Determining memory usage of objects?

1. by object size

to get memory allocation on an object-by-object basis, call object.size() and pass in the object of interest:

object.size(My_Data_Frame)

(unless the argument passed in is a variable, it must be quoted, or else wrapped in a get call.)variable name, then omit the quotes,

you can loop through your namespace and get the size of all of the objects in it, like so:

for (itm in ls()) { 
    print(formatC(c(itm, object.size(get(itm))), 
        format="d", 
        big.mark=",", 
        width=30), 
        quote=F)
}

2. by object type

to get memory usage for your namespace, by object type, use memory.profile()

memory.profile()

   NULL      symbol    pairlist     closure environment     promise    language 
      1        9434      183964        4125        1359        6963       49425 
special     builtin        char     logical     integer      double     complex 
    173        1562       20652        7383       13212        4137           1 

(There's another function, memory.size() but i have heard and read that it only seems to work on Windows. It just returns a value in MB; so to get max memory used at any time in the session, use memory.size(max=T)).

another (slightly prettier) option using dplyr

    data.frame('object' = ls()) %>% 
      dplyr::mutate(size_unit = object %>%sapply(. %>% get() %>% object.size %>% format(., unit = 'auto')),
                    size = as.numeric(sapply(strsplit(size_unit, split = ' '), FUN = function(x) x[1])),
                    unit = factor(sapply(strsplit(size_unit, split = ' '), FUN = function(x) x[2]), levels = c('Gb', 'Mb', 'Kb', 'bytes'))) %>% 
      dplyr::arrange(unit, dplyr::desc(size)) %>% 
      dplyr::select(-size_unit)

A data.table function that separates memory and unit for easier sorting:

ls.obj <- {as.data.table(sapply(ls(),
function(x){format(object.size(get(x)),
nsmall=3,digits=3,unit="Mb")}),keep.rownames=TRUE)[,
c("mem","unit") := tstrsplit(V2, " ", fixed=TRUE)][,
setnames(.SD,"V1","obj")][,.(obj,mem=as.numeric(mem),unit)][order(-mem)]}

ls.obj

                        obj     mem unit
     1:                obj1 848.283   Mb
     2:                obj2  37.705   Mb

...

Here's a tidyverse-based function to calculate the size of all objects in your environment:

weigh_environment <- function(env){
  
  purrr::map_dfr(env, ~ tibble::tibble("object" = .) %>% 
                   dplyr::mutate(size = object.size(get(.x)),
                                 size = as.numeric(size),
                                 megabytes = size / 1000000))
  
}