notice",notice);
 //内容 JSON字符串==》对象
 String content = notice.getContent();
 content = HtmlUtils.htmlUnescape(content);
 HashMap<String,Object> data = JSONObject.parseObject(content, HashMap.class);
 map.put("user",userService.findUserById((Integer)data.get("userId")));
 map.put("entityType",data.get("entityType"));
 map.put("entityId",data.get("entityId"));
 map.put("postId",data.get("postId"));
 map.put("fromUser",userService.findUserById(notice.getFromId())); //系统名
 noticeVoList.add(map);
 }
 }
 model.addAttribute("notices",noticeVoList);
 //设置已读
 List<Integer> ids = getLetterIds(noticeList);
 if(!ids.isEmpty()){
 
 messageService.readMessage(ids);
 }
 return "/site/notice-detail";
 }

### 详情页notice-detail页面 ###

[![img][img 38]][img_img 38][![img][img 39]][img_img 39]

### 头部总消息数通知 ###

[![img][img 40]][img_img 40]

每个请求处理完都要查看所以用**拦截器处理**

**写一个拦截器**

@Component
    public class MessageInterator implements HandlerInterceptor {
        
        @Autowired
        private HostHolder hostHolder;
        @Autowired
        private MessageService messageService;
        @Override
        public void postHandle(HttpServletRequest request, HttpServletResponse response, Object handler, ModelAndView modelAndView) throws Exception {
        
            User user = hostHolder.getUser();
            //user是否登录，是否模板可以携带
            if(user!=null&&modelAndView!=null){
        
                int letterUnreadCount = messageService.findLetterUnreadCount(user.getId(), null);
                int noticeUnreadCount = messageService.findNoticeUnreadCount(user.getId(), null);
                int unreadCount = letterUnreadCount+noticeUnreadCount;
                modelAndView.addObject("unreadCount",unreadCount);
            }
        }
    }

**加入config中**

[![img][img 41]][img_img 41]

**index页面头部处理一下**

[![img][img 42]][img_img 42]

## 仿牛客网第六章 ##

## 一、Elasticsearch入门 ##

> 性能最好、最流行的搜索引擎【github、百度】
> 
> Reatful是一种风格、规定前后端按照啥格式进行交互、不同类型HTTP请求格式【请求标准的描述】
> 
> 使用Es搜索数据，前提：数据在Es中保存【可以当做特殊的数据库】

*  Elasticsearch简介
    
     *  一个分布式的、Restful风格的搜索引擎。
     *  支持对各种类型的数据的检索。
     *  搜索速度快，可以提供实时的搜索服务。
     *  便于水平扩展，每秒可以处理PB级海量数据。
 *  Elasticsearch术语
    
     *  索引、类型、文档、字段。【和数据形态有关】
     *  集群、节点、分片、副本。

术语的解释

*  索引：相当于数据库中的database 改版后作为table
 *  类型：相当于数据库中的table 不再使用
 *  文档：相当于数据库中的一行数据，数据结构为JSON
 *  字段：相当于数据库中的一列

Elasticsearch6.0以后开始逐步废除类型的概念，索引的含义中也包括了类型。

*  集群：分布式部署，提高性能
 *  节点：集群中的每一台服务器
 *  分片：对一个索引的进一步划分存储，提高并发处理能力
 *  副本：对分片的备份，提高可用性  
    [![image][]][image 1]  
    Elasticsearch相关链接：[官网][Link 2]

Elasticsearch选择下载6.4.3版本和**SpringBoot兼容**

### Elasticsearch配置 ###

文件位置config/elasticsearch.yml

集群的名字 数据存放的位置 日志存放的位置

[![image][image 2]][image_image 2]配置环境变量【for方便访问命令】

[![image][image 3]][image_image 3]

### 安装中文分词插件 ###

es默认支持英文分词，中文分词需要单独的插件

github上找

[![image][image 4]][image_image 4]

[![image][image 5]][image_image 5]

解压到指定目录下

[![image][image 6]][image_image 6]

**ik插件配置文件说明**

分词插件已经进行了一些中文分词的配置

IKAnalyzer.cfg 可以自己配置新词

[![image][image 7]][image_image 7][![image][image 8]][image_image 8]

