Unexpected results in benchmark of read.csv / fread [duplicate] - r

Question

I can run a piece of code for 5 or 10 seconds using the following code:
period <- 10 ## minimum time (in seconds) that the loop should run for
tm <- Sys.time() ## starting data & time
while(Sys.time() - tm < period) print(Sys.time())
The code runs just fine for 5 or 10 seconds. But when I replace the period value by 60 for it to run for a minute, the code never stops. What is wrong?

Answer 1

As soon as elapsed time exceeds 1 minute, the default unit changes from seconds to minutes. So you want to control the unit:
while (difftime(Sys.time(), tm, units = "secs")[[1]] < period)
From ?difftime
If ‘units = "auto"’, a suitable set of units is chosen, the
largest possible (excluding ‘"weeks"’) in which all the absolute
differences are greater than one.
Subtraction of date-time objects gives an object of this class, by
calling ‘difftime’ with ‘units = "auto"’.
Alternatively use proc.time, which measures various times ("user", "system", "elapsed") since you started your R session in seconds. We want "elapsed" time, i.e., the wall clock time, so we retrieve the 3rd value of proc.time().
period <- 10
tm <- proc.time()[[3]]
while (proc.time()[[3]] - tm < period) print(proc.time())
If you are confused by the use of [[1]] and [[3]], please consult:
How do I extract just the number from a named number (without the name)?
How to get a matrix element without the column name in R?
Let me add some user-friendly reproducible examples. Your original code with print inside a loop is quite annoying as it prints thousands of lines onto the screen. I would use Sys.sleep.
test.Sys.time <- function(sleep_time_in_secs) {
t1 <- Sys.time()
Sys.sleep(sleep_time_in_secs)
t2 <- Sys.time()
## units = "auto"
print(t2 - t1)
## units = "secs"
print(difftime(t2, t1, units = "secs"))
## use '[[1]]' for clean output
print(difftime(t2, t1, units = "secs")[[1]])
}
test.Sys.time(5)
#Time difference of 5.005247 secs
#Time difference of 5.005247 secs
#[1] 5.005247
test.Sys.time(65)
#Time difference of 1.084357 mins
#Time difference of 65.06141 secs
#[1] 65.06141
The "auto" units is very clever. If sleep_time_in_secs = 3605 (more than an hour), the default unit will change to "hours".
Be careful with time units when using Sys.time, or you may be fooled in a benchmarking. Here is a perfect example: Unexpected results in benchmark of read.csv / fread. I had answered it with a now removed comment:
You got a problem with time units. I see that fread is more than 20 times faster. If fread takes 4 seconds to read a file, read.csv takes 80 seconds = 1.33 minutes. Ignoring the units, read.csv is "faster".
Now let's test proc.time.
test.proc.time <- function(sleep_time_in_secs) {
t1 <- proc.time()
Sys.sleep(sleep_time_in_secs)
t2 <- proc.time()
## print user, system, elapsed time
print(t2 - t1)
## use '[[3]]' for clean output of elapsed time
print((t2 - t1)[[3]])
}
test.proc.time(5)
# user system elapsed
# 0.000 0.000 5.005
#[1] 5.005
test.proc.time(65)
# user system elapsed
# 0.000 0.000 65.057
#[1] 65.057
"user" time and "system" time are 0, because both CPU and the system kernel are idle.