53e0065e3e
配置 SSOT（TOML + .env） 统一错误契约 Auth 与事务边界 Redis / Celery 可靠性:业务 Redis（DB/0）与 Celery broker/backend（DB/1）显式拆分；连接池、sync client 可观测性（OpenTelemetry + LGTM）
76 lines
2.0 KiB
Markdown
76 lines
2.0 KiB
Markdown
---
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title: Avoid Slow Commands in Production
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impact: HIGH
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impactDescription: Prevents Redis from becoming unresponsive
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tags: slow-commands, keys, scan, performance
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description: Avoid Slow Commands in Production
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alwaysApply: true
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---
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## Avoid Slow Commands in Production
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Some Redis commands are slow because they scan large datasets. Use incremental alternatives to avoid blocking the server.
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| Avoid | Use Instead |
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|-------|-------------|
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| `KEYS *` | `SCAN` with cursor |
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| `SMEMBERS` on large sets | `SSCAN` |
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| `HGETALL` on large hashes | `HSCAN` |
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| `LRANGE 0 -1` on large lists | Paginate with `LRANGE 0 100` |
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**Correct:** Use SCAN for iteration.
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**Python** (redis-py):
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```python
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# Good: Non-blocking iteration
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cursor = 0
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while True:
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cursor, keys = redis.scan(cursor, match="user:*", count=100)
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for key in keys:
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process(key)
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if cursor == 0:
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break
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```
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**Java** (Jedis):
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```java
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import redis.clients.jedis.ScanIteration;
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import redis.clients.jedis.UnifiedJedis;
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import java.util.List;
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try (UnifiedJedis jedis = new UnifiedJedis("redis://localhost:6379")) {
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// ScanIteration manages the cursor automatically
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ScanIteration scan = jedis.scanIteration(10, "user:*", "hash");
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while (!scan.isIterationCompleted()) {
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List<String> result = scan.nextBatch().getResult();
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for (String key : result) {
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process(key);
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}
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}
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}
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```
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**Incorrect:** Using KEYS in production.
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**Python** (redis-py):
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```python
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# Bad: Scans all keys, slow on large datasets
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keys = redis.keys("user:*")
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```
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**Java** (Jedis):
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```java
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// Bad: Scans all keys, blocks the server
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Set<String> result = jedis.keys("*");
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```
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**Note:** Truly blocking commands (like `BLPOP`, `BRPOP`, `BLMOVE`) that wait indefinitely for data are appropriate for some use cases like job queues, but should be used with timeouts.
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```python
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# Blocking pop with timeout - appropriate for queue consumers
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result = redis.blpop("task_queue", timeout=5)
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```
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Reference: [Redis SCAN](https://redis.io/docs/latest/commands/scan/)
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