黑马点评全功能实现总结

1. 项目介绍

       黑马点评项目是一个前后端分离项目，类似于大众点评，实现了发布查看商家，达人探店，点赞，关注等功能，业务可以帮助商家引流，增加曝光度，也可以为用户提供查看提供附近消费场所，主要。用来配合学习Redis的知识。

 1.1 项目使用的技术栈

      SpringBoot+MySql+Lombok+MyBatis-Plus+Hutool+Redis

 1.2项目架构

      采用单体架构

1.3项目地址

黑马点评: 基于springboot +mybatis+redis实现的多功能探店APP，涵盖发博客，评价，定位，关注，共同关注，秒杀，消息推送等多个功能

2.功能模块

2.1用户登录模块

手机号创建用户

private User createUserWithPhone(String phone) {
        User user = new User();
        user.setPhone(phone);
        user.setNickName(USER_NICK_NAME_PREFIX+RandomUtil.randomString(10));
        save(user);
        return user;

    }

登录验证

 @Override
    public Result login(LoginFormDTO loginForm, HttpSession session) {
        String phone = loginForm.getPhone();
        String code = loginForm.getCode();
        if (RegexUtils.isPhoneInvalid(phone)){
            return Result.fail("手机号格式错误！");
        }

        String cacheCode = stringRedisTemplate.opsForValue().get(LOGIN_CODE_KEY+phone);
        if (cacheCode ==null || !cacheCode.equals(code)){
            return Result.fail("验证码错误");
        }
        User user = query().eq("phone", phone).one();
        if (user ==null){
            user=createUserWithPhone(phone);
        }
        String token = UUID.randomUUID().toString(true);
        UserDTO userDTO = BeanUtil.copyProperties(user, UserDTO.class);
        Map userMap = BeanUtil.beanToMap(userDTO,new HashMap<>(),
                CopyOptions.create().setIgnoreNullValue(true)
                        .setFieldValueEditor((fieldName,fieldValue)->fieldValue.toString()));
        String tokenKey = LOGIN_USER_KEY + token;
        stringRedisTemplate.opsForHash().putAll(tokenKey,userMap);
        stringRedisTemplate.expire(tokenKey,LOGIN_USER_TTL,TimeUnit.MINUTES);
        return Result.ok(token);
    }

发送验证码

 @Resource
    private StringRedisTemplate stringRedisTemplate;
    @Override
    public Result sendCode(String phone, HttpSession session) {
        if (RegexUtils.isPhoneInvalid(phone)){
            return Result.fail("手机号格式错误！");
        }


        String code = RandomUtil.randomNumbers(6);

        stringRedisTemplate.opsForValue().set(LOGIN_CODE_KEY+phone,code,LOGIN_CODE_TTL, TimeUnit.MINUTES);


        log.debug("你的手机验证码为：{}，时长为2分钟，请尽快使用",code);
        return Result.ok();
    }

登出(代码量太小直接在controll实现)

 @PostMapping("/logout")
    public Result logout(){
        UserHolder.removeUser();
        return Result.ok();
    }

拦截器

登录拦截器

package com.hmdp.utils;

import cn.hutool.core.bean.BeanUtil;
import cn.hutool.core.util.StrUtil;
import com.hmdp.dto.UserDTO;
import org.springframework.data.redis.core.StringRedisTemplate;
import org.springframework.web.servlet.HandlerInterceptor;

import javax.servlet.http.HttpServletRequest;
import javax.servlet.http.HttpServletResponse;
import javax.servlet.http.HttpSession;
import java.util.Map;
import java.util.concurrent.TimeUnit;


public class LoginInterceptor implements HandlerInterceptor {


    @Override
    public boolean preHandle(HttpServletRequest request, HttpServletResponse response, Object handler) throws Exception {
        if (UserHolder.getUser()==null){
            response.setStatus(401);
            return false;
        }
        return true;
    }

