The archivist package allows to store, restore and look for R objects in repositories stored on hard disk. There are different strategies that can be used to find an object, through it’s name, date of creation of meta data. The package is mainly designed as a repository of artifacts, but it can be used in different use-cases.

Let’s see how it can be used as caching engine.

Let’s consider a function with few arguments, which evaluation may takes a significant amount of time. If there is a chance that the function will be executed with same parameteres more than just one, it would be desireble to cache results to avoid unncessary evaluations.

Such cache can be easily constructed with the archivist package.

Heavyweight function

Let’s see an example. The Heavyweight function getMaxDistribution summarizes the distribution of maximum from N draw of random variables from distribuition D with the use of R replications.

getMaxDistribution <- function(
    D = rnorm, 
    N = 10,
    R = 1000000) {
    res <- replicate(R, max(D(N)))

system.time(getMaxDistribution(rnorm, 10))
   user  system elapsed 
  5.477   0.035   5.511 
system.time(getMaxDistribution(rexp, 20))
   user  system elapsed 
  5.156   0.008   5.164 
system.time(getMaxDistribution(rnorm, 10))
   user  system elapsed 
  4.845   0.001   4.844 

Now, let’s load the archivist package and prepare a repository for cached objects.

Cache preparation

cacheRepo <- tempfile()
Directory /tmp/Rtmp45GZsm/file65d3676f9387 did not exist. Forced to create a new directory.

How to work with cache

The cacheRepo is a folder with already evaluated function calls. How to use it?

system.time(cache(cacheRepo, getMaxDistribution, rnorm, 10))
   user  system elapsed 
  4.738   0.004   4.740 
system.time(cache(cacheRepo, getMaxDistribution, rexp, 10))
   user  system elapsed 
  4.950   0.008   4.955 
system.time(cache(cacheRepo, getMaxDistribution, rnorm, 10))
   user  system elapsed 
  0.003   0.000   0.003 

The second evaluation of getMaxDistribution is much, much faster. Results are just read from disk.

How the cache function works?

It create a md5 signature of the function FUN and it’s arguments and use this signature as a key. If such key is present in the cache repository, then the object is just restored. If it’s not present then the call is evaluated and result is stored. Note that, if cacheRepo is a shared folder, then you get a shared cache repository!