[R] Kosaraju's SCC Algorithm Running
Bert Gunter
bgunter.4567 at gmail.com
Mon Nov 7 18:30:48 CET 2016
See here -- found by googling "recursion limits in R"
http://stackoverflow.com/questions/26797537/r-programming-level-of-allowed-recursion-depth-differs-when-calling-a-local-hel
-- Bert
Bert Gunter
"The trouble with having an open mind is that people keep coming along
and sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
On Mon, Nov 7, 2016 at 7:49 AM, Jie C <ginojay at gmail.com> wrote:
> Hi Jeff,
>
> Thanks for your reply! We are definitely not seeking for help with the
> assignment per se. Maybe we should have given you a simpler code to just
> illustrate the problem. We found this to be an interesting case for
> illustrating the recursion limit of R. For other languages such as Python,
> Java, and C++, it seems that they are less likely to hit the problem as R
> does. Even if they do, it is relatively easy to increase the recursion
> depth to the desired numbers. I want to clarify that our purpose is trying
> to understand the limitation of R language in handling big computational
> problems that relies on deep recursion. If you could point us to technical
> documents regarding this, that would be highly appreciated. Also, we could
> definitely re-post a simple code snippet that follows the Posting Guide to
> illustrate that R hits the recursion limitation. Looking forward to your
> advise!
>
> Thanks,
>
> Jie
>
>
>
>
>
> On Mon, Nov 7, 2016 at 2:28 AM, Jeff Newmiller <jdnewmil at dcn.davis.ca.us>
> wrote:
>
>> Please read the Posting Guide mentioned at the bottom of this and every
>> post, which warns you that homework is off topic on this mailing list. Use
>> the support provided by your institution of learning (Coursera in this
>> case).
>> --
>> Sent from my phone. Please excuse my brevity.
>>
>> On November 6, 2016 8:12:38 PM PST, Megan <megan.fight at gmail.com> wrote:
>> >To whom it may concerns,
>> >
>> >We encountered stack overflow issues when we implemented DFS(depth
>> >first search) algorithm on a directed graph having 800,000+ vertices
>> >and millions of edges. The purpose of running DFS is to use Kosaraju
>> >Algorithm to calculate the size of SCC(strongly connected componment)
>> >in the graph. This is an assignment from Coursea.org
>> ><http://coursea.org/>. We know the maximum size of SCC in the graph is
>> >434,821, which means the maximum recursion depth during code running is
>> >434,821. We know it is a large calculation behind the scene, therefore,
>> >we’ve done the below pre-setup hopefully to solve the stack overflow
>> >issue. However, we have not got the luck yet. We’ve tried running on
>> >both R and RStudio.
>> >
>> >We would really appreciate if someone in your team can help to
>> >investigate. We can’t wait to see if our code is working in R.
>> >
>> >System Information:
>> >Model Name: MacBook Pro
>> > Model Identifier: MacBookPro11,1
>> > Processor Name: Intel Core i5
>> > Processor Speed: 2.4 GHz
>> > Number of Processors: 1