}

刷新token拦截器，长时间不操作用户token过期

package com.hmdp.utils;

import cn.hutool.core.bean.BeanUtil;
import cn.hutool.core.util.StrUtil;
import com.hmdp.dto.UserDTO;
import org.springframework.data.redis.core.StringRedisTemplate;
import org.springframework.web.servlet.HandlerInterceptor;

import javax.servlet.http.HttpServletRequest;
import javax.servlet.http.HttpServletResponse;
import javax.servlet.http.HttpSession;
import java.util.Map;
import java.util.concurrent.TimeUnit;


public class RefreshTokenInterceptor implements HandlerInterceptor {
    private StringRedisTemplate stringRedisTemplate;

    public RefreshTokenInterceptor(StringRedisTemplate stringRedisTemplate){
        this.stringRedisTemplate=stringRedisTemplate;
    }

    @Override
    public boolean preHandle(HttpServletRequest request, HttpServletResponse response, Object handler) throws Exception {
        String token = request.getHeader("authorization");
        if (StrUtil.isBlank(token)){

            return true;
        }
        String key = RedisConstants.LOGIN_USER_KEY + token;
        Map userMap = stringRedisTemplate.opsForHash().entries(key);
        if (userMap.isEmpty()){
            return true;
        }
        UserDTO userDTO = BeanUtil.fillBeanWithMap(userMap, new UserDTO(), false);
        UserHolder.saveUser(userDTO);
        stringRedisTemplate.expire(key,RedisConstants.LOGIN_USER_TTL, TimeUnit.MINUTES);
        return true;
    }

    @Override
    public void afterCompletion(HttpServletRequest request, HttpServletResponse response, Object handler, Exception ex) throws Exception {
        UserHolder.removeUser();
    }
}

在注册中心加入这两个拦截器并配置路径

package com.hmdp.config;

import com.hmdp.utils.LoginInterceptor;
import com.hmdp.utils.RefreshTokenInterceptor;
import org.springframework.context.annotation.Configuration;
import org.springframework.data.redis.core.StringRedisTemplate;
import org.springframework.web.servlet.config.annotation.InterceptorRegistry;
import org.springframework.web.servlet.config.annotation.WebMvcConfigurer;

import javax.annotation.Resource;

@Configuration
public class MvcConfig implements WebMvcConfigurer {

    @Resource
    private StringRedisTemplate stringRedisTemplate;

    @Override
    public void addInterceptors(InterceptorRegistry registry) {
        registry.addInterceptor(new LoginInterceptor())
                .excludePathPatterns(
                        "/blog/hot",
                        "/voucher/**",
                        "/upload/**",
                        "/shop/**",
                        "/shop-type/**",
                        "/user/code",
                        "/user/login"
                ).order(1);
        registry.addInterceptor(new RefreshTokenInterceptor(stringRedisTemplate)).addPathPatterns("/**").order(0);
    }
}

2.2查询商户模块

 进入主页，先从Redis中读出商户分类信息，若Redis中为空则向MySQL中读取，并写入Redis中。主页店铺分类信息为常用信息，应使用Redis避免频繁读取数据库。 该功能的实现分别应对Redis缓存容易出现的三种给出了三个不同的解决方案：

1）缓存穿透（用户对不存在的数据进行大量请求，在Redis中为未中便会请求MySQL数据库，造成数据库崩溃）

解决措施（缓存空对象，布隆过滤器）

这里采用设置默认值的方式应对穿透，当请求像MySQL中也未命中数据时，会返回一个默认值并写入Redis缓存。

2）缓存击穿（热点数据在Redis中的缓存失效，大量同时访问MySQL造成崩溃）

 解决措施（设置逻辑过期，互斥锁）

这里采用给热点数据在Redis中的缓存设置逻辑过期+互斥锁

3）缓存雪崩（Redis中大量缓存同时失效或Redis宕机，大量请求同时访问数据库，造成数据库崩溃）

解决措施（设置多级缓存，采用Redis集群服务，给缓存过期时间加上一个随机值，在业务中添加限流）

package com.hmdp.utils;


import cn.hutool.core.util.BooleanUtil;
import cn.hutool.core.util.StrUtil;
import cn.hutool.json.JSONObject;
import cn.hutool.json.JSONUtil;
import com.hmdp.entity.Shop;
import lombok.extern.slf4j.Slf4j;
import org.springframework.data.redis.core.StringRedisTemplate;
import org.springframework.stereotype.Component;

import java.time.LocalDateTime;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
import java.util.concurrent.TimeUnit;
import java.util.function.Function;

import static com.hmdp.utils.RedisConstants.*;

