| dt_parquet | R Documentation | 
 Load data IN- our OUT- of memory.
File extension can be omitted.
dt_parquet(path_base, name = NULL, ext = ".parquet", in_memory = TRUE)
path_base | 
 A character string, providing the path to read from.  | 
name | 
 Optional. A character string. The file name (if absent from   | 
ext | 
 Optional. A character string. The file extension.  | 
in_memory | 
 Logical, should data be loaded in memory?  | 
Output is a data.table.
For meddra and whodrug tables, it is still a good option to load data in-memory.
This function is wrapping arrow::read_parquet(), dplyr::collect() and
data.table::as.data.table() altogether.
If you want to load OUT of memory, set arg in_memory to FALSE.
Be careful that doing so will change the function output format.
For this latter case, the output is not a data.table, so there is no practical
benefit as compared to using arrow::read_parquet() directly, with
as_data_frame = FALSE.
A data.table if in_memory is set to TRUE,
a parquet Table if in_memory is set to FALSE.
tb_vigibase(), tb_who(), tb_meddra()
# Say you have a data.frame stored in a parquet format, such as this one
demo <-
  data.table::data.table(
    UMCReportId = c(1, 2, 3, 4),
    AgeGroup = c(1, 7, 7, 8)
  ) |>
  arrow::as_arrow_table()
tmp_folder <- paste0(tempdir(), "/dtparquetex")
dir.create(tmp_folder)
path_data <- paste0(tmp_folder, "/")
arrow::write_parquet(demo,
                     sink = paste0(path_data, "demo.parquet")
)
# Now you have a new session without demo
rm(demo)
# You may import the file directly to data.table format with dt_parquet
demo <-
  dt_parquet(path_data, "demo")
# Clean up (required for CRAN checks)
unlink(tmp_folder, recursive = TRUE)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.