Redis PatternsSAFE

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---
name: redis-patterns
description: Redisデータ構造パターン、キャッシング戦略、分散ロック、レート制限、Pub/Sub、本番アプリケーション用コネクション管理。
origin: ECC
---

# Redis Patterns

一般的なバックエンド使用例に対するRedisベストプラクティスの参考資料。

## How It Works

Redisはメモリ内データ構造ストアで、文字列、ハッシュ、リスト、セット、ソート済みセット、ストリームなどをサポートします。単一インスタンスでは個々のRedisコマンドは原子的ですが、マルチステップワークフローはLuaスクリプト、MULTI/EXECトランザクション、または明示的な同期化が必要です。RDBスナップショットまたはAOFログを通じてデータをオプションで永続化します。クライアントはRESPプロトコルを使用してTCP経由で通信します。接続プール不可欠でリクエストごとのハンドシェイクオーバーヘッドを回避します。

## When to Activate

- アプリケーションにキャッシング追加
- レート制限またはスロットリング実装
- 分散ロックまたはコーディネーション構築
- セッションまたはトークンストレージ設定
- Pub/SubまたはRedis Streams for messaging使用
- 本番環境でRedis設定(プール、削除、クラスタリング)

## Data Structure Cheat Sheet

| Use Case | Structure | Example Key |
|----------|-----------|-------------|
| Simple cache | String | `product:123` |
| User session | Hash | `session:abc` |
| Leaderboard | Sorted Set | `scores:weekly` |
| Unique visitors | Set | `visitors:2024-01-01` |
| Activity feed | List | `feed:user:456` |
| Event stream | Stream | `events:orders` |
| Counters / rate limits | String (INCR) | `ratelimit:user:123` |
| Bloom filter / HLL | HyperLogLog | `hll:pageviews` |

## Core Patterns

### Cache-Aside (Lazy Loading)

```python
import redis
import json

r = redis.Redis(host='localhost', port=6379, decode_responses=True)

def get_product(product_id: int):
    cache_key = f"product:{product_id}"
    cached = r.get(cache_key)

    if cached:
        return json.loads(cached)

    product = db.query("SELECT * FROM products WHERE id = %s", product_id)
    r.setex(cache_key, 3600, json.dumps(product))  # TTL: 1 hour
    return product
```

### Write-Through Cache

```python
def update_product(product_id: int, data: dict):
    # DB書き込み先
    db.execute("UPDATE products SET ... WHERE id = %s", product_id)

    # キャッシュを即座に更新
    cache_key = f"product:{product_id}"
    r.setex(cache_key, 3600, json.dumps(data))
```

### Cache Invalidation

```python
# タグベース削除 — セット内で関連キーをグループ化
def cache_product(product_id: int, category_id: int, data: dict):
    key = f"product:{product_id}"
    tag = f"tag:category:{category_id}"
    pipe = r.pipeline(transaction=True)
    pipe.setex(key, 3600, json.dumps(data))
    pipe.sadd(tag, key)
    pipe.expire(tag, 3600)
    pipe.execute()

def invalidate_category(category_id: int):
    tag = f"tag:category:{category_id}"
    keys = r.smembers(tag)
    if keys:
        r.delete(*keys)
    r.delete(tag)
```

### Session Storage

```python
import time
import uuid

def create_session(user_id: int, ttl: int = 86400) -> str:
    session_id = str(uuid.uuid4())
    key = f"session:{session_id}"
    pipe = r.pipeline(transaction=True)
    pipe.hset(key, mapping={
        "user_id": user_id,
        "created_at": int(time.time()),
    })
    pipe.expire(key, ttl)
    pipe.execute()
    return session_id

def get_session(session_id: str) -> dict | None:
    data = r.hgetall(f"session:{session_id}")
    return data if data else None

def delete_session(session_id: str):
    r.delete(f"session:{session_id}")
```

## Rate Limiting

### Fixed Window (Simple)

```python
def is_rate_limited(user_id: int, limit: int = 100, window: int = 60) -> bool:
    key = f"ratelimit:{user_id}:{int(time.time()) // window}"
    pipe = r.pipeline(transaction=True)
    pipe.incr(key)
    pipe.expire(key, window)
    count, _ = pipe.execute()
    return count > limit
```

### Sliding Window (Lua — Atomic)

```lua
-- sliding_window.lua
local key = KEYS[1]
local now = tonumber(ARGV[1])
local window = tonumber(ARGV[2])
local limit = tonumber(ARGV[3])

redis.call('ZREMRANGEBYSCORE', key, 0, now - window)
local count = redis.call('ZCARD', key)

if count < limit then
    -- Use unique member (now + sequence) to avoid collisions within the same millisecond
    local seq_key = key .. ':seq'
    local seq = redis.call('INCR', seq_key)
    redis.call('EXPIRE', seq_key, math.ceil(window / 1000))
    redis.call('ZADD', key, now, now .. '-' .. seq)
    redis.call('EXPIRE', key, math.ceil(window / 1000))
    return 1
end
return 0
```

```python
sliding_window = r.register_script(open('sliding_window.lua').read())

def allow_request(user_id: int) -> bool:
    key = f"ratelimit:sliding:{user_id}"
    now = int(time.time() * 1000)
    return bool(sliding_window(keys=[key], args=[now, 60000, 100]))
```

## Distributed Locks

### Distributed Lock (Single Node — SET NX PX)

```python
import uuid

def acquire_lock(resource: str, ttl_ms: int = 5000) -> str | None:
    lock_key = f"lock:{resource}"
    token = str(uuid.uuid4())
    acquired = r.set(lock_key, token, px=ttl_ms, nx=True)
    return token if acquired else None

def release_lock(resource: str, token: str) -> bool:
    release_script = """
    if redis.call('get', KEYS[1]) == ARGV[1] then
        return redis.call('del', KEYS[1])
    else
        return 0
    end
    """
    result = r.eval(release_script, 1, f"lock:{resource}", token)
    return bool(result)

# Usage
token = acquire_lock("order:payment:123")
if token:
    try:
        process_payment()
    finally:
        release_lock("order:payment:123", token)
```

> マルチノード設定の場合、フルRedlockアルゴリズムを実装する `redlock-py` ライブラリを使用してください。

## Pub/Sub & Streams

### Pub/Sub (Fire-and-Forget)

```python
# Publisher
def publish_event(channel: str, payload: dict):
    r.publish(channel, json.dumps(payload))

# Subscriber (blocking — run in separate thread/process)
def subscribe_events(channel: str):
    pubsub = r.pubsub()
    pubsub.subscribe(channel)
    for message in pubsub.listen():
        if message['type'] == 'message':
            handle(json.loads(message['data']))
```

### Redis Streams (Durable Queue)

```python
# Producer
def emit(stream: str, event: dict):
    r.xadd(stream, event, maxlen=10000)  # Cap stream length

# Consumer group — guarantees at-least-once delivery
try:
    r.xgroup_create('events:orders', 'processor', id='0', mkstream=True)
except Exception:
    pass  # Group already exists

def consume(stream: str, group: str, consumer: str):
    while True:
    

SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.

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