Stage a DataFrame by saving it to a HDF5 file.
# S4 method for class 'DataFrame'
saveObject(x, path, DataFrame.character.vls = NULL, ...)
# S4 method for class 'data.frame'
saveObject(x, path, DataFrame.character.vls = NULL, ...)A DataFrame or data.frame.
String containing the path to a directory in which to save x.
Logical scalar indicating whether to save character vectors in the custom variable length string (VLS) array format.
If NULL, this is determined based on a comparison of the expected storage against a fixed length array.
Additional named arguments to pass to specific methods.
A named list containing the metadata for x.
x itself is written to a HDF5 file inside path.
Additional files may also be created inside path and referenced from the metadata.
This method creates a basic_columns.h5 file that contains columns for atomic vectors, factors, dates and date-times.
Dates and date-times are converted to character vectors and saved as such inside the file.
Factors are saved as a HDF5 group with both the codes and the levels as separate datasets.
Any non-atomic columns are saved to a other_columns subdirectory inside path via saveObject,
named after its zero-based positional index within x.
If metadata or mcols are present,
they are saved to the other_annotations and column_annotations subdirectories, respectively, via saveObject.
In the on-disk representation, no distinction is made between DataFrame and data.frame instances of x.
Calling readDataFrame will always produce a DFrame regardless of the class of x.
library(S4Vectors)
df <- DataFrame(A=1:10, B=LETTERS[1:10])
tmp <- tempfile()
saveObject(df, tmp)
list.files(tmp, recursive=TRUE)
#> [1] "OBJECT" "_environment.json" "basic_columns.h5"