the problem I have is that userid's are not just sequential from
1:n_users. if they were, of course I'd have made a big matrix that was
n_users x n_fields and that would be that. but, I think what I cando is
just use the hash to store the index into the result matrix, nothing
more. then the rest
You are getting two very different results in what you are comparing.
system.time(lapply(1:10^4, mean))
user system elapsed
1.310.001.31
is returning a list with 10,000 values in it. It is taking time to allocate
the space and such.
system.time(for(i in 1:10^4) mean(i))
user
On 7/5/07, jim holtman [EMAIL PROTECTED] wrote:
You are getting two very different results in what you are comparing.
system.time(lapply(1:10^4, mean))
user system elapsed
1.310.001.31
is returning a list with 10,000 values in it. It is taking time to allocate
the space and
the CRAN package for SQLite hashes, but that seems to be going a bit
too far.
thanks,
Mike
Intern, Oyster Card Group, Transport for London
(feel free to email back to this address, I'm posting through NAbble so I
hope it works).
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mfrumin wrote:
Hey all; I'm a beginner++ user of R, trying to use it to do some processing
of data sets of over 1M rows, and running into a snafu. imagine that my
input is a huge table of transactions, each linked to a specif user id. as
I run through the transactions, I need to update a
Michael,
A hash provides constant-time access, though the resulting perl-esque
data structures (a hash of lists, e.g.) are not convenient for other
manipulations
n_accts - 10^3
n_trans - 10^4
t - list()
t$amt - runif(n_trans)
t$acct - as.character(round(runif(n_trans, 1, n_accts)))
uhash
i wish it were that simple. unfortunately the logic i have to do on
each transaction is substantially more complicated, and involves
referencing the existing values of the user table through a number of
conditions.
any other thoughts on how to get better-than-linear performance time?
is
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Michael Frumin wrote:
i wish it were that simple. unfortunately the logic i have to do on
each transaction is substantially more complicated, and involves
referencing the existing values of the user table through a number of
conditions.
any other thoughts on how to get better-than-linear
On 7/4/07, Martin Morgan [EMAIL PROTECTED] wrote:
Michael,
A hash provides constant-time access, though the resulting perl-esque
data structures (a hash of lists, e.g.) are not convenient for other
manipulations
n_accts - 10^3
n_trans - 10^4
t - list()
t$amt - runif(n_trans)
t$acct
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