5.Redis 实现点赞 优化登陆(验证码 token..)

1. Redis

（1）简介

• Redis 是一个高性能的 key-value 数据库

• 原子 – Redis的所有操作都是原子性的。多个操作也支持事务，即原子性，通过MULTI和EXEC指令包起来。

• 非关系形数据库

• 数据全部存在内存中，性能高。

（2）数据类型

Redis支持五种数据类型：string（字符串），hash（哈希），list（列表），set（集合）及zset(sorted set：有序集合)。

• string 是 redis 最基本的类型，你可以理解成与 Memcached 一模一样的类型，一个 key 对应一个 value。

• Redis hash 是一个键值(key=>value)对集合。Redis hash 是一个 string 类型的 field 和 value 的映射表，hash 特别适合用于存储对象。

• Redis 列表是简单的字符串列表，按照插入顺序排序。你可以添加一个元素到列表的头部（左边）或者尾部（右边）。

• Redis 的 Set 是 string 类型的无序集合，集合是通过hash实现的

• Redis zset 和 set 一样也是string类型元素的集合,且不允许重复的成员。不同的是每个元素都会关联一个double类型的分数。redis正是通过分数来为集合中的成员进行从小到大的排序。

（3）基本操作

@Test
public void testStrings() {String redisKey = "test:count";redisTemplate.opsForValue().set(redisKey, 1);System.out.println(redisTemplate.opsForValue().get(redisKey));System.out.println(redisTemplate.opsForValue().increment(redisKey));System.out.println(redisTemplate.opsForValue().decrement(redisKey));
}@Test
public void testHashes() {String redisKey = "test:user";redisTemplate.opsForHash().put(redisKey, "id", 1);redisTemplate.opsForHash().put(redisKey, "username", "zhangsan");System.out.println(redisTemplate.opsForHash().get(redisKey, "id"));System.out.println(redisTemplate.opsForHash().get(redisKey, "username"));
}@Test
public void testLists() {String redisKey = "test:ids";redisTemplate.opsForList().leftPush(redisKey, 101);redisTemplate.opsForList().leftPush(redisKey, 102);redisTemplate.opsForList().leftPush(redisKey, 103);System.out.println(redisTemplate.opsForList().size(redisKey));System.out.println(redisTemplate.opsForList().index(redisKey, 0));System.out.println(redisTemplate.opsForList().range(redisKey, 0, 2));System.out.println(redisTemplate.opsForList().leftPop(redisKey));System.out.println(redisTemplate.opsForList().leftPop(redisKey));System.out.println(redisTemplate.opsForList().leftPop(redisKey));
}@Test
public void testSets() {String redisKey = "test:teachers";redisTemplate.opsForSet().add(redisKey, "刘备", "关羽", "张飞", "赵云", "诸葛亮");System.out.println(redisTemplate.opsForSet().size(redisKey));System.out.println(redisTemplate.opsForSet().pop(redisKey));System.out.println(redisTemplate.opsForSet().members(redisKey));
}@Test
public void testSortedSets() {String redisKey = "test:students";redisTemplate.opsForZSet().add(redisKey, "唐僧", 80);redisTemplate.opsForZSet().add(redisKey, "悟空", 90);redisTemplate.opsForZSet().add(redisKey, "八戒", 50);redisTemplate.opsForZSet().add(redisKey, "沙僧", 70);redisTemplate.opsForZSet().add(redisKey, "白龙马", 60);System.out.println(redisTemplate.opsForZSet().zCard(redisKey));System.out.println(redisTemplate.opsForZSet().score(redisKey, "八戒"));System.out.println(redisTemplate.opsForZSet().reverseRank(redisKey, "八戒"));System.out.println(redisTemplate.opsForZSet().reverseRange(redisKey, 0, 2));
}多次访问同一个key
@Test
public void testBoundOperations() {String redisKey = "test:count";BoundValueOperations operations = redisTemplate.boundValueOps(redisKey);operations.increment();operations.increment();operations.increment();operations.increment();operations.increment();System.out.println(operations.get());
}

（4）spring 配置 redis

引入依赖

<dependency><groupId>org.springframework.boot</groupId><artifactId>spring-boot-starter-data-redis</artifactId>
</dependency>