@Slf4j
@Component
public class CacheClient {

    private final StringRedisTemplate stringRedisTemplate;


    public CacheClient(StringRedisTemplate stringRedisTemplate) {
        this.stringRedisTemplate = stringRedisTemplate;
    }

    public void set(String key, Object value, Long time, TimeUnit unit){
        stringRedisTemplate.opsForValue().set(key, JSONUtil.toJsonStr(value),time,unit);
    }

    public void setWithLogicalExpire(String key, Object value, Long time, TimeUnit unit){

        RedisData redisData = new RedisData();
        redisData.setData(value);
        redisData.setExpireTime(LocalDateTime.now().plusSeconds(unit.toSeconds(time)));
        stringRedisTemplate.opsForValue().set(key, JSONUtil.toJsonStr(redisData));
    }

    public   R queryWithPassThrougn(
            String keyPrefix, ID id, Class type, Function dbFallback,Long time, TimeUnit unit){
        String key = keyPrefix + id;
        String json = stringRedisTemplate.opsForValue().get(key);
        if (StrUtil.isNotBlank(json)){

            return JSONUtil.toBean(json, type);
        }
        if (json!=null){
            return null;
        }
        R r = dbFallback.apply(id);
        if (r==null){
            stringRedisTemplate.opsForValue().set(key,"",CACHE_NULL_TTL,TimeUnit.MINUTES);
            return null;
        }
        this.set(key,r,time,unit);

        return r;
    }

    private static final ExecutorService CACHE_REBUILD_EXECUTOR= Executors.newFixedThreadPool(10);

    public   R queryWithLogicalExpire(
            String keyPrefix, ID id, Class type, Function dbFallback,Long time, TimeUnit unit){
        String key = CACHE_SHOP_KEY + id;
        String shopJson = stringRedisTemplate.opsForValue().get(key);
        if (StrUtil.isBlank(shopJson)){

            return null;
        }
        RedisData redisData = JSONUtil.toBean(shopJson, RedisData.class);
        JSONObject data = (JSONObject) redisData.getData();
        R r = JSONUtil.toBean(data, type);
        LocalDateTime expireTime = redisData.getExpireTime();
        if (expireTime.isAfter(LocalDateTime.now())){
            return r;
        }
        String lockKey = LOCK_SHOP_KEY + id;
        boolean isLock = tryLock(lockKey);
        if (isLock){
            CACHE_REBUILD_EXECUTOR.submit(()->{
                try {
                    R r1 = dbFallback.apply(id);
                    this.setWithLogicalExpire(key,r1,time,unit);
                } catch (Exception e) {
                    throw new RuntimeException(e);
                } finally {
                    unlock(lockKey);
                }
            });
        }


        return r;
    }

    private boolean tryLock(String key){
        Boolean flag = stringRedisTemplate.opsForValue().setIfAbsent(key, "1", 10, TimeUnit.SECONDS);
        return BooleanUtil.isTrue(flag);
    }

    private void unlock(String key){
        stringRedisTemplate.delete(key);
    }

}

2.3优惠券秒杀模块

 采用异步下单的方式，先运行Lua脚本，判断是否下过单，若未下过单，则扣减Redis库存，脚本运行成功，有购买资格，则生成一个全局Id作为订单id，生成订单信息，把订单保存到一个阻塞队列，阻塞队列收到订单后，获取分布式锁后再把订单信息和库存信息同步到MySQL，然后释放锁。该模块利用分布式锁实现一人一单功能，利用Lua确保库存不会变负数。

package com.hmdp.service.impl;

