Memory use spikes up with iotable_get()

[rafserqui]

The following code spikes memory up to 28GB when calling iotable_get() then crashes.

• iotables version: 0.9.3
• R version: 4.4.2
• Both on Windows and Pop!_OS

library(iotables)
library(tidyverse)
library(here)

# Getting the data
naio_10_cp1750 <- iotables_download("naio_10_cp1750",
    data_directory = here("data/naio-10-cp1750/"))

# Filter countries and year
c_naio <- naio_10_cp1750 %>%
    filter(geo %in% ccodes$country_code[2]) %>%
    filter(year %in% c(2015))

# Obtain the IO-Table
io_tables <-  iotable_get(labelled_io_data = c_naio,
    source = "naio_10_cp1750", geo = "BE",
    year = 2015, unit = "MIO_EUR",
    stk_flow = "IMP", labelling = "short",
    data_directory = here("data/naio-10-cp1750/"))

[antaldaniel]

Yes, indeed, I want to write a new function, because unfortunately the downloader first downloads the entire statiscal dispatch from Eurostat, which has grown considerably since the first release of the package.