Discretising intra-day data -- how to get by with less memory?

Ajay Shah wrote:

I'm using this function to convert intra-day data into a grid with an
observation each N seconds:

  # This function consumes "z" a zoo object where timestamps are 
intraday
  # and a period for discretisation Nseconds.
  # The key ideas are from this thread:
  #    https://stat.ethz.ch/pipermail/r-sig-finance/2009q4/005144.html
  intraday.discretise <- function(z, Nseconds) {
    toNsec <- function(x) 
as.POSIXct(Nseconds*ceiling(as.numeric(x)/Nseconds),
                                   origin = "1970-01-01")
    d <- aggregate(z, toNsec, tail, 1)
    # At this point there is one problem: NA records are not created
    # for blocks of time in which there were no records.

    # To solve this:
    dreg <- as.zoo(as.ts(d))
    class(time(dreg)) <- class(time(d))

    dreg
  }

This works correctly but it's incredibly memory-intensive. I'm running
out of core in running this for some problems.

Is there a way to write this which would use less RAM?

  

Jeff Ryan, Abe Winter, and I came up with an align.time function a few 
months back:

align.time <- function(x, n=30) {
 structure(unclass(x) + (n - unclass(x) %% n), 
class=c("POSIXt","POSIXct")) }

x is xts data
n is seconds

Regards,

 - Brian