### 安装Postman模拟网页访问 ###

Postman相关链接：[官网][Link 3]

> 可以模拟Web客服端，即模拟HTTP请求
> 
> 直接通过命令行查询、存一些数据到es中太复杂了

### 使用命令行操作Elasticsearch ###

1.启动ES—./bin/elasticsearch.bat

2.常用命令介绍

*  查看节点健康状态

curl -X GET "localhost:9200/_cat/health?v"

这个命令需要下载curl相关包：[参考链接][Link 4]

[![image][image 9]][image_image 9]

*  查看节点具体信息

curl -X GET "localhost:9200/_cat/nodes?v"

[![image][image 10]][image_image 10]

*  查看索引相关信息

curl -X GET "localhost:9200/_cat/indices?v"

新装的没有索引：

[![image][image 11]][image_image 11]

*  创建索引

curl -X PUT "localhost:9200/test"  //test就是索引名字

[![image][image 12]][image_image 12]

查看状态显示yellow是因为没有分片（备份）。

[![image][image 13]][image_image 13]

*  删除索引

curl -X DELETE "localhost:9200/test"  //test就是索引名字

[![image][image 14]][image_image 14]

### 使用Postman/RESTer访问ES ###

RESTer是火狐插件也很好用。

*  查索引  
    [![image][image 15]][image_image 15]
 *  建索引  
    [![image][image 16]][image_image 16]
 *  删除索引  
    [![image][image 17]][image_image 17]
 *  提交数据

//test:索引  _doc:固定格式  1：id号 然后在请求body中写数据
    
    PUT localhost：9200/test/_doc/1

[![image][image 18]][image_image 18]

*  查数据

GET localhost:9200/test/_doc/1

[![image][image 19]][image_image 19]

*  改数据

和添加数据一样，底层会先删除再添加

*  删除数据

DELETE localhost:9200/test/_doc/1

[![image][image 20]][image_image 20]

*  **搜索功能的演示**
    
    搜索：**分词、全文匹配**【title、content】
    
    ①先插入一些数据  
    [![image][image 21]][image_image 21][![image][image 22]][image_image 22]  
    [![image][image 23]][image_image 23]
    
    ②开始搜索演示  
    [![image][image 24]][image_image 24]

③搜索时会先分词然后搜索，并不一定完全匹配【既在title中搜、又在content中搜】

query：关键字 fields：在哪些字段进行搜索

[![image][image 25]][image_image 25]

## 二、Spring整合Elasticsearch ##

*  引入依赖
    
     *  spring-boot-starter-data-elasticsearch
 *  配置Elasticsearch
    
     *  cluster-name、cluster-nodes
 *  Spring Data Elasticsearch
    
     *  ElasticsearchTemplate【类】
     *  ElasticsearchRepository【接口，我们需要定义子接口实现】  
        [![image][image 26]][image_image 26]

### 导包 ###

<dependency>
 
 <groupId>org.springframework.data</groupId>
 
 <artifactId>spring-data-elasticsearch</artifactId>
 
 </dependency>

### 配置 ###

1.application.properties

spring:
    
      data:
    
        elasticsearch:
    
          cluster-name: nowcoder
    
          cluster-nodes: 127.0.0.1:9300

2.解决Netty冲突问题

问题原因：Redis底层使用了Netty，Elasticsearch也用了Netty，当被注册两次就会报错

[![image][image 27]][image_image 27]

解决思路：Elasticsearch中注册Netty前会判断有无一个参数，如果有就不注册

[![image][image 28]][image_image 28]这么解决：

> @postConstruct管理Bean的生命周期
> 
> @postConstruct修饰的方法，在构造器调用之后执行

[![image][image 29]][image_image 29]

> 使用ElasticsearchRepository接口来实现帖子的管理，相比于第一种方法来说，更简单【没法解决，使用类的方法
> 
> 使用ElasticsearchRepository接口，其所有代码实现类都是Spring自动生成的，生成之前做一个配置
> 
> 例如：索引和表的对应关系 字段和索引字段的关系

