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### Benchmark of save/read times vs save/load
require(h5)
require(testthat)
fname <- "test.h5"
if(file.exists(fname)) file.remove(fname)
fname.rda <- "test.rda"
if(file.exists(fname.rda)) file.remove(fname.rda)
dates <- seq(as.POSIXct("2005-01-01"), as.POSIXct("2015-01-01"), by = "mins")
dat <- cbind(unclass(dates),
matrix(as.numeric(seq(length.out = length(dates)*4)), ncol = 4))
if(file.exists(fname)) file.remove(fname)
time.saveh5 <- system.time({
file <- h5file(fname, "a")
file["/bigset", "bigset",
chunksize = c(nrow(dat), 1),
compression = 6] <- dat
h5close(file)
})
if(file.exists(fname.rda)) file.remove(fname.rda)
time.saverda <- system.time(
save(dat, file = fname.rda, compress = "gzip", compression_level = 6)
)
benchmark.save <- cbind(time.saveh5, time.saverda)
# time.saveh5 time.saverda
# user.self 0.35 20.39
# sys.self 0.07 0.11
# elapsed 0.75 20.51
time.subseth5 <- system.time({
file <- h5file(fname, "r")
vec <- seq(1, nrow(dat), by = 60)
dset <- file["/bigset", "bigset"]
out.subseth5 <- dset[vec, 2]
h5close(dset)
h5close(file)
})
# read entire set
time.subseth52 <- system.time({
file <- h5file(fname, "r")
vec <- seq(1, nrow(dat), by = 60)
dset <- file["/bigset", "bigset"]
out.subseth52 <- dset[]
out.subseth52 <- out.subseth52[vec, 2, drop = FALSE]
h5close(dset)
h5close(file)
})
# use hyperslabs
time.subseth53 <- system.time({
file <- h5file(fname, "r")
vec <- seq(1, nrow(dat), by = 60)
dset <- file["/bigset", "bigset"]
out.subseth53 <- readData(dset,
selectDataSpace(dset, offset = c(1, 2), count = c(nrow(dat), 1)))
out.subseth53 <- out.subseth53[vec,, drop = FALSE]
h5close(dset)
h5close(file)
})
time.subsetrda <- system.time({
load(file = "test.rda")
out.subsetrda <- dat[vec, 2, drop = FALSE]
})
file.remove(fname)
file.remove(fname.rda)
identical(out.subseth5, out.subseth52)
identical(out.subseth5, out.subseth53)
identical(out.subseth5, out.subsetrda)
benchmark.read <- cbind(time.subseth5, time.subseth52, time.subseth53, time.subsetrda)
# time.subseth5 time.subseth52 time.subseth53 time.subsetrda
# user.self 15.97 0.42 0.02 0.67
# sys.self 0.01 0.11 0.04 0.06
# elapsed 15.99 0.53 0.05 0.73
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