学习目标：
提示：学习如何利用Redisson实现点赞排行榜功能，按照时间顺序
当用户给某一篇文章点赞后，会再数据库中存储一条数据，并且在Redis中存储一条数据为当前博客的点赞用户标识，来区分哪个用户对文章进行了点赞，使用ZSet数据结构对点赞用户进行排序来实现排行榜功能
学习产出：
解决方案：
- 点赞后的用户记录在Redis的set数据类型中
1. 准备pom环境
java
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-data-redis</artifactId>
</dependency>
<dependency>
<groupId>org.apache.commons</groupId>
<artifactId>commons-pool2</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-web</artifactId>
</dependency>
<dependency>
<groupId>mysql</groupId>
<artifactId>mysql-connector-java</artifactId>
<scope>runtime</scope>
<version>5.1.47</version>
</dependency>
<dependency>
<groupId>org.projectlombok</groupId>
<artifactId>lombok</artifactId>
<optional>true</optional>
</dependency>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-test</artifactId>
<scope>test</scope>
</dependency>
<dependency>
<groupId>com.baomidou</groupId>
<artifactId>mybatis-plus-boot-starter</artifactId>
<version>3.4.3</version>
</dependency>
<!--hutool-->
<dependency>
<groupId>cn.hutool</groupId>
<artifactId>hutool-all</artifactId>
<version>5.7.17</version>
</dependency>
<dependency>
<groupId>org.redisson</groupId>
<artifactId>redisson</artifactId>
<version>3.23.1</version>
</dependency>2. 配置ThreadLocal和过滤器
java
public class UserHolder {
private static final ThreadLocal<UserDTO> tl = new ThreadLocal<>();
public static void saveUser(UserDTO user){
tl.set(user);
}
public static UserDTO getUser(){
return tl.get();
}
public static void removeUser(){
tl.remove();
}
}
java
@Configuration
public class MvcConfig implements WebMvcConfigurer {
@Autowired
private StringRedisTemplate redis;
@Override
public void addInterceptors(InterceptorRegistry registry) {
registry.addInterceptor(new LoginInterceptor()).excludePathPatterns("/user/code","/user/login","/blog/hot","/shop/**","/shop-type/**","/voucher/**").order(2);
registry.addInterceptor(new RefreshTokenInterceptor(redis)).addPathPatterns("/**").order(1);
}
}
---------------------------------------------
@Slf4j
public class LoginInterceptor implements HandlerInterceptor {
//controller执行之前
@Override
public boolean preHandle(HttpServletRequest request, HttpServletResponse response, Object handler) throws Exception {
//1.判断是否需要拦截ThreadLocal
if (UserHolder.getUser()==null) {
response.setStatus(401);
return false;
}
//7.放行
return true;
}
//渲染后返回给前台数据前
@Override
public void afterCompletion(HttpServletRequest request, HttpServletResponse response, Object handler, Exception ex) throws Exception {
//移除用户，避免内存泄露
UserHolder.removeUser();
}
}
---------------------------------------------------
@Slf4j
public class RefreshTokenInterceptor implements HandlerInterceptor {
//这个对象不是由spring管理的所以不能用注解自动注入
private StringRedisTemplate redis;
public RefreshTokenInterceptor(StringRedisTemplate redis) {
this.redis = redis;
}
//controller执行之前
@Override
public boolean preHandle(HttpServletRequest request, HttpServletResponse response, Object handler) throws Exception {
//1.获取请求头中的token
String token = request.getHeader("authorization");
if (StrUtil.isBlank(token)) {
return true;
}
//2.基于token获取redis中的用户
//通过key取到hash中的map集合数据
Map<Object, Object> userMap = redis.opsForHash().entries("login:token:" + token);
//3.判断用户是否存在
if (userMap.isEmpty()) {
return true;
}
//5.将查询到的hash数据转为userDto对象
UserDTO userDTO = BeanUtil.fillBeanWithMap(userMap, new UserDTO(), false);
//6.存在，保存用户信息到ThreadLocal中
UserHolder.saveUser(userDTO);
//7.刷新token有效期
redis.expire(LOGIN_USER_KEY + token, 30, TimeUnit.MINUTES);
log.info("我是第一个拦截器当前拦截所有请求的用户为，线程为{},{}",UserHolder.getUser(),Thread.currentThread());
//8.放行
return true;
}3. Controller层：负责接收请求和向下分配
java
@RestController
@RequestMapping("/blog")
public class BlogController{
@Resource
private IBlogService blogService;
@PutMapping("/like/{id}")
public Result likeBlog(@PathVariable("id") Long id) {
return blogService.likeBlog(id);
}
}4. Service层：负责业务的处理逻辑点赞功能，将文章的点赞用户以时间戳为分数存入Redis
java
@Service
public class BlogServiceImpl extends ServiceImpl<BlogMapper, Blog> implements IBlogService {
@Autowired
private IUserService userService;
@Resource
private StringRedisTemplate redis;
@Override
public Result likeBlog(Long id) {
//1.获取登录用户
Long userId = UserHolder.getUser().getId();
//2.判断当前用户是否已经点赞
String key = "blog:liked:" + id;
//获取当前登录用户的分数，若文章中的用户id分数为null说明未点赞
Double score = redis.opsForZSet().score(key, userId.toString());
if (score == null) {
//3.如果未点赞，可以点赞
//3.1 点赞+1
boolean isSuccess = update().setSql("liked= liked +1").eq("id", id).update();
//3.2保存当前点赞用户到Redis的文章set集合中，文章set集合中记录的是点赞用户的id，
//分数是时间戳，可以进行排序
if (isSuccess) {
//存入Redis的分数值以当前时间戳存入
redis.opsForZSet().add(key, userId.toString(), System.currentTimeMillis());
}
} else {
//4.如果已点赞，取消点赞
//4.1点赞-1
boolean isSuccess = update().setSql("liked = liked -1").eq("id", id).update();
//4.2把用户从Redis的set集合移除
if (isSuccess) {
redis.opsForZSet().remove(key, userId.toString());
}
}
return null;
}
}5. 上述为下面的排行榜做铺垫
查询当前文章的点赞排行榜，id是文章id号
java
@PutMapping("/likes/{id}")
public Result likesBlog(@PathVariable("id") Long id) {
return blogService.queryBlogLikes(id);
}
java
@Override
public Result queryBlogLikes(Long id) {
String key="blog:liked:" + id;
//取出前五条数据
Set<String> rangeData = redis.opsForZSet().range(key, 0, 4);
if (rangeData==null) {
return Result.ok(Collections.emptyList());
}
//将文章点赞的前五条用户id转换为Long类型
List<Long> ids = rangeData.stream().map(Long::valueOf).collect(Collectors.toList());
String idStr = StrUtil.join(",", ids);
//去数据库把这些用户查询出来，并且数据脱敏返回给前端
List<User> users = userService.query().in("id",ids).last("order by field(id,"+idStr+")").list();
UserDTO userData = BeanUtil.copyProperties(users, UserDTO.class);
return Result.ok(userData);
}