3.给discussPost加注解

//indexName:索引名，type：固定_doc,shards：分片，replicas:备份
    
    @Document(indexName = "discusspost",type = "_doc",shards =6 ,replicas = 2)
    
    public class DiscussPost {
        
    
        @Id//id
    
        private int id;
    
        @Field(type = FieldType.Integer)//普通的类型
    
        private int userId;
    
        //analyzer:存储时的解析器  互联网校招--->建立最大的索引（就是各种拆分）
    
        //searchAnalyzer：搜索时的解析器 拆分尽可能少的满足意图的分词器
    
        @Field(type = FieldType.Text,analyzer = "ik_max_word",searchAnalyzer = "ik_smart")
    
        private String title;
    
        @Field(type = FieldType.Text,analyzer = "ik_max_word",searchAnalyzer = "ik_smart")
    
        private String content;
    
        @Field(type = FieldType.Integer)
    
        //0-普通; 1-置顶;
    
        private int type;
    
        @Field(type = FieldType.Integer)
    
        //0-正常; 1-精华; 2-拉黑;
    
        private int status;
    
        @Field(type = FieldType.Date)
    
        private Date createTime;
    
        @Field(type = FieldType.Integer)
    
        private int commentCount;
    
        @Field(type = FieldType.Double)
    
        private double score;

### 写数据层 ###

在dao下建立子包elasticsearch，并创建DiscussPostRepository接口

[![image][image 30]][image_image 30]

### 测试一波 ###

Elasticsearch中配置再加一个这个：

[![image][image 31]][image_image 31]

elasticsearch包不要放在dao包下边，会导致bean注入失败。

> 数据来源MySQL==》es中

@SpringBootTest
 
 @ContextConfiguration(classes = CommunityApplication.class)
 
 public class ElasticsearchTest {
 
 
 @Autowired
 
 private DiscussPostMapper discussMapper;
 
 @Autowired
 
 private DiscussPostRepository discussRepository;
 
 //有些功能上边的解决不了，所以引入下边的【第一种方法 类】
 
 @Autowired
 
 private ElasticsearchTemplate elasticTemplate;
 
 @Test //插入一条数据【不用特地写索引，底层自动创建】
 
 public void testInsert() {
 
 
 discussRepository.save(discussMapper.selectDiscussPostById(271));
 
 discussRepository.save(discussMapper.selectDiscussPostById(272));
 
 discussRepository.save(discussMapper.selectDiscussPostById(273));
 
 }
 
 @Test//插入多条数据
 
 public void testInsertList() {
 
 
 discussRepository.saveAll(discussMapper.selectDiscussPosts(101, 0, 100));
 
 discussRepository.saveAll(discussMapper.selectDiscussPosts(102, 0, 100));
 
 discussRepository.saveAll(discussMapper.selectDiscussPosts(103, 0, 100));
 
 discussRepository.saveAll(discussMapper.selectDiscussPosts(111, 0, 100));
 
 discussRepository.saveAll(discussMapper.selectDiscussPosts(112, 0, 100));
 
 discussRepository.saveAll(discussMapper.selectDiscussPosts(131, 0, 100));
 
 discussRepository.saveAll(discussMapper.selectDiscussPosts(132, 0, 100));
 
 discussRepository.saveAll(discussMapper.selectDiscussPosts(133, 0, 100));
 
 discussRepository.saveAll(discussMapper.selectDiscussPosts(134, 0, 100));
 
 }
 
 //localhost:9200/discusspost/_doc/231
 
 @Test//修改数据
 
 public void testUpdate() {
 
 
 DiscussPost post = discussMapper.selectDiscussPostById(231);
 
 post.setContent("我是新人,使劲灌水.");
 
 discussRepository.save(post);
 
 }
 
 @Test//删除数据
 
 public void testDelete() {
 
 
 discussRepository.deleteById(231);
 
 //discussRepository.deleteAll();
 
 }
 
 @Test//利用接口搜索，第二种方法
 //利用SearchQuery组件构造搜索条件 以及搜索后的结果 排序、分页、高亮显示【在搜索词前后加标签】
 
 public void testSearchByRepository() {
 
 
 SearchQuery searchQuery = new NativeSearchQueryBuilder()
 
