[R] zoo performance regression noticed (1.6-5 is faster...)
jmarca at translab.its.uci.edu
Fri Nov 4 17:34:07 CET 2011
I have discovered what I believe to be a performance regression
between Zoo 1.6x and Zoo 1.7-6 in the application of rollapply.
On zoo 1.6x, rollapply of my function over my data takes about 20
minutes. Using 1.7-6, the same code takes about 6 hours.
R version 2.13.1 (2011-07-08)
Copyright (C) 2011 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
Two versions of zoo 1.6 run *fast* On one machine I am running
Title: Z's ordered observations
Packaged: 2010-04-23 07:28:47 UTC; zeileis
Date/Publication: 2010-04-23 07:43:54
Built: R 2.10.1; ; 2010-04-25 06:41:34 UTC; unix
(Thankfully I forgot to upgrade.packages() on this machine!)
On the other
Packaged: 2011-04-08 17:13:47 UTC; zeileis
Date/Publication: 2011-04-08 17:27:47
Built: R 2.13.1; ; 2011-11-04 15:49:54 UTC; unix
I have stripped out zoo 1.7-6 from all my machines.
I tried to ensure all libraries were identical on the two machines
(using lsof), and after finally downgrading zoo I got the second
machine to be as fast as the first, so I am quite certain the
difference in speed is down to the Zoo version used.
My code runs a fairly simple function over a time series using the
following call to process a year of 30s data (9 columns, about a
vals <- rollapply(data=ts.data[,c(n.3.cols, o.3.cols,volocc.cols)]
(The rolling.function.fn call returns a function that is initialized
If this is a known situation with the new 1.7 generation Zoo, my
apologies and I'll go away. If my code could be turned into a useful
test, I'd be happy to help out as much as I'm able. Given the extreme
runtime difference though, I thought I should offer my help in this
case, since zoo is such a useful package in my work.
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