sort.integer64: High-level intger64 methods for sorting and ordering
In truecluster/bit64: A S3 Class for Vectors of 64bit Integers

Description Usage Arguments Details Value Author(s) See Also Examples

Fast high-level methods for sorting and ordering. These are wrappers to ramsort and friends and do not modify their arguments.

## S3 method for class 'integer64'
sort(x, decreasing = FALSE, has.na = TRUE, na.last = TRUE, stable = TRUE
, optimize = c("time", "memory"), VERBOSE = FALSE, ...)
## S3 method for class 'integer64'
order(..., na.last = TRUE, decreasing = FALSE, has.na = TRUE, stable = TRUE
, optimize = c("time", "memory"), VERBOSE = FALSE)

`x`	a vector to be sorted by `ramsort` and `ramsortorder`, i.e. the output of `sort`
`has.na`	boolean scalar defining whether the input vector might contain `NA`s. If we know we don't have NAs, this may speed-up. Note that you risk a crash if there are unexpected `NA`s with `has.na=FALSE`
`na.last`	boolean scalar telling ramsort whether to sort `NA`s last or first. Note that 'boolean' means that there is no third option `NA` as in `sort`
`decreasing`	boolean scalar telling ramsort whether to sort increasing or decreasing
`stable`	boolean scalar defining whether stable sorting is needed. Allowing non-stable may speed-up.
`optimize`	by default ramsort optimizes for 'time' which requires more RAM, set to 'memory' to minimize RAM requirements and sacrifice speed
`VERBOSE`	cat some info about chosen method
`...`	further arguments, passed from generics, ignored in methods

see sort and order

sort returns the sorted vector and vector returns the order positions.

Jens Oehlschlägel <Jens.Oehlschlaegel@truecluster.com>

sort, sortcache

  x <- as.integer64(sample(c(rep(NA, 9), 1:9), 32, TRUE))
  x
  sort(x)
  message("the following has default optimize='time' which is faster but requires more RAM
, this calls 'ramorder'")
  order.integer64(x)
  message("slower with less RAM, this calls 'ramsortorder'")
  order.integer64(x, optimize="memory")