 .withQuery(QueryBuilders.multiMatchQuery("互联网寒冬", "title", "content"))
 
 .withSort(SortBuilders.fieldSort("type").order(SortOrder.DESC)) //按字段排序
 
 .withSort(SortBuilders.fieldSort("score").order(SortOrder.DESC))
 
 .withSort(SortBuilders.fieldSort("createTime").order(SortOrder.DESC))
 
 .withPageable(PageRequest.of(0, 10)) //分页
 
 .withHighlightFields(
 
 new HighlightBuilder.Field("title").preTags("").postTags(""),
 
 new HighlightBuilder.Field("content").preTags("").postTags("")
 
 ).build();
 
 // 底层调用：elasticTemplate.queryForPage(searchQuery, class, SearchResultMapper)
 
 // 底层获取得到了高亮显示的值【另一份数据】, 但是没有返回.所以为了得到高亮显示直接用elasticTemplate.queryForPage见下面
 
 Page<DiscussPost> page = discussRepository.search(searchQuery);
 
 System.out.println(page.getTotalElements());
 
 System.out.println(page.getTotalPages());
 
 System.out.println(page.getNumber());
 
 System.out.println(page.getSize());
 
 for (DiscussPost post : page) {
 
 
 System.out.println(post);
 
 }
 
 }
 
 @Test//利用类搜索，第一种方法【高亮显示可以成功】
 
 public void testSearchByTemplate() {
 
 
 SearchQuery searchQuery = new NativeSearchQueryBuilder()
 
 .withQuery(QueryBuilders.multiMatchQuery("互联网寒冬", "title", "content"))
 
 .withSort(SortBuilders.fieldSort("type").order(SortOrder.DESC))
 
 .withSort(SortBuilders.fieldSort("score").order(SortOrder.DESC))
 
 .withSort(SortBuilders.fieldSort("createTime").order(SortOrder.DESC))
 
 .withPageable(PageRequest.of(0, 10))
 
 .withHighlightFields(
 
 new HighlightBuilder.Field("title").preTags("").postTags(""),
 
 new HighlightBuilder.Field("content").preTags("").postTags("")
 
 ).build();
 
 Page<DiscussPost> page = elasticTemplate.queryForPage(searchQuery, DiscussPost.class, new SearchResultMapper() {
 
 
 @Override //处理SearchResultMapper接口，实现两部分数据的合并【高亮】
 
 public <T> AggregatedPage<T> mapResults(SearchResponse response, Class<T> aClass, Pageable pageable) {
 
 
 SearchHits hits = response.getHits();//多条命中的数据
 
 if (hits.getTotalHits() <= 0) {
 
 
 return null;
 
 }
 
 List<DiscussPost> list = new ArrayList<>();
 
 for (SearchHit hit : hits) {
 
 //每得到一条命中的数据、包装到实体类中，返回
 
 DiscussPost post = new DiscussPost();
 
 String id = hit.getSourceAsMap().get("id").toString();
 
 post.setId(Integer.valueOf(id));
 
 String userId = hit.getSourceAsMap().get("userId").toString();
 
 post.setUserId(Integer.valueOf(userId));
 //原始的title
 
 String title = hit.getSourceAsMap().get("title").toString();
 
 post.setTitle(title);
 //原始的content
 
 String content = hit.getSourceAsMap().get("content").toString();
 
 post.setContent(content);
 
 String status = hit.getSourceAsMap().get("status").toString();
 
 post.setStatus(Integer.valueOf(status));
 
 String createTime = hit.getSourceAsMap().get("createTime").toString(); //long类型的字符串
 
 post.setCreateTime(new Date(Long.valueOf(createTime)));
 
 String commentCount = hit.getSourceAsMap().get("commentCount").toString();
 
 post.setCommentCount(Integer.valueOf(commentCount));
 
 // 处理高亮显示的结果
 //获取与title有关的高亮显示的内容
 
 HighlightField titleField = hit.getHighlightFields().get("title");
 
 if (titleField != null) {
 
 //覆盖原始的title
 
 post.setTitle(titleField.getFragments()[0].toString());
 