>> > Total Number of Cores: 2
>> > L2 Cache (per Core): 256 KB
>> > L3 Cache: 3 MB
>> > Memory: 8 GB
>> >
>> >System settings we have tried:
>> >1. ulimit- s 65000 (to increase stack size before starting up R)
>> >2. R --max-ppsize =500000 (start R with max ppsize)
>> >3. options(expression=500000)
>> >
>> >
>> >The data we used can be found on
>> >https://d18ky98rnyall9.cloudfront.net/_410e934e6553ac56409b2cb7096a44
>> aa_SCC.txt?Expires=1478649600&Signature=YC0OjTn4hmzWpzAMw3WkQjXgxkAc0q
>> hZrCd07JAPtud3dGQqywpQgkAASf-bWX6qgGafVvObciJ3ww-7wbNqY0YhWxwcg-
>> IxmCnz1xJu1SORdDobiVKmhhfSaqgTyullX1hFmcxAA4y6Ud33hY1dhIP~
>> UTAlW~IV8Y-zSliAts8_&Key-Pair-Id=APKAJLTNE6QMUY6HBC5A
>> ><https://d18ky98rnyall9.cloudfront.net/_410e934e6553ac56409b2cb7096a44
>> aa_SCC.txt?Expires=1478649600&Signature=YC0OjTn4hmzWpzAMw3WkQjXgxkAc0q
>> hZrCd07JAPtud3dGQqywpQgkAASf-bWX6qgGafVvObciJ3ww-7wbNqY0YhWxwcg-
>> IxmCnz1xJu1SORdDobiVKmhhfSaqgTyullX1hFmcxAA4y6Ud33hY1dhIP~
>> UTAlW~IV8Y-zSliAts8_&Key-Pair-Id=APKAJLTNE6QMUY6HBC5A>
>> >
>> >Data discription provided as follow:
>> >https://www.coursera.org/learn/algorithm-design-analysis/exam/rOtFq/
>> programming-assignment-4
>> ><https://www.coursera.org/learn/algorithm-design-analysis/exam/rOtFq/
>> programming-assignment-4>
>> >
>> >
>> >Below is our code:
>> >
>> >options(expressions=500000)
>> >#Prepare input test file
>> >g=read.table("Downloads/scc.txt")
>> >x<<-as.matrix(g)
>> >remove(g)
>> >vector.is.empty<<-function(x) {return(length(x)==0)}
>> >'%!in%' <- function(x,y)!('%in%'(x,y))
>> >#g<-c(2,1,3,1,3,4,4,2,5,4,5,6,6,7,7,8,8,9,2,3)
>> >#x<<-matrix(g,nrow=10,ncol=2, byrow=TRUE)
>> >#g<-c(1,4,2,8,3,6,4,7,5,2,6,9,7,1,8,5,8,6,9,3,9,7,10,2)
>> >#x<<-matrix(g,nrow=12,ncol=2, byrow=TRUE)
>> >#g<-c(1,2,2,3,2,4,3,4,3,5,4,1,4,13,5,6,6,7,7,8,8,9,9,6,10,
>> 9,10,11,11,8,11,12,12,13,12,14,13,10,14,15)
>> >#x<<-matrix(g,20,2,byrow=TRUE)
>> >
>> >u1<-unique(x[,1])
>> >u2<-unique(x[,2])
>> >u<-c(u1,u2)
>> >n<<-length(unique(u))
>> >remove(u1,u2,u)
>> >
>> >G <<- vector("list", length=n)
>> >G_REV <<- vector("list", length=n)
>> >P = numeric(n)
>> >FT = numeric(n)
>> >
>> >for (i in 1:nrow(x)) {
>> > a = x[i,1]
>> > b = x[i,2]
>> > #for G
>> > if (is.null(G[[a]])) {
>> > G[[a]] = c(b)
>> > } else {
>> > G[[a]] = c(G[[a]], b)
>> > }
>> > if (is.null(G[[b]])) {
>> > G[[b]] = numeric()
>> > }
>> > #for G_VEV
>> > if (is.null(G_REV[[b]])) {
>> > G_REV[[b]] = c(a)
>> > } else {
>> > G_REV[[b]] = c(G_REV[[b]], a)
>> > }
>> > if (is.null(G_REV[[a]])) {
>> > G_REV[[a]] = numeric()
>> > }
>> >}
>> >
>> >G_TEMP <<- G_REV
>> >
>> >#G_REV<<-x[,c(2,1)]
>> >
>> >#P<<-matrix(c(1:n,rep(0,2*n)),nrow=n,ncol=3) #tracking whether vertex
>> >is explored or not
>> >
>> >#colnames(P)<-c("node","f","parent_vertex")
>> >explore<<-numeric()
>> >assign("time",0,envir=globalenv())
>> >#Algorithm -DFS
>> >
>> >DFS_LOOP<<-function(G){
>> > counter = n
>> > for(i in n : 1){
>> > if (i < counter) {
>> > counter = counter - 1000;
>> > print(i);
>> > }
>> > if (i %in% explore){next}
