scalacache memoization asynchronous refresh

Question

I'd like to do a TTL based memoization with active refresh asynchronously in scala.

ScalaCache example in the documentation allows for TTL based memoization as follows:

import scalacache._
import memoization._

implicit val scalaCache = ScalaCache(new MyCache())

def getUser(id: Int): User = memoize(60 seconds) {
  // Do DB lookup here...
  User(id, s"user${id}")
}

Curious whether the DB lookup gets triggered after TTL expires for existing value, synchronously and lazily during the next getUser invocation, or if the refresh happens aggressively and asynchronously - even before the next getUser call.

If the ScalaCache implementation is synchronous, is there an alternate library that provides ability to refresh cache actively and asynchronously ?

Answer 1

Expiration and refresh are closely related but different mechanisms. An expired entry is considered stale and cannot be used, so it must be discarded and refetched. An entry eligible for being refreshed means that the content is still valid to use, but the data should be refetched as it may be out of date. Guava provides these TTL policies under the names expireAfterWrite and refreshAfterWrite, which may be used together if the refresh time is smaller than the expiration time.

The design of most caches prefer discarding unused content. An active refresh would require a dedicated thread that reloads entries regardless of whether they have been used. Therefore most caching libraries do not provide active refresh themselves, but make it easy for applications to add that customization on top.

When a read in Guava detects that the entry is eligible for refresh, that caller will perform the operation. All subsequent reads while the refresh is in progress will obtain the current value. This means that to the refresh is performed synchronously on the user's thread that triggered it, and asynchronously to other threads reading that value. A refresh may be fully asynchronous if CacheLoader.reload is overridden to perform the work on an executor.

Caffeine is a rewrite of Guava's cache and differs slightly by always performing the refresh asynchronously to a user's thread. The cache delegates the operation to an executor, by default ForkJoinPool.commonPool which is a JVM-wide executor. The Policy api provides means of inspecting the runtime state of the cache, such as the age of an entry, for adding application-specific custom behavior.

For other ScalaCache backends support is mixed. Ehcache has a RefreshAheadCache decorator that refreshes lazily using its own threadpool. Redis and memcached do not refresh as they are not aware of the system of record. LruMap has expiration support grafted on and does not have any refresh capabilities.