public void updateData(Data data) {  
    // 1. 更新數(shù)據(jù)庫  
    dataDao.update(data);  
    
    // 2. 首次刪除緩存  
    redis.del("data:" + data.getId());  
    
    // 3. 延遲二次刪除  
    executor.schedule(() -> {  
        redis.del("data:" + data.getId());  
    }, 500, TimeUnit.MILLISECONDS); // 根據(jù)主從延遲調(diào)整  
}  

# 寫入更新命令  
XADD data_ops * type update id 123 value 100  

# 消費者順序執(zhí)行  
XREAD BLOCK 0 STREAMS data_ops $  

canal.instance.master.address=127.0.0.1:3306  
canal.instance.dbUsername=canal  
canal.instance.dbPassword=canal  
canal.mq.topic=data_cache  

@GlobalTransactional  
public void updateData(Data data) {  
    dataDao.update(data); // 更新DB  
    redisTemplate.delete("data:" + data.getId()); // 刪緩存  
}  

public Data getData(long id) {  
    String cacheKey = "data:" + id;  
    Data data = redis.get(cacheKey);  
    if (data == null) {  
        data = db.query("SELECT * FROM data WHERE id=?", id);  
        redis.set(cacheKey, data);  
    } else if (data.version < db.getVersion(id)) {  
        // 版本落后則刷新  
        data = refreshFromDb(id);  
    }  
    return data;  
}  

// 帶重試的刪除  
void deleteWithRetry(String key, int maxRetries) {  
    int retry = 0;  
    while (retry < maxRetries) {  
        if (redis.del(key) == 1) break;  
        Thread.sleep(100);  
        retry++;  
    }  
    if (retry == maxRetries) {  
        mq.send("cache_clean", key); // 投遞消息隊列  
    }  
}  

延遲雙刪的等待時間 > 主從延遲最大值  

// 偽代碼:標(biāo)準(zhǔn)操作順序  
void updateData(Data data) {  
    1. db.update(data);  
    2. redis.delete(key);  
    3. // 可選:延遲二次刪除  
}  

# 緩存不一致率 = (緩存錯誤數(shù) / 總請求數(shù))  
redis-cli info | grep keyspace_misses  
mysql> SHOW STATUS LIKE 'Innodb_rows_read';