Seems like the "by-without-by" is what's slowing things down: require(data.table) dtx <- data.table(x=which(X), key="x") dty <- data.table(y=which(Y), key="y") dtx[, x1 := x] dty[, y1 := y] system.time(ans <- dty[dtx, roll="nearest"][, abs(x1-y1)]) user system elapsed 1.321 0.076 1.396 system.time(ans2 <- flodel(x,y)) user system elapsed 0.936 0.044 0.977
identical(ans, ans2) # [1] TRUE On Wed, Feb 5, 2014 at 4:32 PM, Arunkumar Srinivasan <[email protected]>wrote: > Just tested. Works just fine (on 1.8.11). Takes 16 seconds as opposed to > Flodel's which takes 1.4 seconds on my laptop. Also identical returned TRUE. > Will see where's the delay coming from. > > > On Wed, Feb 5, 2014 at 4:22 PM, Gabor Grothendieck < > [email protected]> wrote: > >> There was anoither benchmark posted with larger data and longer times >> but this time data.table stopped with an error. See: >> >> >> http://stackoverflow.com/questions/21499742/fast-minimum-distance-interval-between-elements-of-2-logical-vectors-take-2/21500855#21500855 >> >> On Mon, Feb 3, 2014 at 6:46 AM, Matt Dowle <[email protected]> >> wrote: >> > Gabor, >> > >> > With that said about it being a micro benchmark, by-without-by might >> be at >> > play in GG2(X,Y) here; i.e. running j for each row of i, where it could >> run >> > once. I remember you and others quite rightly said by-without-by >> should be >> > explicit ... still got to make that change. A similar speed issue came >> up >> > recently somewhere else as well which the change in default should help. >> > >> > Matt >> > >> > >> > On 02/02/14 18:57, Matt Dowle wrote: >> > >> > >> > But this is at the *micro* second level ?!! >> > >> > I confirm those results on my slow netbook but remember these are >> **micro** >> > seconds i.e. 71,000 here is less than 0.1 of a second. >> > >> >> microbenchmark(flodel(X,Y), GG1(X,Y), GG2(X,Y)) >> > Unit: microseconds >> > expr min lq median uq max >> neval >> > flodel(X, Y) 330.798 369.369 402.7935 455.3225 17996.26 >> 100 >> > GG1(X, Y) 14287.380 14370.038 14466.5990 16010.5440 121082.77 >> 100 >> > GG2(X, Y) 71164.270 85751.437 107951.3415 161676.5720 366003.62 >> 100 >> > >> > To put it in some perspective : >> > >> >> system.time(GG2(X,Y)) >> > user system elapsed >> > 0.072 0.000 0.072 >> >> system.time(GG2(X,Y)) >> > user system elapsed >> > 0.080 0.000 0.079 >> >> system.time(GG2(X,Y)) >> > user system elapsed >> > 0.072 0.000 0.072 >> > >> > Where those times are in seconds. So the task in question here, takes >> > 0.07 seconds ?! >> > >> > The 150x longer figure is actually (using figures from the S.O. answer) >> > 24695 microseconds (i.e. 0.024 seconds) divided by 168 microseconds >> > (0.000168 seconds). 0.024 seconds / 0.000168 = "150 times". If you >> > rounded to milliseconds you could say data.table is infinitely slower >> (24ms >> > / 0ms = Inf). >> > >> > I can believe there's scope for improvement, sure, but not from this >> > benchmark. The vectors need to be *much* bigger and replications needs >> to be >> > *much* smaller, say 3. The task being timed needs to take a meaningful >> > amount of time (say 5 seconds) *for a single run*. >> > >> > Matt >> > >> > >> > On 02/02/14 12:27, Gabor Grothendieck wrote: >> > >> > The benchmark at the bottom of this post shows a problem where a >> data.table >> > roll="next" took nearly 150x longer than a base findInterval() solution. >> > (The data.table solution is easier to write though.) This suggests an >> area >> > for possible speed improvement. >> > >> > >> http://stackoverflow.com/questions/21499742/fast-minimum-distance-interval-between-elements-of-2-logical-vectors-take-2/21500855#21500855 >> > >> > -- >> > Statistics & Software Consulting >> > GKX Group, GKX Associates Inc. >> > tel: 1-877-GKX-GROUP >> > email: ggrothendieck at gmail.com >> > >> > >> > _______________________________________________ >> > datatable-help mailing list >> > [email protected] >> > >> https://lists.r-forge.r-project.org/cgi-bin/mailman/listinfo/datatable-help >> > >> > >> > >> >> >> >> -- >> Statistics & Software Consulting >> GKX Group, GKX Associates Inc. >> tel: 1-877-GKX-GROUP >> email: ggrothendieck at gmail.com >> _______________________________________________ >> datatable-help mailing list >> [email protected] >> >> https://lists.r-forge.r-project.org/cgi-bin/mailman/listinfo/datatable-help >> > >
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