CODEWITHSUNDEEP
scalacaching
Jeriho
Jeriho

Reputation: 7309

How to cache results in scala?

This page has a description of Map's getOrElseUpdate usage method:

object WithCache{
  val cacheFun1 = collection.mutable.Map[Int, Int]()
  def fun1(i:Int) = i*i
  def catchedFun1(i:Int) = cacheFun1.getOrElseUpdate(i, fun1(i))
}

So you can use catchedFun1 which will check if cacheFun1 contains key and return value associated with it. Otherwise, it will invoke fun1, then cache fun1's result in cacheFun1, then return fun1's result.

I can see one potential danger - cacheFun1 can became to large. So cacheFun1 must be cleaned somehow by garbage collector?

P.S. What about scala.collection.mutable.WeakHashMap and java.lang.ref.* ?

Upvotes: 22

Views: 28690

Answers (6)

skjagini
skjagini

Reputation: 3217

We are using Scaffeine (Scala + Caffeine), and you can read abouts its pros/cons compared to other frameworks over here.

You add your sbt,

"com.github.blemale" %% "scaffeine" % "4.0.1"

Build your cache

import com.github.blemale.scaffeine.{Cache, Scaffeine}
import scala.concurrent.duration._

val cachedItems: Cache[String, Int] = 
  Scaffeine()
    .recordStats()
    .expireAtferWrite(60.seconds)
    .maximumSize(500)
    .build[String, Int]()

cachedItems.put("key", 1) // Add items

cache.getIfPresent("key") // Returns an option

Upvotes: 3

Johnny
Johnny

Reputation: 15423

For simple caching needs, I'm still using Guava cache solution in Scala as well. Lightweight and battle tested.

If it fit's your requirements and constraints generally outlined below, it could be a great option:

  • Willing to spend some memory to improve speed.
  • Expecting that keys will sometimes get queried more than once.
  • Your cache will not need to store more data than what would fit in RAM. (Guava caches are local to a single run of your application. They do not store data in files, or on outside servers.)

Example for using it will be something like this:

  lazy val cachedData = CacheBuilder.newBuilder()
    .expireAfterWrite(60, TimeUnit.MINUTES)
    .maximumSize(10)
    .build(
      new CacheLoader[Key, Data] {
        def load(key: Key): Data = {
          veryExpansiveDataCreation(key)
        }
      }
    )

To read from it, you can use something like:

  def cachedData(ketToData: Key): Data = {
    try {
      return cachedData.get(ketToData)
    } catch {
      case ee: Exception => throw new YourSpecialException(ee.getMessage);
    }
  }

Upvotes: 4

oluies
oluies

Reputation: 17831

See the Memo pattern and the Scalaz implementation of said paper.

Also check out a STM implementation such as Akka.

Not that this is only local caching so you might want to lookinto a distributed cache or STM such as CCSTM, Terracotta or Hazelcast

Upvotes: 15

Nimrod007
Nimrod007

Reputation: 9913

Take a look at spray caching (super simple to use)

http://spray.io/documentation/1.1-SNAPSHOT/spray-caching/

makes the job easy and has some nice features

for example :

      import spray.caching.{LruCache, Cache}

      //this is using Play for a controller example getting something from a user and caching it
      object CacheExampleWithPlay extends Controller{

        //this will actually create a ExpiringLruCache and hold data for 48 hours
        val myCache: Cache[String] = LruCache(timeToLive = new FiniteDuration(48, HOURS))

        def putSomeThingInTheCache(@PathParam("getSomeThing") someThing: String) = Action {
          //put received data from the user in the cache
          myCache(someThing, () => future(someThing))
          Ok(someThing)
        }

        def checkIfSomeThingInTheCache(@PathParam("checkSomeThing") someThing: String) = Action {
          if (myCache.get(someThing).isDefined)
            Ok(s"just $someThing found this in the cache")
          else
            NotFound(s"$someThing NOT found this in the cache")
        }
      }

Upvotes: 7

dimitrisli
dimitrisli

Reputation: 21411

Since it hasn't been mentioned before let me put on the table the light Spray-Caching that can be used independently from Spray and provides expected size, time-to-live, time-to-idle eviction strategies.

Upvotes: 1

Debilski
Debilski

Reputation: 67888

On the scala mailing list they sometimes point to the MapMaker in the Google collections library. You might want to have a look at that.

Upvotes: 6

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