@prsm/cache

Distributed read-through cache for Redis. Single-flight loader execution across instances, stale-while-revalidate, tag-based invalidation, negative and error caching.

Install

npm install @prsm/cache

The pattern

import { createCache } from '@prsm/cache'

const cache = createCache({
  redis: { host: '127.0.0.1', port: 6379 },
  defaultTtl: '5m',
})

const user = await cache.fetch(`user:${id}`, async () => {
  return await db.users.findById(id)
}, { ttl: '5m' })

The loader is called only on a miss. When N instances race for the same missing key, only one of them runs the loader. The rest wait for the result and receive it from Redis pub/sub. Your database sees one query, not N.

Why not just use Redis directly?

The pattern most teams write looks correct but causes outages under load:

const cached = await redis.get(`user:${id}`)
if (cached) return JSON.parse(cached)
const user = await db.users.findById(id)
await redis.setex(`user:${id}`, 300, JSON.stringify(user))
return user

When a hot key expires and 800 concurrent requests arrive in the same millisecond, all 800 see a miss, all 800 call the database. The database melts. This is the cache stampede problem.

This package handles it by acquiring a per-key lock when a miss happens. The lock winner runs the loader, writes the value, and publishes the result. Everyone else waits on the pub/sub channel and receives the value when the leader finishes. One database query for N concurrent requests.

Stale-while-revalidate

When staleWhile is set, a key past its TTL but still within the stale window is served immediately while a background refresh runs. Requests never block on cache regeneration.

const trending = await cache.fetch('trending', loadTrending, {
  ttl: '1m',          // fresh window
  staleWhile: '10m',  // serve stale up to 10 minutes past TTL while refreshing
})

Tag-based invalidation

Keys can carry tags. Invalidating a tag wipes every key that was set with it.

await cache.set(`order:${id}`, order, {
  ttl: '1h',
  tags: [`user:${order.userId}`, `org:${order.orgId}`],
})

await cache.invalidateTag(`user:42`)  // removes every key tagged user:42

Negative and error caching

const profile = await cache.fetch(`profile:${id}`, loadProfile, {
  ttl: '10m',
  negativeTtl: '30s',  // cache nulls for 30s so missing-user lookups don't hit the DB forever
  errorTtl: '5s',      // briefly cache thrown errors so an outage doesn't cascade
})

undefined returns are never cached. null is cached using negativeTtl if it is set.

API

createCache(options)

const cache = createCache({
  redis: { host, port, password, db, url },  // or a node-redis client
  prefix: 'cache:',
  defaultTtl: '5m',
  defaultStaleWhile: 0,
  defaultNegativeTtl: null,
  defaultErrorTtl: 0,
  defaultLockTtl: '30s',
  waitTimeout: '10s',
  serialize: JSON.stringify,
  deserialize: JSON.parse,
})

cache.fetch(key, loader, options?)

Returns the cached value, or runs loader if missing. Options override defaults: ttl, staleWhile, negativeTtl, errorTtl, lockTtl, waitTimeout, tags.

cache.get(key)

Returns the value if the key is fresh, otherwise undefined. Does not call any loader.

cache.set(key, value, options?)

Writes a value directly. Options: ttl, staleWhile, tags.

cache.del(key)

Removes a key and its tag membership. Returns true if a key was removed.

cache.has(key)

Returns true if the key is fresh.

cache.invalidateTag(tag)

Removes every key associated with the tag. Returns the number of keys removed.

cache.stats()

Returns a snapshot of counters: hits, misses, sets, dels, errors, refreshes, stampedeLeads, stampedeWaits, stampedeSavings, invalidations.

cache.on(event, handler)

Events: hit, miss, set, del, invalidate, stampede:lead, stampede:wait, stampede:result, stampede:timeout, refresh, error.

cache.close()

Closes the underlying Redis connections.

Dev

make up      # start Redis
make test    # run tests
make down    # stop Redis

Redis must be running on localhost:6379 for tests.