import com.hmdp.dto.Result;
import com.hmdp.entity.VoucherOrder;
import com.hmdp.mapper.VoucherOrderMapper;
import com.hmdp.service.ISeckillVoucherService;
import com.hmdp.service.IVoucherOrderService;
import com.baomidou.mybatisplus.extension.service.impl.ServiceImpl;
import com.hmdp.utils.RedisIdWorker;
import com.hmdp.utils.UserHolder;
import lombok.extern.slf4j.Slf4j;
import org.redisson.api.RLock;
import org.redisson.api.RedissonClient;
import org.springframework.aop.framework.AopContext;
import org.springframework.core.io.ClassPathResource;
import org.springframework.data.redis.core.StringRedisTemplate;
import org.springframework.data.redis.core.script.DefaultRedisScript;
import org.springframework.stereotype.Service;
import org.springframework.transaction.annotation.Transactional;

import javax.annotation.PostConstruct;
import javax.annotation.Resource;
import java.util.Collections;
import java.util.concurrent.ArrayBlockingQueue;
import java.util.concurrent.BlockingQueue;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;

/**
 * 

 *  服务实现类
 * 
 *
 * @author 青云
 * @since 2021-12-22
 */
@Slf4j
@Service
public class VoucherOrderServiceImpl extends ServiceImpl implements IVoucherOrderService {

    @Resource
    private ISeckillVoucherService seckillVoucherService;

    @Resource
    private RedisIdWorker redisIdWorker;

    @Resource
    private StringRedisTemplate stringRedisTemplate;

    @Resource
    private RedissonClient redissonClient;
    private static final DefaultRedisScript SECKILL_SCRIPT;

    static {
        SECKILL_SCRIPT=new DefaultRedisScript<>();
        SECKILL_SCRIPT.setLocation(new ClassPathResource("seckill.lua"));
        SECKILL_SCRIPT.setResultType(Long.class);
    }

    private BlockingQueue orderTasks=new ArrayBlockingQueue<>(1024*1024);

    private static final ExecutorService SECKILL_ORDER_EXECUTOR = Executors.newSingleThreadExecutor();

    @PostConstruct
    private void init(){
        SECKILL_ORDER_EXECUTOR.submit(new VoucherOrderHandle());
    }
    private class VoucherOrderHandle implements Runnable{

        @Override
        public void run() {
            while (true){
                try {
                    VoucherOrder voucherOrder = orderTasks.take();
                    handleVoucherOrder(voucherOrder);
                } catch (InterruptedException e) {
                    log.error("处理订单异常",e);
                }
            }
        }
    }
    private IVoucherOrderService proxy;

    private void handleVoucherOrder(VoucherOrder voucherOrder) {
        Long userId = voucherOrder.getUserId();
        RLock lock= redissonClient.getLock("lock:order:" + userId);

        boolean isLock = lock.tryLock();
        if (!isLock){
            log.error("不允许重复下单");
            return ;
        }
        //获取代理对象
        try {
            proxy.createVoucherOrder(voucherOrder);
        } finally {
            lock.unlock();
        }
    }

    @Override
    public Result seckillVoucher(Long voucherId) {
        Long userId = UserHolder.getUser().getId();
        //执行lua脚本
        Long result = stringRedisTemplate.execute(
                SECKILL_SCRIPT,
                Collections.emptyList(),
                voucherId.toString(), userId.toString()
        );
        //判断结果是否为0
        int r = result.intValue();
        if (r!=0){
            //不为0，代表没有购买资格
            return Result.fail(r==1?"库存不足":"不能重复下单");
        }
        //为0，有购买资格，把下单信息保存到阻塞队列
        VoucherOrder voucherOrder = new VoucherOrder();

        long orderId = redisIdWorker.nextId("order");

        voucherOrder.setId(orderId);
        voucherOrder.setUserId(userId);
        voucherOrder.setVoucherId(voucherId);
        orderTasks.add(voucherOrder);

        proxy = (IVoucherOrderService) AopContext.currentProxy();

