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Asked: 2026-06-08T20:42:20+00:00

I spotted the following behavior. Say I create the following multi-dimensional array: spam =

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I spotted the following behavior. Say I create the following multi-dimensional array:

spam = array(runif(96*48*60*360), dim = c(96,48,60,360))

It is quite predictable how much memory R should use for this, namely (96*48*60*360) * 4 bytes = 759.4 Mbyte. This is nicely confirmed using the lsos function (see this post):

> lsos()
         Type      Size PrettySize Rows Columns
spam    array 796262520   759.4 Mb   96      48
lsos function       776  776 bytes   NA      NA

R as a process however uses much more memory, roughly twice the size:

$ top | grep rsession
82:17628 hiemstra  20   0 1614m **1.5g** 8996 S  0.3 40.4   0:04.85 rsession

Why does R do this? I assume the extra reserved memory is allocated to make it more quickly accessible to R? Any thought’s?

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1 Answer

  1. Editorial Team

    Because the garbage collector has not run yet.
    So there’s a lot of garbage, probably generated during the creation of the big array, that has to be cleared.

    If you force a garbage collection by calling gc() function, you will see that the used memory will be pretty near to the size of your array:

    > memory.size()
[1] 775.96
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