在 application.properties 中声明：访问哪个库，host地址，端口号

# RedisProperties
spring.redis.database=11
spring.redis.host=localhost
spring.redis.port=6379

在 config 下实现 RedisConfig 类

注入连接工厂才能访问数据库 RedisConnectionFactory factory

实例化 bean new RedisTemplate<>();

设置工厂后有访问数据库能力 template.setConnectionFactory(factory);

指定序列化方式（数据转化方式）

//定义自定义的redis对象@Beanpublic RedisTemplate<String, Object> redisTemplate(RedisConnectionFactory factory){RedisTemplate<String,Object> redisTemplate = new RedisTemplate<>();redisTemplate.setConnectionFactory(factory);//主要配置 序列化的方式//设置key 的 序列化方式redisTemplate.setKeySerializer(RedisSerializer.string());//设置value的序列化方式redisTemplate.setValueSerializer(RedisSerializer.json());//设置hash 的 key序列化redisTemplate.setHashKeySerializer(RedisSerializer.string());//设置 hash 的 value 序列化redisTemplate.setHashValueSerializer(RedisSerializer.json());//出发 使其生效redisTemplate.afterPropertiesSet();return  redisTemplate;}

（5）Redis 事务 管理

事务内命令不会立即执行，提交后统一执行

使用编程式事务进行管理，声明式事务用的少

调用 redisTemplate ，方法内部做匿名实现

SessionCallback() 里方法execute重写，内部实现事务逻辑

启用事务 operations.multi();

提交事务 operations.exec();

// 编程式事务
@Test
public void testTransactional() {Object obj = redisTemplate.execute(new SessionCallback() {@Overridepublic Object execute(RedisOperations operations) throws DataAccessException {String redisKey = "test:tx";operations.multi();operations.opsForSet().add(redisKey, "zhangsan");operations.opsForSet().add(redisKey, "lisi");operations.opsForSet().add(redisKey, "wangwu");System.out.println(operations.opsForSet().members(redisKey));return operations.exec();}});System.out.println(obj);
}

2.点赞

（1）业务层

生成redis key的工具 在 util 下实现 RedisKeyUtil，集合set存储谁给某个实体点的赞

public class RedisKeyUtil {private static final String SPLIT = ":";private static final String PREFIX_ENTITY_LIKE = "like:entity";private static final String PREFIX_USER_LIKE = "like:user";// 某个实体的赞// like:entity:entityType:entityId -> set(userId)public static String getEntityLikeKey(int entityType, int entityId) { //实体类型  实体IDreturn PREFIX_ENTITY_LIKE + SPLIT + entityType + SPLIT + entityId;}}

Service 下实现 LikeService

@Service
public class LikeService {@Autowiredprivate RedisTemplate redisTemplate;// 点赞public void like(int userId, int entityType, int entityId) {//获取keyString entityLikeKey = RedisKeyUtil.getEntityLikeKey(entityType,entityId);//判断当前用户是否点过赞   即userid 是否在set中if(redisTemplate.opsForSet().isMember(entityLikeKey,userId)){redisTemplate.opsForSet().remove(entityLikeKey,userId);}else {redisTemplate.opsForSet().add(entityLikeKey,userId);}}// 查询某实体点赞的数量public long findEntityLikeCount(int entityType, int entityId){String entityLikeKey = RedisKeyUtil.getEntityLikeKey(entityType,entityId);return redisTemplate.opsForSet().size(entityLikeKey);}// 查询某人对某实体的点赞状态public int findEntityLikeStatus(int userId, int entityType, int entityId) {String entityLikeKey = RedisKeyUtil.getEntityLikeKey(entityType,entityId);return redisTemplate.opsForSet().isMember(entityLikeKey,userId)? 1:0 ;}
}