        //返回订单id
        return Result.ok(orderId);
    }

//    @Override
//    public Result seckillVoucher(Long voucherId) {
//       //查询优惠券
//        SeckillVoucher voucher = seckillVoucherService.getById(voucherId);
//
//        //判断秒杀是否开始
//        if (voucher.getBeginTime().isAfter(LocalDateTime.now())) {
//            return Result.fail("秒杀尚未开始!");
//        }
//        //判断秒杀是否结束
//        if (voucher.getEndTime().isBefore(LocalDateTime.now())) {
//            return Result.fail("秒杀已结束!");
//        }
//        //判断库存是否充足
//        if (voucher.getStock()<1){
//            return Result.fail("库存不足！");
//        }
//
//        Long userId = UserHolder.getUser().getId();
        synchronized (UserHolder.getUser().getId().toString().intern()) {
        SimpleRedisLock lock = new SimpleRedisLock("order:" + userId, stringRedisTemplate);
//
//        RLock lock= redissonClient.getLock("lock:order:" + userId);
//
//        boolean isLock = lock.tryLock();
//        if (!isLock){
//            return Result.fail("不允许重复下单");
//        }
//        //获取代理对象
//        try {
//            IVoucherOrderService proxy = (IVoucherOrderService) AopContext.currentProxy();
//            return proxy.createVoucherOrder(voucherId);
//        } finally {
//            lock.unlock();
//        }
//
//    }

    @Transactional
    public void createVoucherOrder(VoucherOrder voucherOrder) {
        Long userId = voucherOrder.getId();

        int count = query().eq("user_id", userId).eq("voucher_id", voucherOrder.getVoucherId()).count();
        if (count>0){
            log.error("获取次数已上限");
            return ;
        }
        //扣减库存
        boolean success = seckillVoucherService.update()
                .setSql("stock=stock-1")
                .eq("voucher_id", voucherOrder.getVoucherId())
//                .eq("stock",voucher.getStock())
                .gt("stock",0)
                .update();
        if (!success){
            log.error("库存不足");
            return ;
        }
        //创建订单
//        VoucherOrder voucherOrder = new VoucherOrder();
//        long orderId = redisIdWorker.nextId("order");
//        voucherOrder.setId(orderId);
//        voucherOrder.setUserId(userId);
//        voucherOrder.setVoucherId(voucherOrder);
        save(voucherOrder);
        //返回订单id
//        return Result.ok(orderId);
    }
}

lua脚本

-- 1.参数列表
-- 1.1 优惠券id
local voucherId = ARGV[1]
-- 1.2 用户id
local userId = ARGV[2]

-- 2.数据key
-- 2.1 库存key   key 是优惠的业务名称加优惠券id  value 是优惠券的库存数
local stockKey = 'seckill:stock:' .. voucherId
-- 2.2 订单key   key 也是拼接的业务名称加优惠权id  而value是用户id， 这是一个set集合，凡购买该优惠券的用户都会将其id存入集合中
local orderKey = 'seckill:order:' .. voucherId

-- 3.脚本业务
-- 3.1 判断库存是否充足 get stockKey
if (tonumber(redis.call('get', stockKey)) <= 0)  then  --将get的value先转为数字类型才能判断比较
    -- 3.2 库存不足，返回1
    return 1
end
-- 3.3 判断用户是否下单 sismember orderKey userId命令，判断当前key集合中，是否存在该value；返回1存在，0不存在
if (redis.call('sismember', orderKey, userId) == 1) then
    --3.4 存在说明是重复下单，返回2
    return 2
end
-- 3.5 扣库存
redis.call('incrby', stockKey, -1)
-- 3.6 下单（保存用户）
redis.call('sadd', orderKey, userId)
return 0

2.4博客模块

点赞：用户浏览博客时，可以对博客进行点赞，点赞过的用户id，写入，Redis缓存中（zset：博客id，用户ID，时间）博客页并展示点赞次数和点赞列表头像，展示点赞列表时，注意点赞列表按时间排序，点赞时间早的排在前面，SQL语句应拼接order By  。

package com.hmdp.service.impl;

import cn.hutool.core.bean.BeanUtil;
import cn.hutool.core.util.BooleanUtil;
import cn.hutool.core.util.StrUtil;
import com.baomidou.mybatisplus.extension.plugins.pagination.Page;
import com.hmdp.dto.Result;
import com.hmdp.dto.ScrollResult;
import com.hmdp.dto.UserDTO;
import com.hmdp.entity.Blog;
import com.hmdp.entity.Follow;
import com.hmdp.entity.User;
import com.hmdp.mapper.BlogMapper;
import com.hmdp.service.IBlogService;
import com.baomidou.mybatisplus.extension.service.impl.ServiceImpl;
import com.hmdp.service.IFollowService;
import com.hmdp.service.IUserService;
import com.hmdp.utils.SystemConstants;
import com.hmdp.utils.UserHolder;
import org.springframework.data.redis.core.StringRedisTemplate;
import org.springframework.data.redis.core.ZSetOperations;
import org.springframework.stereotype.Service;