 }
 
 HighlightField contentField = hit.getHighlightFields().get("content");
 
 if (contentField != null) {
 
 
 post.setContent(contentField.getFragments()[0].toString());
 
 }
 
 list.add(post);
 
 }
 				//返回的是构造类，底层需要【不是简单的list】
 //显示的不是整个文章，返回匹配的局部内容【类似百度】
 return new AggregatedPageImpl(list, pageable,
 
 hits.getTotalHits(), response.getAggregations(), response.getScrollId(), hits.getMaxScore());
 
 }
 
 @Override
 
 public <T> T mapSearchHit(SearchHit searchHit, Class<T> aClass) {
 
 
 return null;
 
 }
 
 });
 
 System.out.println(page.getTotalElements());
 
 System.out.println(page.getTotalPages());
 
 System.out.println(page.getNumber());
 
 System.out.println(page.getSize());
 
 for (DiscussPost post : page) {
 
 
 System.out.println(post);
 
 }
 
 }
 
 }

## 三、开发社区搜索功能 ##

*  搜索服务【业务层】
    
     *  将帖子保存至Elasticsearch服务器。
     *  从Elasticsearch服务器删除帖子。
     *  从Elasticsearch服务器搜索帖子。
 *  发布事件【表现层、以事件方式】
    
     *  发布帖子时，将帖子异步的提交到Elasticsearch服务器。
     *  增加评论时，将帖子异步的提交到Elasticsearch服务器。
     *  在消费组件中增加一个方法，消费帖子发布事件。
 *  显示结果
    
     *  在控制器中处理搜索请求，在HTML上显示搜索结果。

**一个小问题的解决**

> 不加keyProperty，MyBatics不知道哪个是主键，增加后不会把生成的组件存到实体类中
> 
> 后面实体类想要使用组件，no

[![image][image 32]][image_image 32]

### ElasticsearchService ###

@Service
 
 public class ElasticsearchService {
 
 
 @Autowired
 
 private DiscussPostRepository discussPostRepository;
 
 @Autowired
 
 private ElasticsearchTemplate elasticTemplate;//高亮显示
 
 //添加、修改
 
 public void saveDiscussPost(DiscussPost discussPost){
 
 
 discussPostRepository.save(discussPost);
 
 }
 
 //删除
 
 public void deleteDiscussPost(int id){
 
 
 discussPostRepository.deleteById(id);
 
 }
 
 //查询
 
 public Page<DiscussPost> searchDiscussPost(String keyword,int current,int limit){
 
 
 SearchQuery searchQuery = new NativeSearchQueryBuilder()
 
 .withQuery(QueryBuilders.multiMatchQuery(keyword, "title", "content"))
 
 .withSort(SortBuilders.fieldSort("type").order(SortOrder.DESC))
 
 .withSort(SortBuilders.fieldSort("score").order(SortOrder.DESC))
 
 .withSort(SortBuilders.fieldSort("createTime").order(SortOrder.DESC))
 
 .withPageable(PageRequest.of(current, limit))
 
 .withHighlightFields(
 
 new HighlightBuilder.Field("title").preTags("").postTags(""),
 
 new HighlightBuilder.Field("content").preTags("").postTags("")
 
 ).build();
 
 return elasticTemplate.queryForPage(searchQuery, DiscussPost.class, new SearchResultMapper() {
 
 
 @Override
 
 public <T> AggregatedPage<T> mapResults(SearchResponse response, Class<T> aClass, Pageable pageable) {
 
 
 SearchHits hits = response.getHits();
 
 if (hits.getTotalHits() <= 0) {
 
 
 return null;
 
 }
 
 List<DiscussPost> list = new ArrayList<>();
 
 for (SearchHit hit : hits) {
 
 
 DiscussPost post = new DiscussPost();
 
 String id = hit.getSourceAsMap().get("id").toString();
 
 post.setId(Integer.valueOf(id));
 
 String userId = hit.getSourceAsMap().get("userId").toString();
 
 post.setUserId(Integer.valueOf(userId));
 
 String title = hit.getSourceAsMap().get("title").toString();
 
 post.setTitle(title);
 
