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27
Caching Written by Tanner Nelson

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Whether you’re creating a JSON API, building an iOS app, or even designing the circuitry of a CPU, you’ll eventually need a cache. Caches (pronounced cashes) are a method of speeding up slow processes and, without them, the Internet would be a terribly slow place. The philosophy behind caching is simple: store the result of a slow process so you only have to run it once. Some examples of slow processes you may encounter while building a web app are:

  • Large database queries.
  • Requests to external services, e.g., other APIs.
  • Complex computation, e.g., parsing a large document.

By caching the results of these slow processes, you can make your app feel snappier and more responsive.

Cache storage

As part of DatabaseKit, Vapor defines the protocol KeyedCache. This protocol creates a common interface for different cache storage methods. The protocol itself is quite simple; take a look:

public protocol KeyedCache {
  // 1
  func get<D>(_ key: String, as decodable: D.Type) 
    -> Future<D?> where D: Decodable

  // 2
  func set<E>(_ key: String, to encodable: E) 
    -> Future<Void> where E: Encodable

  // 3
  func remove(_ key: String) -> Future<Void>
}

Here’s what each method does:

  1. get(_:as:) fetches stored data from the cache for a given key. If no data exists for that key, it returns nil.
  2. set(_:to:) stores data in the cache at the supplied key. If a value existed previously, it’s replaced.
  3. remove(_:): Removes data, if any, from the cache at the supplied key.

Each method returns a Future since interaction with the cache may happen asynchronously.

Now that you understand the concept of caching and the KeyedCache protocol, it’s time to take a look at some of the actual caching implementations available with Vapor.

In-memory caches

Vapor comes with two memory-based caches: MemoryKeyedCache and DictionaryKeyedCache. These caches store their data in your program’s running memory. This makes both of these caches great for development and testing because they have no external dependencies. However, they may not be perfect for all uses as the storage is cleared when the application restarts and can’t be shared between multiple instances of your application. Most likely though, this memory volatility won’t affect a well thought out caching design.

Memory cache

The contents of a MemoryKeyedCache are shared across all your application’s event loops. This means once something is stored in the cache, all future requests will see that same item regardless of which event loop they are assigned to. This is great for testing and development because it simulates how an external cache would operate. However, MemoryKeyedCache storage is still process-local, meaning it can not be shared across multiple instances of your application when scaling horizontally.

Dictionary cache

The contents of a DictionaryKeyedCache are local to each event loop. This means that subsequent requests assigned to different event loops may see different cached data. Separate instances of your application may also cache different data. This behavior is fine for purely performance-based caching, such as caching the result of a slow query, where logic does not rely on the cache storage being synchronized. However, for uses like session storage, where cache data must be synchronized, DictionaryKeyedCache will not work.

Database caches

All DatabaseKit-based caches support using a configured database as your cache storage. This includes all of Vapor’s Fluent mappings (FluentPostgreSQL, FluentMySQL, etc.) and database drivers (PostgreSQL, MySQL, Redis, etc.).

Redis

Redis is an open-source, cache storage service. It’s used commonly as a cache database for web applications and is supported by most deployment services like Heroku. Redis databases are usually very easy to configure and they allow you to persist your cached data between application restarts and share the cache between multiple instances of your application. Redis is a great, fast and feature-rich alternative to in-memory caches and it only takes a little bit more work to configure.

Example: Pokédex

When building a web app, making requests to other APIs can introduce delays. If the API you’re communicating with is slow, it can make your API feel slow. Additionally, external APIs may enforce rate limits on the number of requests you can make to them in a given time period.

vapor xcode -y

Overview

This simple Pokédex API has two routes:

Normal request

A typical Vapor requests takes only a couple of milliseconds to respond, when working locally. In the screenshot that follows, you can see the GET /pokemon route has a total response time of about 40ms.

PokeAPI dependent request

In the screenshot below, you can see that the POST /pokemon route is 25x slower at around 1,500ms. This is because the pokeapi.co API can be slow to respond to the query.

Verifying the name

In Xcode, open PokeAPI.swift and look at verifyName(_:on:).

Creating a KeyedCache

The first task is to create a KeyedCache for the PokeAPI wrapper. In PokeAPI.swift, add a new property to store the cache below let client: Client:

let cache: KeyedCache
public init(client: Client, cache: KeyedCache) {
  self.client = client
  self.cache = cache
}
return try PokeAPI(
  client: container.make(),
  cache: container.make())
[ ERROR ] ServiceError.ambiguity: Please choose which KeyedCache you prefer, multiple are available: MemoryKeyedCache, DictionaryKeyedCache, DatabaseKeyedCache<ConfiguredDatabase<SQLiteDatabase>>. (Config.swift:72)
[ DEBUG ] Suggested fixes for ServiceError.ambiguity: `config.prefer(MemoryKeyedCache.self, for: KeyedCache.self)`. `config.prefer(DictionaryKeyedCache.self, for: KeyedCache.self)`. `config.prefer(DatabaseKeyedCache<ConfiguredDatabase<SQLiteDatabase>>.self, for: KeyedCache.self)`. (Logger+LogError.swift:20)
migrations.prepareCache(for: .sqlite)
config.prefer(SQLiteCache.self, for: KeyedCache.self)
{
    "error": true,
    "reason": "Invalid Pokemon Test."
}

Fetch and Store

Now that the PokeAPI wrapper has access to a working KeyedCache, you can use the cache to store responses from the pokeapi.co API and subsequently fetch them much more quickly.

public func verifyName(_ name: String, on worker: Worker) 
    -> Future<Bool> {
  // 1
  let key = name.lowercased()
  // 2
  return cache.get(key, as: Bool.self).flatMap { result in
    if let exists = result {
      // 3
      return worker.eventLoop.newSucceededFuture(result: exists)
    }

    // 4
    return self.fetchPokemon(named: name).flatMap { res in
      switch res.http.status.code {
      case 200..<300:
        // 5
        return self.cache.set(key, to: true).transform(to: true)
      case 404:
        return self.cache.set(key, to: false)
          .transform(to: false)
      default:
        let reason = 
          "Unexpected PokeAPI response: \(res.http.status)"
        throw Abort(.internalServerError, reason: reason)
      }
    }
  }
}

Where to go from here?

Caching is an important concept in Computer Science and understanding how to use it will help make your web applications feel fast and responsive. There are several methods for storing your cache data for web applications: in-memory, Fluent database, Redis and more. Each has distinct benefits over the other.

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