import javax.annotation.Resource;
import java.util.ArrayList;
import java.util.Collections;
import java.util.List;
import java.util.Set;
import java.util.stream.Collectors;

import static com.hmdp.utils.RedisConstants.BLOG_LIKED_KEY;
import static com.hmdp.utils.RedisConstants.FEED_KEY;

/**
 * 

 *  服务实现类
 * 
 *
 * @author 青云
 * @since 2021-12-22
 */
@Service
public class BlogServiceImpl extends ServiceImpl implements IBlogService {

    @Resource
    private IUserService userService;

    @Resource
    private StringRedisTemplate stringRedisTemplate;

    @Resource
    private IFollowService followService;
    @Override
    public Result queryHotBlog(Integer current) {
        // 根据用户查询
        Page page = query()
                .orderByDesc("liked")
                .page(new Page<>(current, SystemConstants.MAX_PAGE_SIZE));
        // 获取当前页数据
        List records = page.getRecords();
        // 查询用户
        records.forEach(blog -> {
            this.queryBlogUser(blog);
            this.isBlogLiked(blog);
        });
        return Result.ok(records);
    }

    private void queryBlogUser(Blog blog) {
        Long userId = blog.getUserId();
        User user = userService.getById(userId);
        blog.setName(user.getNickName());
        blog.setIcon(user.getIcon());
    }

    @Override
    public Result queryBlogById(Long id) {
        Blog blog = getById(id);
        if (blog ==null){
            return Result.fail("博客不存在");
        }
        queryBlogUser(blog);

        isBlogLiked(blog);

        return Result.ok(blog);
    }

    private void isBlogLiked(Blog blog) {
        UserDTO user = UserHolder.getUser();
        if (user == null){
            return;
        }
        Long userId = UserHolder.getUser().getId();
        //判断当前用户是否点赞
        String key = BLOG_LIKED_KEY + blog.getId();
        Double score = stringRedisTemplate.opsForZSet().score(key, userId.toString());
        blog.setIsLike(score !=null);
    }

    @Override
    public Result likeBlog(Long id) {
        Long userId = UserHolder.getUser().getId();
        //判断当前用户是否点赞
        String key = BLOG_LIKED_KEY + id;
        Double score = stringRedisTemplate.opsForZSet().score(key, userId.toString());
        if (score==null){
            boolean isSuccess = update().setSql("liked=liked+1").eq("id", id).update();
            if (isSuccess){
                stringRedisTemplate.opsForZSet().add(key,userId.toString(),System.currentTimeMillis());
            }
        }else {
            boolean isSuccess = update().setSql("liked = liked - 1").eq("id", id).update();

            if (isSuccess){
                stringRedisTemplate.opsForZSet().remove(key,userId.toString());
            }
        }
        return Result.ok();
    }

    @Override
    public Result queryBlogLikes(Long id) {
        String key = BLOG_LIKED_KEY + id;
        //查询top点赞用户
        Set top5 = stringRedisTemplate.opsForZSet().range(key, 0, 4);
        if (top5==null||top5.isEmpty()){
            return Result.ok(Collections.emptyList());
        }
        List ids = top5.stream().map(Long::valueOf).collect(Collectors.toList());
        String idStr = StrUtil.join(",", ids);
        List userDTOS = userService.query().in("id",ids)
                .last("ORDER BY FIELD(id,"+idStr+")").list()
                .stream()
                .map(user -> BeanUtil.copyProperties(user, UserDTO.class))
                .collect(Collectors.toList());
        return Result.ok(userDTOS);
    }

