REDCapR (version 0.9.8)

create_batch_glossary: Creates a base::data.frame() that help batching long-running read and writes.

Description

The function returns a base::data.frame() that other functions use to separate long-running read and write REDCap calls into multiple, smaller REDCap calls. The goal is to (1) reduce the chance of time-outs, and (2) introduce little breaks between batches so that the server isn't continually tied up.

Usage

create_batch_glossary(row_count, batch_size)

Arguments

row_count

The number records in the large dataset, before it's split.

batch_size

The maximum number of subject records a single batch should contain.

Value

Currently, a base::data.frame() is returned with the following columns,

• id: an integer that uniquely identifies the batch, starting at 1.

• start_index: the index of the first row in the batch. integer.

• stop_index: the index of the last row in the batch. integer.

• id_pretty: a character representation of id, but padded with zeros.

• start_index: a character representation of start_index, but padded with zeros.

• stop_index: a character representation of stop_index, but padded with zeros.

• label: a character concatenation of id_pretty, start_index, and stop_index_pretty.

Details

This function can also assist splitting and saving a large base::data.frame() to disk as smaller files (such as a .csv). The padded columns allow the OS to sort the batches/files in sequential order.

See Also

See redcap_read() for a function that uses create_batch_gloassary.

Examples

# NOT RUN {
library(REDCapR) #Load the package into the current R session.
create_batch_glossary(100, 50)
create_batch_glossary(100, 25)
create_batch_glossary(100, 3)
d <- data.frame(
  record_id = 1:100,
  iv        = sample(x=4, size=100, replace=TRUE),
  dv        = rnorm(n=100)
)
create_batch_glossary(nrow(d), batch_size=40)
# }