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What's the fastest way to determine the number of rows of a CSV in R?
# What's the fastest way to determine the number of rows of a CSV in R?
# ...Reading the entire CSV to only get the dimensions is likely too slow. Is there a faster way?
# Benchmarks done on a EC2 r3.8xlarge
# Cowritten with Abel Castillo <github.com/abelcastilloavant>
m <- 1000000
d <- data.frame(id = seq(m), a = rnorm(m), b = runif(m))
dim(d)
# [1] 1000000 3
pryr::object_size(d)
# 20 MB
readr::write_csv(d, "tmp.csv")
microbenchmark::microbenchmark(
{lines <- 0; f <- file("tmp.csv", "r"); while (TRUE) {
line <- readLines(f, n = 1)
if (length(line) == 0) { break }; lines <- lines + 1}
print(lines - 1) }, # 2784.9ms
{ sqldf::read.csv.sql("tmp.csv", "select count(*) from file")[[1]] }, # 2103.0ms
{ length(readLines("tmp.csv")) - 1 }, # 1750.3ms
{ length(count.fields("tmp.csv")) - 1 }, # 1519.1ms
{ R.utils::countLines("tmp.csv")[[1]] - 1 }, # 1071.3ms
{ dim(data.table::fread("tmp.csv"))[[1]] }, # 493.4ms
{ NROW(data.table::fread("tmp.csv")) }, # 472.7ms
{ dim(readr::read_csv("tmp.csv"))[[1]] }, # 414.4ms
{ NROW(readr::read_csv("tmp.csv")) }, # 391.7ms
{ length(readr::count_fields("tmp.csv", tokenizer = readr::tokenizer_csv())) - 1 }, # 254.8ms
{ as.integer(strsplit(system("wc -l tmp.csv", intern = TRUE), " ")[[1]][[1]]) - 1 }, # 24.9ms
{ as.numeric(system("cat tmp.csv | wc -l", intern = TRUE)) - 1 }, # 17.9ms
times = 4)
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