    @Override
    public Result saveBlog(Blog blog) {
        // 获取登录用户
        UserDTO user = UserHolder.getUser();
        blog.setUserId(user.getId());
        // 保存探店博文
        boolean isSuccess = save(blog);
        if (!isSuccess){
            return Result.fail("新增笔记失败");
        }
        //查询所有粉丝
        List follows = followService.query().eq("follow_user_id", user.getId()).list();
        for (Follow follow : follows) {
            Long userId = follow.getUserId();
            String key = FEED_KEY + userId;
            stringRedisTemplate.opsForZSet().add(key,blog.getId().toString(),System.currentTimeMillis());

        }
        // 返回id
        return Result.ok(blog.getId());
    }

    @Override
    public Result queryBlogOfFollow(Long max, Integer offset) {
        Long userId = UserHolder.getUser().getId();
        String key = FEED_KEY + userId;
        Set> typedTuples = stringRedisTemplate.opsForZSet()
                .reverseRangeByScoreWithScores(key, 0, max, offset, 2);
        if (typedTuples==null||typedTuples.isEmpty()){
            return Result.ok();
        }
        ArrayList ids = new ArrayList<>(typedTuples.size());
        long minTime=0;
        int os=1;
        for (ZSetOperations.TypedTuple tuple : typedTuples) {
            String idStr = tuple.getValue();
            ids.add(Long.valueOf(idStr));
            long time = tuple.getScore().longValue();
            if (time==minTime){
                os++;
            }else {
                minTime = time;
                os=1;
            }

        }
        String idStr = StrUtil.join(",", ids);
        List blogs = query()
                .in("id",ids)
                .last("ORDER BY FIELD(id,"+idStr+")").list();
        for (Blog blog : blogs) {
            queryBlogUser(blog);

            isBlogLiked(blog);

        }

        ScrollResult r = new ScrollResult();
        r.setList(blogs);
        r.setOffset(os);
        r.setMinTime(minTime);
        return Result.ok(r);
    }
}

2.5关注模块

package com.hmdp.service.impl;

import cn.hutool.core.bean.BeanUtil;
import com.baomidou.mybatisplus.core.conditions.query.QueryWrapper;
import com.hmdp.dto.Result;
import com.hmdp.dto.UserDTO;
import com.hmdp.entity.Follow;
import com.hmdp.mapper.FollowMapper;
import com.hmdp.service.IFollowService;
import com.baomidou.mybatisplus.extension.service.impl.ServiceImpl;
import com.hmdp.service.IUserService;
import com.hmdp.utils.UserHolder;
import org.springframework.data.redis.core.StringRedisTemplate;
import org.springframework.stereotype.Service;

import javax.annotation.Resource;
import java.util.Collections;
import java.util.List;
import java.util.Set;
import java.util.stream.Collectors;

/**
 * 

 *  服务实现类
 * 
 *
 * @author 青云
 * @since 2021-12-22
 */
@Service
public class FollowServiceImpl extends ServiceImpl implements IFollowService {

    @Resource
    private StringRedisTemplate stringRedisTemplate;

    @Resource
    private IUserService userService;
    @Override
    public Result follow(Long followUserId, Boolean isFollow) {
        Long userId = UserHolder.getUser().getId();
        String key = "follows" + userId;

        if (isFollow){
            Follow follow=new Follow();
            follow.setFollowUserId(followUserId);
            follow.setUserId(userId);
            boolean isSuccess = save(follow);
            if (isSuccess){
                stringRedisTemplate.opsForSet().add(key,followUserId.toString());
            }
        }else {
            boolean isSuccess = remove(new QueryWrapper()
                    .eq("user_id", userId)
                    .eq("follow_user_id", followUserId)
            );
            if (isSuccess){
                stringRedisTemplate.opsForSet().remove(key,followUserId.toString());

            }
        }
        return Result.ok();
    }

    @Override
    public Result isFollow(Long followUserId) {
        Long userId = UserHolder.getUser().getId();
        Integer count = query().eq("user_id", userId)
                .eq("follow_user_id", followUserId)
                .count();
        return Result.ok(count>0);
    }

