Implementing Caching Logic

1. Implementing Cache-Aside Pattern

Example: Read-through

public User get(long id) {
    var cached = cache.get(id);
    if (cached != null) return cached;
    var user = repo.findById(id).orElseThrow();
    cache.put(id, user);
    return user;
}

2. Implementing Write-Through Cache

Aspect	Detail
Write	To cache and DB synchronously
Read	From cache (always fresh)
Pro	Strong consistency
Con	Write latency higher

3. Implementing Write-Behind Cache

Aspect	Detail
Write	To cache; async to DB
Pro	Low write latency, batching
Con	Data loss risk on crash
Use	Metrics, analytics, non-critical

4. Implementing Cache Invalidation Logic

Strategy	Detail
TTL	Time-based; eventual consistency
Explicit on write	Evict matching keys
Event-driven	Invalidate on domain event
Versioned key	Bump version on data change

Warning: Cache invalidation is one of the two hard problems in CS — design for staleness tolerance.

5. Implementing In-Memory Caching

Example: Caffeine

Cache<Long, User> cache = Caffeine.newBuilder()
    .maximumSize(10_000)
    .expireAfterWrite(Duration.ofMinutes(10))
    .recordStats()
    .build();
User u = cache.get(id, repo::findById);

6. Implementing Distributed Caching

System	Trait
Redis	Single-master + replicas; rich types
Memcached	Simple key/value; multi-threaded
Hazelcast	Embedded, JVM
Apache Ignite	Compute + cache

7. Implementing Cache Hierarchies

Request → L1 (in-memory, <1ms) → miss → L2 (Redis, ~1-5ms) → miss → DB
                                  ↑                              ↓
                            backfill on miss ← - - - - - - - - - ┘

8. Implementing Cache Warming

Trigger	Detail
App startup	Load hot keys
Scheduled job	Refresh popular content
Event-driven	Pre-load on related event
Predictive	ML-based prefetch

9. Designing Cache Key Generation

Practice	Detail
Namespace prefix	`user:123`
Include version	`v2:user:123` for migrations
Tenant scope	`tenant:42:user:123`
Avoid PII	Hash sensitive parts
Hash long keys	SHA-256 if > 250 chars

10. Handling Cache Stampede

Technique	Detail
Single-flight	Coalesce concurrent loads (Caffeine does this)
Probabilistic early expire	Refresh slightly before TTL
Mutex/lock per key	Only one loader allowed
Stale-while-revalidate	Serve stale, refresh async

11. Using Cache Annotations

Example: Spring Cache

@Cacheable(value = "users", key = "#id")
public User get(long id) { return repo.findById(id).orElseThrow(); }

@CachePut(value = "users", key = "#u.id")
public User update(User u) { return repo.save(u); }

@CacheEvict(value = "users", key = "#id")
public void delete(long id) { repo.deleteById(id); }

12. Implementing Cache Metrics

Metric	What to Track
Hit ratio	hits / (hits + misses)
Eviction rate	Capacity pressure
Load time p99	Slow miss path
Size	Memory usage
Stampede events	Concurrent loads coalesced

Related Cheat Sheets

Prisma

Implementing Caching Logic

1. Implementing Cache-Aside Pattern

Example: Read-through

2. Implementing Write-Through Cache

3. Implementing Write-Behind Cache

4. Implementing Cache Invalidation Logic

5. Implementing In-Memory Caching

Example: Caffeine

6. Implementing Distributed Caching

7. Implementing Cache Hierarchies

8. Implementing Cache Warming

9. Designing Cache Key Generation

10. Handling Cache Stampede

11. Using Cache Annotations

Example: Spring Cache

12. Implementing Cache Metrics

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