View source: R/create-batch-glossary.R
| create_batch_glossary | R Documentation |
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.
create_batch_glossary(row_count, batch_size)
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. |
This function can also assist splitting and saving a large 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.
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.
Will Beasley
See redcap_read() for a function that uses create_batch_glossary.
REDCapR::create_batch_glossary(100, 50)
REDCapR::create_batch_glossary(100, 25)
REDCapR::create_batch_glossary(100, 3)
REDCapR::create_batch_glossary( 0, 3)
d <- data.frame(
record_id = 1:100,
iv = sample(x=4, size=100, replace=TRUE),
dv = rnorm(n=100)
)
REDCapR::create_batch_glossary(nrow(d), batch_size=40)
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