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Redis Best Practices | Skills Pool

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Redis Best Practices

Redis best practices for caching, data structures, and in-memory data architecture

baekenough17 星標2026年3月13日

職業: 資料庫管理員
分類: NoSQL 數據庫

技能內容

Caching Patterns

Cache-Aside (CRITICAL)

Read: check cache → miss → read DB → set cache
Write: update DB → invalidate cache
Best for read-heavy workloads

Write-Through

Write: update cache AND DB simultaneously
Ensures consistency
Higher write latency

Write-Behind

Write: update cache → async DB update
Lowest latency
Risk of data loss

Data Structures

String

Simple key-value: SET key value
Counters: INCR, DECR, INCRBY
Bit operations: SETBIT, BITCOUNT

Hash

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Redis Best Practices

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作者: baekenough
星標: 17
更新時間: 2026年3月13日
職業

本頁內容

01Caching Patterns

Object storage: HSET user:1 name "Alice"
Partial updates: HINCRBY user:1 visits 1
Memory efficient for small hashes

List

Queues: LPUSH, RPOP (FIFO)
Stacks: LPUSH, LPOP (LIFO)
Capped collections: LTRIM

Set

Unique collections: SADD, SMEMBERS
Intersections: SINTER
Random sampling: SRANDMEMBER

Sorted Set

Leaderboards: ZADD, ZRANGEBYSCORE
Rate limiting: ZADD timestamp
Priority queues

Stream

Event log: XADD, XREAD
Consumer groups: XGROUP, XACK
Pub/Sub with persistence

Performance

Memory Optimization

Set maxmemory policy: allkeys-lru, volatile-lru
Monitor memory: INFO memory
Use appropriate data structures (Hash vs String)

Pipelining

Batch multiple commands
Reduces round-trip latency
Use for bulk operations

High Availability

Redis Cluster

Horizontal scaling
Automatic sharding (16384 slots)
Multi-master replication

Redis Sentinel

Automatic failover
Monitoring and notifications
Configuration provider

References

Redis Best Practices

02

Cache-Aside (CRITICAL)

03Write-Through

05Data Structures

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