found it here:https://stackoverflow.com/questions/1358003/tricks-to-manage-the-available-memory-in-an-r-session

.ls.objects <- function (pos = 1, pattern, order.by, decreasing=FALSE, head=FALSE, n=5) { napply <- function(names, fn) sapply(names, function(x) fn(get(x, pos = pos))) names <- ls(pos = pos, pattern = pattern) obj.class <- napply(names, function(x) as.character(class(x))[1]) obj.mode <- napply(names, mode) obj.type <- ifelse(is.na(obj.class), obj.mode, obj.class) obj.prettysize <- napply(names, function(x) { format(utils::object.size(x), units = "auto") }) obj.size <- napply(names, object.size) obj.dim <- t(napply(names, function(x) as.numeric(dim(x))[1:2])) vec <- is.na(obj.dim)[, 1] & (obj.type != "function") obj.dim[vec, 1] <- napply(names, length)[vec] out <- data.frame(obj.type, obj.size, obj.prettysize, obj.dim) names(out) <- c("Type", "Size", "PrettySize", "Length/Rows", "Columns") if (!missing(order.by)) out <- out[order(out[[order.by]], decreasing=decreasing), ] if (head) out <- head(out, n) out }

shorthand

lsos <- function(..., n=10) { .ls.objects(..., order.by="Size", decreasing=TRUE, head=TRUE, n=n) }

lsos()

MatthieuStigler / matPkg

show memory usage #19

shorthand