（2）表现层

Controller 下实现 LikeController

1. 获取当前用户

2. 调用service点赞方法

3. 获取数量和状态

4. 放入map

5. 返回json格式数据

@Controller
public class LikeController {@Autowiredprivate LikeService likeService;@Autowiredprivate HostHolder hostHolder;@RequestMapping(path = "/like", method = RequestMethod.POST)@ResponseBodypublic String like(int entityType, int entityId){User user = hostHolder.getUser();//点赞likeService.like(user.getId(), entityType,entityId);//更新点赞数量long likeCount = likeService.findEntityLikeCount(entityType,entityId);//查询状态int likeStatus = likeService.findEntityLikeStatus(user.getId(),entityType,entityId);Map<String,Object> map = new HashMap<>();map.put("likeCount", likeCount);map.put("likeStatus", likeStatus);return CommunityUtil.getJSONString(0, null, map);}
}

帖子详情页面赞的数量的显示

修改 DiscussPostController 下的 getDiscussPost

//根据 帖子id 查询帖子内容 评论 评论的回复@RequestMapping(path = "/detail/{discussPostId}",method = RequestMethod.GET)public String getDiscussPost(@PathVariable("discussPostId") int discussPostId, Model model, Page page){//根据帖子id查询帖子DiscussPost post = discussPostService.findDiscussPostById(discussPostId);model.addAttribute("post",post);//根据userid查询userUser user =userService.findUserById(post.getUserId());model.addAttribute("user",user);// 点赞数量long likeCount = likeService.findEntityLikeCount(ENTITY_TYPE_POST, discussPostId);model.addAttribute("likeCount", likeCount);// 点赞状态int likeStatus = hostHolder.getUser() == null ? 0 :likeService.findEntityLikeStatus(hostHolder.getUser().getId(), ENTITY_TYPE_POST, discussPostId);model.addAttribute("likeStatus", likeStatus);//查评论的分页信息page.setLimit(5);page.setPath("/discuss/detail/" + discussPostId);page.setRows(post.getCommentCount());//评论：给帖子的评论//回复：给评论的评论//获取所有评论List<Comment> commentList = commentService.findCommentsByEntity(ENTITY_TYPE_POST,post.getId(), page.getOffset(),page.getLimit());//用于封装 每条评论及每条评论的回复。。。List<Map<String,Object>> commentVoList = new ArrayList<>();//每一条评论 找到评论的作者。找到该评论的回复，回复的作者，回复的用户for (Comment comment:commentList) {Map<String,Object> commentVo = new HashMap<>();//存入评论内容commentVo.put("comment",comment);//放入 作者commentVo.put("user",userService.findUserById(comment.getUserId()));// 点赞数量likeCount = likeService.findEntityLikeCount(ENTITY_TYPE_COMMENT, comment.getId());commentVo.put("likeCount", likeCount);// 点赞状态likeStatus = hostHolder.getUser() == null ? 0 :likeService.findEntityLikeStatus(hostHolder.getUser().getId(), ENTITY_TYPE_COMMENT, comment.getId());commentVo.put("likeStatus", likeStatus);//获取该评论的所有回复List<Comment> replyList = commentService.findCommentsByEntity(ENTITY_TYPE_COMMENT, comment.getId(), 0, Integer.MAX_VALUE);//用于封装 每一条回复的 作者 回复咪表List<Map<String, Object>> replyVoList = new ArrayList<>();if(replyVoList != null){for (Comment reply: replyList) {Map<String,Object> replyVo = new HashMap<>();//回复replyVo.put("reply", reply);// 放入 回复的作者replyVo.put("user", userService.findUserById(reply.getUserId()));//回复目标User target = reply.getTargetId() == 0 ? null : userService.findUserById(reply.getTargetId());replyVo.put("target", target);// 点赞数量likeCount = likeService.findEntityLikeCount(ENTITY_TYPE_COMMENT, reply.getId());replyVo.put("likeCount", likeCount);// 点赞状态likeStatus = hostHolder.getUser() == null ? 0 :likeService.findEntityLikeStatus(hostHolder.getUser().getId(), ENTITY_TYPE_COMMENT, reply.getId());replyVo.put("likeStatus", likeStatus);//将 单条回复放入 此 评论 总的 回复表replyVoList.add(replyVo);}}//将回复总表 嵌入 单条评论commentVo.put("replys", replyVoList);//回复数量int replyCount = commentService.findCommentCount(ENTITY_TYPE_COMMENT, comment.getId());commentVo.put("replyCount", replyCount);commentVoList.add(commentVo);}model.addAttribute("comments", commentVoList);return "/site/discuss-detail";}

