R intersect data.frame on multiple criteria

Question

I am trying to populate a binary vector based on the intersection of two data.frames on multiple criteria.

I have the code working but I feel that it is memory excessive just to get the binary vector.

When I apply my code to my full data (40mm+ rows). I begin to have memory problems.

Is there a simpler way to produce the vector?

Here is some sample data (e.g., sub sample will only include obs. in full sample):

ob1_1 <- as.data.frame(cbind(c(1999),c("111","222","666","777")),stringsAsFactors=FALSE)
ob2_1 <- as.data.frame(cbind(c(2000),c("111","333","555","777")),stringsAsFactors=FALSE)
ob3_1 <- as.data.frame(cbind(c(2001),c("111","222","333","777")),stringsAsFactors=FALSE)
ob4_1 <- as.data.frame(cbind(c(2002),c("111","444","555","777")),stringsAsFactors=FALSE)

full_sample <-  rbind(ob1_1,ob2_1,ob3_1,ob4_1)
colnames(full_sample) <- c("yr","ID")

ob1_2 <- as.data.frame(cbind(c(1999),c("111","222","777")),stringsAsFactors=FALSE)
ob2_2 <- as.data.frame(cbind(c(2000),c("333")),stringsAsFactors=FALSE)
ob3_2 <- as.data.frame(cbind(c(2001),c("888")),stringsAsFactors=FALSE)
ob4_2 <- as.data.frame(cbind(c(2002),c("111","444","555","777")),stringsAsFactors=FALSE)

sub_sample <-  rbind(ob1_2,ob2_2,ob3_2,ob4_2)
colnames(sub_sample) <- c("yr","ID")

Here is my working code:

q_intersect <- ""
q_intersect <- paste(q_intersect , "select       a.yr, a.ID       ", sep=" ")
q_intersect <- paste(q_intersect , "from         full_sample a  ", sep=" ")
q_intersect <- paste(q_intersect , "intersect                     ", sep=" ")
q_intersect <- paste(q_intersect , "select       b.yr, b.ID       ", sep=" ")
q_intersect <- paste(q_intersect , "from         sub_sample b  ", sep=" ")
q_intersect <- trim(gsub(" {2,}", " ", q_intersect ))

intersect_temp <- cbind(sqldf(q_intersect ),1)
colnames(intersect_temp ) <- c("yr","ID","in_both")

q_expand <- ""
q_expand <- paste(q_expand , "select       in_both            ", sep=" ")
q_expand <- paste(q_expand , "from         full_sample a      ", sep=" ")
q_expand <- paste(q_expand , "left join    intersect_temp  b  ", sep=" ")
q_expand <- paste(q_expand , "on           a.yr=b.yr          ", sep=" ")
q_expand <- paste(q_expand , "and          a.ID=b.ID          ", sep=" ")
q_expand <- trim(gsub(" {2,}", " ", q_expand ))

solution <- as.integer(sqldf(q_expand)[,1])
solution [is.na(solution )] <- 0 

Thanks ahead of time for any help!

Answer 1

It's not altogether clear what you are trying to accomplish, but I believe something like this would be a lot simpler.

library(data.table)
fullDT <- data.table(full_sample, key=c("yr", "ID"))
subDT  <- data.table(sub_sample,  key=c("yr", "ID"))

fullDT[ , intersect := 0L]
fullDT[subDT, intersect := 1, nomatch=0]

The idea is that you set the key of each data.table to be the columns you want to intersect. When you call full[sub], nomatch=0] you get your inner join, and we set only those values to 1; the values not identified in the inner join are left as 0, as set in the line prior.

fullDT
#        yr  ID intersect
#   1: 1999 111         1
#   2: 1999 222         1
#   3: 1999 666         0
#   4: 1999 777         1
#   5: 2000 111         0
#   6: 2000 333         1
#   7: 2000 555         0
#   8: 2000 777         0
#   9: 2001 111         0
#  10: 2001 222         0
#  11: 2001 333         0
#  12: 2001 777         0
#  13: 2002 111         1
#  14: 2002 444         1
#  15: 2002 555         1
#  16: 2002 777         1