context("rkt_get_max_n_rows")
test_that("Can create such a big data frame, #9", {
skip("Really needed?")
# Ideal
ncols <- rkt_get_max_n_cols()
nrows <- rkt_get_max_n_rows()
if (!beastier::is_on_travis()) {
# Smaller on local computer
ncols <- ncols / 10
nrows <- nrows / 10
}
ncells <- ncols * nrows
testit::assert(ncells < 2 ^ 32 - 1)
mem_use <- ncells * object.size(3.14)
format(mem_use, units = "Mb")
# Computer will freeze if you ignore this warning ..
testit::assert(mem_use < 2 ^ 32 - 1)
df <- data.frame(matrix(nrow = nrows, ncol = ncols, data = seq(1, ncells)))
# Save and load should work
filename <- tempfile()
utils::write.csv(x = df, file = filename, row.names = FALSE)
df2 <- utils::read.csv(file = filename)
testthat::expect_true(all.equal(df2, df, tolerance = 0.1))
rm(df)
rm(df2)
# Manually call garbage collection, we need that memory directly
gc()
})
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