[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"public:announcements":3,"public:navigations:zh":4,"footer:categories:zh":56,"post:detail:post-8-Redis缓存设计:zh":177},[],[5,18,25,33,41,49],{"id":6,"title":7,"url":12,"icon":13,"parent_id":13,"location":14,"order":6,"is_active":15,"target_blank":16,"created_at":17,"updated_at":13},1,{"zh":8,"en":9,"ja":10,"zh_TW":11},"首页","Home","ホーム","首頁","\u002F",null,"header",true,false,"2026-09-30T18:09:54.251095Z",{"id":19,"title":20,"url":24,"icon":13,"parent_id":13,"location":14,"order":19,"is_active":15,"target_blank":16,"created_at":17,"updated_at":13},2,{"zh":21,"en":22,"ja":23,"zh_TW":21},"文章","Posts","記事","\u002Fposts",{"id":26,"title":27,"url":32,"icon":13,"parent_id":13,"location":14,"order":26,"is_active":15,"target_blank":16,"created_at":17,"updated_at":13},3,{"zh":28,"en":29,"ja":30,"zh_TW":31},"分类","Categories","カテゴリー","分類","\u002Fcategories",{"id":34,"title":35,"url":40,"icon":13,"parent_id":13,"location":14,"order":34,"is_active":15,"target_blank":16,"created_at":17,"updated_at":13},4,{"zh":36,"en":37,"ja":38,"zh_TW":39},"标签","Tags","タグ","標籤","\u002Ftags",{"id":42,"title":43,"url":48,"icon":13,"parent_id":13,"location":14,"order":42,"is_active":15,"target_blank":16,"created_at":17,"updated_at":13},5,{"zh":44,"en":45,"ja":46,"zh_TW":47},"关于","About","概要","關於","\u002Fpage\u002Fabout",{"id":50,"title":51,"url":55,"icon":13,"parent_id":13,"location":14,"order":50,"is_active":15,"target_blank":16,"created_at":17,"updated_at":13},6,{"zh":52,"en":53,"ja":54,"zh_TW":52},"留言板","Guestbook","ゲストブック","\u002Fpage\u002Fguestbook",[57,73,87,102,117,133,148,162],{"id":6,"name":58,"slug":63,"description":64,"icon":69,"color":70,"cover_image":13,"created_at":71,"post_count":72},{"en":59,"ja":60,"zh":61,"zh_Hant":62},"Technology","テクノロジー","技术","技術","technology",{"en":65,"ja":66,"zh":67,"zh_Hant":68},"Cutting-edge 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redis.Redis(host=\"localhost\", port=6379, db=0, decode_responses=True)\n\ndef cache_aside(ttl: int = 300, jitter: float = 0.1):\n    def decorator(fn: Callable):\n        @wraps(fn)\n        def wrapper(*args, **kwargs):\n            k = f\"c:{fn.__name__}:{hashlib.md5(str((args,sorted(kwargs.items()))).encode()).hexdigest()[:10]}\"\n            cached = r.get(k)\n            if cached == \"__NULL__\": return None\n            if cached is not None: return json.loads(cached)\n            result = fn(*args, **kwargs)\n            t = int(ttl * (1 + random.uniform(-jitter, jitter)))\n            if result is None: r.setex(k, max(30, t\u002F\u002F5), \"__NULL__\")\n            else: r.setex(k, max(1, t), json.dumps(result, default=str))\n            return result\n        return wrapper\n    return decorator\n\ndef write_through(key: str, value: Any, db_update: Callable, ttl: int = 300):\n    pipe = r.pipeline()\n    pipe.setex(key, ttl, json.dumps(value, default=str))\n    try:\n        db_update(value)\n        pipe.execute()\n    except Exception:\n        pipe.reset(); raise\n\nbg_queue: list[tuple[str, Any]] = []\ndef write_behind(key: str, value: Any):\n    bg_queue.append((key, value))\n    r.setex(key, 60, json.dumps(value, default=str))\n\ndef flush_bg(db_update: Callable):\n    while bg_queue:\n        k, v = bg_queue.pop(0)\n        try: db_update(k, v)\n        except Exception: bg_queue.insert(0, (k, v)); break\n\n@cache_aside(ttl=600)\ndef get_product(pid: int):\n    return {\"id\": pid, \"name\": f\"Product {pid}\", \"price\": 99.99}\n```\n```\n\n## Write-Through \u002F Write-Behind\n\nWrite-Through 写缓存同时同步写 DB，原子性强但延迟高。Write-Behind 先写缓存，异步批量刷 DB，吞吐高但存在短窗口数据丢失风险。\n\n| 模式 | 一致性 | 读性能 | 写性能 | 适用场景 |\n|------|--------|--------|--------|---------|\n| Cache-Aside | 最终一致 | 高 | 中 | 读多写少 |\n| Write-Through | 强一致 | 高 | 低延迟差 | 一致性要求高 |\n| Write-Behind | 弱一致\u002F最终 | 高 | 极高 | 日志\u002F统计写多读少 |\n| Refresh-Ahead | 最终一致 | 极高 | 中 | 热点Key可预测 |\n\n## 最佳实践\n\n设置随机 TTL ±10% 防止雪崩，热点 Key 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