 String content = hit.getSourceAsMap().get("content").toString();
 
 post.setContent(content);
 
 String status = hit.getSourceAsMap().get("status").toString();
 
 post.setStatus(Integer.valueOf(status));
 
 String createTime = hit.getSourceAsMap().get("createTime").toString(); //long类型的字符串
 
 post.setCreateTime(new Date(Long.valueOf(createTime)));
 
 String commentCount = hit.getSourceAsMap().get("commentCount").toString();
 
 post.setCommentCount(Integer.valueOf(commentCount));
 
 // 处理高亮显示的结果
 
 HighlightField titleField = hit.getHighlightFields().get("title");
 
 if (titleField != null) {
 
 
 post.setTitle(titleField.getFragments()[0].toString());
 
 }
 
 HighlightField contentField = hit.getHighlightFields().get("content");
 
 if (contentField != null) {
 
 
 post.setContent(contentField.getFragments()[0].toString());
 
 }
 
 list.add(post);
 
 }
 
 return new AggregatedPageImpl(list, pageable,
 
 hits.getTotalHits(), response.getAggregations(), response.getScrollId(), hits.getMaxScore());
 
 }
 
 @Override
 
 public <T> T mapSearchHit(SearchHit searchHit, Class<T> aClass) {
 
 
 return null;
 
 }
 
 }); 
 
 }
 
 }

### 处理DiscussPostController.addDiscussPost ###

[![image][image 33]][image_image 33]

### 处理CommentController.addComment ###

[![image][image 34]][image_image 34]

### EventConsumer写一个消费发帖事件的方法 ###

@KafkaListener(topics = {
        TOPIC_PUBLISH})
    
        public void handlePublishMessage(ConsumerRecord record){
        
    
            if(record==null||record.value()==null){
        
    
                logger.error("消息的内容为空");
    
                return;
    
            }
    
            Event event = JSONObject.parseObject(record.value().toString(),Event.class);
    
            if(event==null){
        
    
                logger.error("消息格式错误");
    
                return;
    
            }
    
            //查询出这个帖子
    
            DiscussPost post = discussPostService.findDiscussPostById(event.getEntityId());
    
            //往es中存数据
    
            elasticsearchService.saveDiscussPost(post);
    
        }

### 新写一个SearchController ###

@Controller
 
 public class SearchController implements CommunityContant {
 
 
 @Autowired
 
 private ElasticsearchService elasticsearchService;
 
 @Autowired
 
 private UserService userService;
 
 @Autowired
 
 private LikeService likeService;
 
 @RequestMapping(path="/search",method = RequestMethod.GET)
 
 //路径 search?keyword=xxx
 
 public String search(String keyword, Page page, Model model){
 
 
 //搜索帖子
 
 org.springframework.data.domain.Page<DiscussPost> 
 
 searchResult = elasticsearchService.searchDiscussPost(keyword, page.getCurrent() - 1, page.getLimit());
 
 //聚合数据
 
 List<Map<String,Object>> discussPosts = new ArrayList<>();
 
 if(searchResult!=null){
 
 
 for(DiscussPost post:searchResult){
 
 
 Map<String,Object> map = new HashMap<>();
 
 //帖子
 
 map.put("post",post);
 
 //作者
 
 map.put("user",userService.findUserById(post.getUserId()));
 
 //点赞数量
 
 map.put("likeCount",likeService.findEntityLikeCount(ENTITY_TYPE_POST,post.getId()));
 
 discussPosts.add(map);
 
 }
 
 }
 
 model.addAttribute("discussPosts",discussPosts);
 
 model.addAttribute("keyword",keyword);
 
 
 
 //分页信息
 
 page.setPath("/search?keyword="+keyword);
 
 page.setRows(searchResult==null?0:(int)searchResult.getTotalElements());
 
 return "/site/search";
 
 }
 
 }

### 处理页面index处理搜索框 ###

[![image][image 35]][image_image 35]

### 处理页面search ###

[![image][image 36]][image_image 36]

### 突然发现之前的一个bug ###

MessageController.getNoticeList

先把message加入messageVo,不然模板判断显示不显示的时候会报null

[![image][image 37]][image_image 37]

