On Mon, Mar 22, 2010 at 6:37 AM, <Jan.Sunde at biokapital.no>
wrote:> Hi
> I have a problem in R that I have been trying to solve but without
> success.
> I am trying to join two tables on two variables : an ID and a date
> (optional) that will be common between the two tables
>
> In SQL (and SAS PROC SQL) I am a frequent user of the "select"
command and
> I am used to the following nomenclature :
>
> select a.*, b.c, b.y, b.z from table1 a, table2 b where a.date=b.date and
> a.id=b.id
>
> I tried this in R (using sqldf) but it takes waaaay too long to get the
> result. My data sets are >1 gb each.
Try adding indexes to the join columns. I was able to do a join
between two 1 million row tables in 13 seconds (under a minute
including the time to add the indexes) on a laptop (not a particularly
fast machine).
> set.seed(1)
> n <- 1000000
> DF1 <- data.frame(a = sample(n, n), b1 = runif(n))
> DF2 <- data.frame(a = sample(n, n), b2 = runif(n))
> library(sqldf)
>
> sqldf()
<SQLiteConnection:(2708,1)>> system.time(sqldf("create index ai1 on DF1(a)"))
user system elapsed
16.63 0.09 16.85> system.time(sqldf("create index ai2 on DF2(a)"))
user system elapsed
16.06 0.04 16.30> system.time(sqldf("select * from main.DF1 natural join
main.DF2"))
user system elapsed
12.72 0.21 12.93> sqldf()
> Is there any way this can be done by merge() or any other more
"R-like"
> way ?
> I have tried making a compound variable with paste(id, as.character(date),
> sep="") and merge() on that but since the date more often than
not is NA
> this doesnt seem to work. I'm a bit stuck and the documentation is of
> little help to me in this case.
> If anybody would be kind to point me in the right direction I would be
> grateful.
>
> Jan
>
>
> ? ? ? ?[[alternative HTML version deleted]]
>
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