cache {bit64}R Documentation

Atomic Caching

Description

Functions for caching results attached to atomic objects

Usage

newcache(x)

jamcache(x)

cache(x)

setcache(x, which, value)

getcache(x, which)

remcache(x)

## S3 method for class 'cache'
print(x, all.names = FALSE, pattern, ...)

Arguments

x

an integer64 vector (or a cache object in case of print.cache)

which

A character naming the object to be retrieved from the cache or to be stored in the cache

value

An object to be stored in the cache

all.names, pattern

passed to ls() when listing the cache content

...

ignored

Details

A cache is an environment attached to an atomic object with the attribute name 'cache'. It contains at least a reference to the atomic object that carries the cache. This is used when accessing the cache to detect whether the object carrying the cache has been modified meanwhile.

Value

See details

Functions

See Also

bit::still.identical() for testing whether to symbols point to the same RAM.

Functions that get and set small cache-content automatically when a cache is present: bit::na.count(), bit::nvalid(), bit::is.sorted(), bit::nunique() and bit::nties()

Setting big caches with a relevant memory footprint requires a conscious decision of the user: hashcache, sortcache, ordercache, sortordercache

Functions that use big caches: match.integer64(), %in%.integer64, duplicated.integer64(), unique.integer64(), unipos(), table.integer64(), keypos(), tiepos(), rank.integer64(), prank(), qtile(), quantile.integer64(), median.integer64(), and summary.integer64()

Examples

  x <- as.integer64(sample(c(rep(NA, 9), 1:9), 32, TRUE))
  y <- x
  still.identical(x,y)
  y[1] <- NA
  still.identical(x,y)
  mycache <- newcache(x)
  ls(mycache)
  mycache
  rm(mycache)
  jamcache(x)
  cache(x)
  x[1] <- NA
  cache(x)
  getcache(x, "abc")
  setcache(x, "abc", 1)
  getcache(x, "abc")
  remcache(x)
  cache(x)

[Package bit64 version 4.6.0-1 Index]