[img]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/16/07fbfae3d06243b69a801ecf7de0ca7c.png
[img 1]: https://xiaochen-pictures.oss-cn-guangzhou.aliyuncs.com/computer-pictures/1650460684294.png
[img 2]: https://img-blog.csdnimg.cn/img_convert/5235fecb6c8c1a98bba2ad3f6d467363.png
[img_img 2]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/16/0eb98942782148938e9d31408e620025.png
[img 3]: https://img-blog.csdnimg.cn/img_convert/dd0794f0ce5c39f8d36dd183b2c3c256.png
[img_img 3]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/16/85023ae0113b430597984c90b0b73d8c.png
[Link 1]: http://kafka.apache.org/
[img 4]: https://img-blog.csdnimg.cn/img_convert/3b9b2f5cbe793810be128eb7864b1f2e.png
[img_img 4]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/16/440cadf82cff4432b50d482c8d402558.png
[img 5]: https://img-blog.csdnimg.cn/img_convert/7fc9815fbc109a6c8bb1059c1416523e.png
[img_img 5]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/16/fe3f4a656d084cd8a9ae0de8f3e796cd.png
[img 6]: https://img-blog.csdnimg.cn/img_convert/02f829364357ef40654eaea29708adae.png
[img_img 6]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/16/ae0bbea6518249e0a801fcf34f0671f5.png
[img 7]: https://img-blog.csdnimg.cn/img_convert/73913d7288d104ebefdf61823e503a6d.png
[img_img 7]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/16/7860ad9ce1764c71b9d646caa9b446fd.png
[img 8]: https://img-blog.csdnimg.cn/img_convert/be525a2febb7306816e960ba42ac90e5.png
[img_img 8]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/16/698d08b04b1d4d2a88d6d5c68c52d0c4.png
[img 9]: https://img-blog.csdnimg.cn/img_convert/f0dfb9b04595e17b44c5d35d451d4def.png
[img_img 9]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/16/83101671a7a34779b977e33574a84217.png
[img 10]: https://img-blog.csdnimg.cn/img_convert/adb22adaa0d5a65c9b5726fd22ba4e83.png
[img_img 10]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/16/29ff7920e5ac4668bcc9f18b91686bdb.png
[img 11]: https://img-blog.csdnimg.cn/img_convert/6cbf36240ecbda22c04bd9bf70d37d0a.png
[img_img 11]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/16/55df8efabe29460e9a1fe02ad43c2e27.png
[img 12]: https://img-blog.csdnimg.cn/img_convert/08d86df98bcd48e6d7962c2a9f1e4ddd.png
[img_img 12]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/16/b469e5c9bab74d88b9101e7a33308824.png
[img 13]: https://img-blog.csdnimg.cn/img_convert/abaf533a9ee4bae8f97f96e28fd19e7d.png
[img_img 13]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/16/8334b74423404166ab50840600ce8e5c.png
[img 14]: https://img-blog.csdnimg.cn/img_convert/b4743a321bc33fb19a3cf103986861fc.png
[img_img 14]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/16/628a7ee20c8446c4aab4503ed3a2d061.png
[img 15]: https://img-blog.csdnimg.cn/img_convert/13cfa216c8e778c813f7ed2a84355692.png
[img_img 15]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/16/db84146ac5f2416f904b3a6e168eaee7.png
[img 16]: https://img-blog.csdnimg.cn/img_convert/87d74d9ef9e1598908d0c8c6cc3f6d43.png
[img_img 16]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/16/d2c8cb22d8c0461aaaa2e532a52072c1.png
[img 17]: https://img-blog.csdnimg.cn/img_convert/7e1d309b1791bb79db8214f71433583d.png
[img_img 17]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/16/de9d3428f87e47869272834e8b5165f6.png
[img 18]: https://img-blog.csdnimg.cn/img_convert/0aa5d175da1758337f45d0742a0944fc.png
[img_img 18]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/16/bf21ffe368084dc59cff8af5f3862835.png
[img 19]: https://img-blog.csdnimg.cn/img_convert/aeb234007abe0b151bd5c69b7bf7f689.png
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