3.使用Redis存储验证码

LoginController.getKaptcha

        //  老方法 验证码 存入session//session.setAttribute("kaptcha", text);// 验证码的归属 一个验证码 绑定 一个 kaptchaOwnerString kaptchaOwner = CommunityUtil.generateUUID();Cookie cookie = new Cookie("kaptchaOwner", kaptchaOwner);cookie.setMaxAge(60);cookie.setPath(contextPath);response.addCookie(cookie);//存入redisString redisKey = RedisKeyUtil.getKaptchaKey(kaptchaOwner);redisTemplate.opsForValue().set(redisKey, text, 60, TimeUnit.SECONDS);

LoginController.login

// 检查验证码 String kaptcha = (String) session.getAttribute("kaptcha");//获取验证码String kaptcha =null;if(StringUtils.isNotBlank(kaptchaOwner)){//是否存在String redisKey = RedisKeyUtil.getKaptchaKey(kaptchaOwner);kaptcha = (String) redisTemplate.opsForValue().get(redisKey);}//比对验证码if(StringUtils.isBlank(kaptcha) || StringUtils.isBlank(code) || !kaptcha.equals(code)){model.addAttribute("codeMsg", "验证码不正确!");return "/site/login";}

4. 使用Redis存储登录凭证

UserService

1. login 生成登录凭证

// 生成登录凭证LoginTicket loginTicket = new LoginTicket();loginTicket.setUserId(user.getId());loginTicket.setTicket(CommunityUtil.generateUUID());loginTicket.setStatus(0);loginTicket.setExpired(new Date(System.currentTimeMillis() + expiredSeconds * 1000));//loginTicketMapper.insertLoginTicket(loginTicket);String redisKey = RedisKeyUtil.getTicketKey(loginTicket.getTicket());redisTemplate.opsForValue().set(redisKey, loginTicket);

2. logout 退出登录，ticket取出来再存进去

public void logout(String ticket) {//loginTicketMapper.updateStatus(ticket, 1);String redisKey  = RedisKeyUtil.getTicketKey(ticket);LoginTicket loginTicket = (LoginTicket) redisTemplate.opsForValue().get(redisKey);loginTicket.setStatus(1);redisTemplate.opsForValue().set(redisKey,loginTicket);}

3. LoginTicket 查询凭证

public LoginTicket findLoginTicket(String ticket) {// return loginTicketMapper.selectByTicket(ticket);String redisKey  = RedisKeyUtil.getTicketKey(ticket);LoginTicket loginTicket = (LoginTicket) redisTemplate.opsForValue().get(redisKey);return  loginTicket;}

5.使用Redis缓存用户数据

查用户时： 先查缓存 在查mysql

UserService

// 1.优先从缓存中取值
private User getCache(int userId) {String redisKey = RedisKeyUtil.getUserKey(userId);return (User) redisTemplate.opsForValue().get(redisKey);
}// 2.取不到时初始化缓存数据
private User initCache(int userId) {User user = userMapper.selectById(userId);String redisKey = RedisKeyUtil.getUserKey(userId);redisTemplate.opsForValue().set(redisKey, user, 3600, TimeUnit.SECONDS);return user;
}// 3.数据变更时清除缓存数据
private void clearCache(int userId) {String redisKey = RedisKeyUtil.getUserKey(userId);redisTemplate.delete(redisKey);
}public User findUserById(int id) {
//        return userMapper.selectById(id);User user = getCache(id);if (user == null) {user = initCache(id);}return user;
}public int activation(int userId, String code) {User user = userMapper.selectById(userId);if (user.getStatus() == 1) {return ACTIVATION_REPEAT;} else if (user.getActivationCode().equals(code)) {userMapper.updateStatus(userId, 1);clearCache(userId);return ACTIVATION_SUCCESS;} else {return ACTIVATION_FAILURE;}
}public int updateHeader(int userId, String headerUrl) {
//        return userMapper.updateHeader(userId, headerUrl);int rows = userMapper.updateHeader(userId, headerUrl);clearCache(userId);return rows;
}