    @Override
    public Result followCommons(Long id) {
        Long userId = UserHolder.getUser().getId();
        String key = "follows" + userId;
        String key2 = "follows" + id;
        Set intersect = stringRedisTemplate.opsForSet().intersect(key, key2);
        if (intersect==null||intersect.isEmpty()){
            return Result.ok(Collections.emptyList());
        }
        List ids = intersect.stream().map(Long::valueOf).collect(Collectors.toList());
        List userDTOS = userService.listByIds(ids).stream()
                .map(user -> BeanUtil.copyProperties(user, UserDTO.class))
                .collect(Collectors.toList());
        return Result.ok(userDTOS);
    }
}

2.6订阅模块

用户发布的内容推送给粉丝，实现策略有三种模式：拉取模式，推模式，推拉结合模式

该处实现了推模式，发布博客时，把博客推送给粉丝，会向粉丝的信箱（ZSet：粉丝id，博客id，时间）中存入博客id，用户查看订阅时，即根据信箱滚动分页查询最新的博客

 @Override
    public Result queryBlogOfFollow(Long max, Integer offset) {
        Long userId = UserHolder.getUser().getId();
        String key = FEED_KEY + userId;
        Set> typedTuples = stringRedisTemplate.opsForZSet()
                .reverseRangeByScoreWithScores(key, 0, max, offset, 2);
        if (typedTuples==null||typedTuples.isEmpty()){
            return Result.ok();
        }
        ArrayList ids = new ArrayList<>(typedTuples.size());
        long minTime=0;
        int os=1;
        for (ZSetOperations.TypedTuple tuple : typedTuples) {
            String idStr = tuple.getValue();
            ids.add(Long.valueOf(idStr));
            long time = tuple.getScore().longValue();
            if (time==minTime){
                os++;
            }else {
                minTime = time;
                os=1;
            }

        }
        String idStr = StrUtil.join(",", ids);
        List blogs = query()
                .in("id",ids)
                .last("ORDER BY FIELD(id,"+idStr+")").list();
        for (Blog blog : blogs) {
            queryBlogUser(blog);

            isBlogLiked(blog);

        }

        ScrollResult r = new ScrollResult();
        r.setList(blogs);
        r.setOffset(os);
        r.setMinTime(minTime);
        return Result.ok(r);
    }

2.7签到模块

使用时间bitMap，打卡取1，为打卡取0，从第0位开始，n日的打卡数据在n-1位

把当月签到数据和1做与运算，得到最近一天是否打卡，为0则直接返回，为1则把签到数据右移一位和1做与运算，循环，直到与运算结果为0，循环次数为连续签到天数。

 @Override
    public Result sign() {
        Long userId = UserHolder.getUser().getId();
        LocalDateTime now = LocalDateTime.now();
        String keySuffix= now.format(DateTimeFormatter.ofPattern(":yyyyMM"));
        String key = USER_SIGN_KEY + userId + keySuffix;
        int dayOfMonth = now.getDayOfMonth();
        stringRedisTemplate.opsForValue().setBit(key,dayOfMonth-1,true);
        return Result.ok();
    }

    @Override
    public Result signCount() {
        Long userId = UserHolder.getUser().getId();
        LocalDateTime now = LocalDateTime.now();
        String keySuffix= now.format(DateTimeFormatter.ofPattern(":yyyyMM"));
        String key = USER_SIGN_KEY + userId + keySuffix;
        int dayOfMonth = now.getDayOfMonth();

        List result = stringRedisTemplate.opsForValue().bitField(key, BitFieldSubCommands.create()
                .get(BitFieldSubCommands.BitFieldType.unsigned(dayOfMonth))
                .valueAt(0)
        );
        if (result==null||result.isEmpty()){
            return Result.ok(0);
        }
        Long num = result.get(0);
        if (num==null||num==0){
            return  Result.ok(0);
        }
        int count=0;
        while (true){
            if ((num&1)==0){
                break;
            }else {
                count++;
            }
            num >>>=1;
        }
        return Result.ok(count);
    }

3.心得体会

黑马点评是一个非常适合我们学习的项目，尽管功能大部分是Redis实现，但是可以学到很多新知识，例如秒杀的各种情况如何解决等，希望经过以后的学习能轻松的独立写出类似项目