>> > else {
>> > DFS(i)
>> > }
>> > }
>> >}
>> >
>> >DFS<<-function(i){
>> > #if(time>=n){return(p)}
>> > #else{
>> > #print(c("i=",i))
>> > explore<<-c(explore,i)
>> > #print(c("explore",explore))
>> >
>> > #P[i,2] <<- 1 # gray
>> > v=G_TEMP[[i]]
>> >
>> > #print(c("v=",v))
>> > if (vector.is.empty(v) ==TRUE){
>> > len=1
>> > v=i
>> > }
>> >
>> > if(vector.is.empty(v)==FALSE){
>> > len=length(v)
>> > }
>> >
>> > for(j in 1: len){
>> > if(v[j] %!in% explore){
>> > DFS(v[j])
>> > #P[v[j],3] <<-i
>> > P[v[j]] <<- i
>> > # print(c("child",j,"parent",i))
>> > }
>> > }
>> >
>> > time<<-time + 1
>> > FT[i] <<- time
>> > #P[i,2] <<- time
>> > #P[i,2] <<- 2 #black
>> > # } <<-else
>> >}
>> >print('Starting DFS_loop on G_REV')
>> >DFS_LOOP(G_REV)
>> >###################################################
>> >#temp0<-matrix(1:n,n,1)
>> ># temp1<-P[,c(1,2)]
>> ># colnames(temp1)<-c("before","after")
>> ># temp1<-as.data.frame(temp1)
>> ># colnames(x)<-c("vertex","edge")
>> ># X<-as.data.frame(x)
>> ># X_NEW<-merge(x=X,y=temp1,by.x="vertex",by.y="before")
>> ># remove(X)
>> ># names(X_NEW)[names(X_NEW)=="after"]<-"vertex_new"
>> ># X_NEW2<-merge(x=X_NEW,y=temp1,by.x="edge",by.y="before")
>> ># remove(X_NEW,temp1)
>> ># names(X_NEW2)[names(X_NEW2)=="after"]<-"edge_new"
>> ># G2<-as.matrix(X_NEW2)
>> ># remove(X_NEW2)
>> ># G2<-G2[,c(3,4)]
>> ># u1<-unique(G2[,1])
>> ># u2<-unique(G2[,2])
>> ># u<-c(u1,u2)
>> ># n<<-length(unique(u))
>> ># remove(u1,u2,u)
>> >
>> >FT_SORTED = numeric(n)
>> >for (i in length(FT):1) {
>> > finish_time = FT[i]
>> > FT_SORTED[finish_time] = i
>> >}
>> >
>> >P = numeric(n)
>> >FT = numeric(n)
>> >
>> >#P<<-matrix(c(1:n,rep(0,2*n)),nrow=n,ncol=3) #tracking whether vertex
>> >is explored or not
>> >#colnames(P)<-c("vertex","f","parent_vertex")
>> >explore<<-numeric()
>> >assign("time",0,envir=globalenv())
>> >
>> >print('Starting DFS_loop on G')
>> >#DFS_LOOP(G2)#2nd DFS
>> >explore<<-numeric()
>> >
>> >G_TEMP <<- G
>> >
>> >for (i in length(FT_SORTED):1) {
>> > k = FT_SORTED[i]
>> > if (k %!in% explore) {
>> > DFS(k)
>> > }
>> >}
>> >
>> >mscc_temp = which(P==0)
>> >scc_temp=FT[mscc_temp]
>> >#scc_temp<-P[P[,3]==0,2]
>> >scc_temp=sort(scc_temp,decreasing=TRUE)
>> >m=length(scc_temp)
>> >scc=numeric()
>> >for (i in 1:(m-1)){
>> > scc[i]=scc_temp[i]-scc_temp[i+1]
>> >}
>> >scc[m]<-scc_temp[m]
>> >scc_top_5<-tail(sort(scc),5)
>> >
>> >
>> >Thanks,
>> >Jing
>> > [[alternative HTML version deleted]]
>> >
>> >______________________________________________
>> >R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
>> >https://stat.ethz.ch/mailman/listinfo/r-help
>> >PLEASE do read the posting guide
>> >http://www.R-project.org/posting-guide.html
>> >and provide commented, minimal, self-contained, reproducible code.
>>
>>
>
>
> --
> Best regards,
>
> Jie
>
> [[alternative HTML version deleted]]
>
> ______________________________________________
> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
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