@Test
    public void testGuavaWithBloomFilter()
    {
    // 创建布隆过滤器对象
        BloomFilter<Integer> filter = BloomFilter.create(Funnels.integerFunnel(), 100);
    // 判断指定元素是否存在
        System.out.println(filter.mightContain(1));
        System.out.println(filter.mightContain(2));
    // 将元素添加进布隆过滤器
        filter.put(1);
        filter.put(2);
        System.out.println(filter.mightContain(1));
        System.out.println(filter.mightContain(2));
    }

// 采用定时器将参与聚划算活动的特价商品新增进入redis
@Service
@Slf4j
public class JHSTaskService
{
    public  static final String JHS_KEY="jhs";
    public  static final String JHS_KEY_A="jhs:a";
    public  static final String JHS_KEY_B="jhs:b";
    @Autowired
    private RedisTemplate redisTemplate;
    /**
     * 偷个懒不加mybatis了，模拟从数据库读取100件特价商品，用于加载到聚划算的页面中
     * @return
     */
    private List<Product> getProductsFromMysql() {
        List<Product> list=new ArrayList<>();
        for (int i = 1; i <=20; i++) {
            Random rand = new Random();
            int id= rand.nextInt(10000);
            Product obj=new Product((long) id,"product"+i,i,"detail");
            list.add(obj);
        }
        return list;
    }
    @PostConstruct
    public void initJHS(){
        log.info("启动定时器淘宝聚划算功能模拟.........."+ DateUtil.now());
        new Thread(() -> {
            //模拟定时器一个后台任务，定时把数据库的特价商品，刷新到redis中
            while (true){
                //模拟从数据库读取100件特价商品，用于加载到聚划算的页面中
                List<Product> list=this.getProductsFromMysql();
                //采用redis list数据结构的lpush来实现存储
                this.redisTemplate.delete(JHS_KEY);
                //lpush命令
                this.redisTemplate.opsForList().leftPushAll(JHS_KEY,list);
                //间隔一分钟 执行一遍，模拟聚划算每3天刷新一批次参加活动
                try { TimeUnit.MINUTES.sleep(1); } catch (InterruptedException e) { e.printStackTrace(); }
                log.info("runJhs定时刷新..............");
            }
        },"t1").start();
    }
}

@RestController
@Slf4j
@Api(tags = "聚划算商品列表接口")
public class JHSProductController
{
    public  static final String JHS_KEY="jhs";
    public  static final String JHS_KEY_A="jhs:a";
    public  static final String JHS_KEY_B="jhs:b";
    @Autowired
    private RedisTemplate redisTemplate;
    /**
     * 分页查询：在高并发的情况下，只能走redis查询，走db的话必定会把db打垮
     * @param page
     * @param size
     * @return
     */
    @RequestMapping(value = "/pruduct/find",method = RequestMethod.GET)
    @ApiOperation("按照分页和每页显示容量，点击查看")
    public List<Product> find(int page, int size) {
        List<Product> list=null;
        long start = (page - 1) * size;
        long end = start + size - 1;
        try {
            //采用redis list数据结构的lrange命令实现分页查询
            list = this.redisTemplate.opsForList().range(JHS_KEY, start, end);
            if (CollectionUtils.isEmpty(list)) {
                //TODO 走DB查询
            }
            log.info("查询结果：{}", list);
        } catch (Exception ex) {
            //这里的异常，一般是redis瘫痪 ，或 redis网络timeout
            log.error("exception:", ex);
            //TODO 走DB查询
        }
        return list;
    }
    @RequestMapping(value = "/pruduct/findab",method = RequestMethod.GET)
    @ApiOperation("防止热点key突然失效，AB双缓存架构")
    public List<Product> findAB(int page, int size) {
        List<Product> list=null;
        long start = (page - 1) * size;
        long end = start + size - 1;
        try {
            //采用redis list数据结构的lrange命令实现分页查询
            list = this.redisTemplate.opsForList().range(JHS_KEY_A, start, end);
            if (CollectionUtils.isEmpty(list)) {
                log.info("=========A缓存已经失效了，记得人工修补，B缓存自动延续5天");
                //用户先查询缓存A(上面的代码)，如果缓存A查询不到（例如，更新缓存的时候删除了），再查询缓存B
                this.redisTemplate.opsForList().range(JHS_KEY_B, start, end);
                //TODO 走DB查询
            }
            log.info("查询结果：{}", list);
        } catch (Exception ex) {
            //这里的异常，一般是redis瘫痪 ，或 redis网络timeout
            log.error("exception:", ex);
            //TODO 走DB查询
        }
        return list;
    }
}