替换R中的嵌套循环

Question

I am very new to R and searched about this on forums but couldn't get a close enough solution for this. I am trying to do a mapping between the ip address & corresponding geo locations. I have 2 data sets.

Set-a (1,60,000 rows):
ip(int) | ID(int)

Set-b (16,00,000 rows):
Ip1(int) | Ip2(int) | Code(str) | Country(str) | Area1(str) | Area2(str)

I am trying to do the following: if ip lies between Ip1 & Ip2 then add Country & Region to Set-a.

I am doing the following (obviously not a very good way to do this):

ip1<-as.numeric(b$Ip1)
ip2<-as.numeric(b$Ip2)
country<-b$Country
area1<-b$Area1
area2<-b$Area2

for(i in 1:160000){
  for(j in 1:1674303){
    if(a[i]>ip1[j] & a[i]<ip2[j]) {
                                   a$country[i]<-country[j]
                                   a$area1[i]<-area1[j]
                                   a$area2[i]<-area2[j]}
   }
}

Can someone please tell me an efficient way to do this. This is taking a lot of time. (for i=1 to 100 took some 10 mins to run).

The sample data set-b is:

Ip1, Ip2, Code, Country, Area1, Area2
"0","16777215","-","-","-","-"
"16777216","16777471","AU","AUSTRALIA","QUEENSLAND","SOUTH BRISBANE"
"16777472","16778239","CN","CHINA","FUJIAN","FUZHOU"
"16778240","16778495","AU","AUSTRALIA","VICTORIA","MELBOURNE"
"16778496","16778751","AU","AUSTRALIA","NEW SOUTH WALES","SYDNEY"

It is in continuos increasing order.

The dput(head(a)) & dput(head(b)) respectively are: (refer sample data above)

structure(IP_Addr = c("38825563", "38921619", "42470287", "42471923","42473368","42473428"), 
 Desc_value = c("0", "1.2", "4.97", "1", "5.9", "22.06")), .Names = c("IP_Addr", "Desc_value"), row.names = c(NA, 6L), class = "data.frame")

structure(list(Ip1 = c("0", "16777216", "16777472", "16778240", 
"16778496", "16778752"), Ip2 = c("16777215", "16777471", "16778239", 
"16778495", "16778751", "16779263"), Code = c("-", "AU", "CN", 
"AU", "AU", "AU"), Country = c("-", "AUSTRALIA", "CHINA", "AUSTRALIA", 
"AUSTRALIA", "AUSTRALIA"), Area1 = c("-", "QUEENSLAND", "FUJIAN", 
"VICTORIA", "NEW SOUTH WALES", "-"), Area2 = c("-", "SOUTH BRISBANE", 
"FUZHOU", "MELBOURNE", "SYDNEY", "-")), .Names = c("Ip1", "Ip2", 
"Code", "Country", "Area1", "Area2"), row.names = c(NA, 6L), class = "data.frame")

Answer 1

Here's a data.table solution:

# Let's take Blue Magister's example set:
set.seed(10)
a <- data.frame(ip=sample(16777216:16778751,10,replace=TRUE))
b <- read.table(sep=",",header=TRUE,text='Ip1, Ip2, Code, Country, Area1, Area2
"0","16777215","-","-","-","-"
"16777216","16777471","AU","AUSTRALIA","QUEENSLAND","SOUTH BRISBANE"
"16777472","16778239","CN","CHINA","FUJIAN","FUZHOU"
"16778240","16778495","AU","AUSTRALIA","VICTORIA","MELBOURNE"
"16778496","16778751","AU","AUSTRALIA","NEW SOUTH WALES","SYDNEY"')

b$Ip1 <-as.numeric(b$Ip1)

# include library, convert to data.table
library(data.table)

a = data.table(a)
b = data.table(b, key = "Ip1")

# and now the actual computation
a = b[a, roll = Inf][, Ip2 := NULL] # yep, amazingly, it's *that* simple in data.table
setnames(a, "Ip1", "ip")            # you can also include, exclude whatever columns you want
a
#          ip Code   Country      Area1          Area2
# 1: 16777995   CN     CHINA     FUJIAN         FUZHOU
# 2: 16777687   CN     CHINA     FUJIAN         FUZHOU
# 3: 16777871   CN     CHINA     FUJIAN         FUZHOU
# 4: 16778280   AU AUSTRALIA   VICTORIA      MELBOURNE
# 5: 16777346   AU AUSTRALIA QUEENSLAND SOUTH BRISBANE
# 6: 16777562   CN     CHINA     FUJIAN         FUZHOU
# 7: 16777637   CN     CHINA     FUJIAN         FUZHOU
# 8: 16777634   CN     CHINA     FUJIAN         FUZHOU
# 9: 16778161   CN     CHINA     FUJIAN         FUZHOU
#10: 16777875   CN     CHINA     FUJIAN         FUZHOU

Had Ip1 been an exhaustive list of numbers that ip could match, then above would simply be a merge (of Ip1 in b with first column of a , ie ip ), but data.table also provides an option of what to do when there is no exact match. You can tell it to eg roll the previous observation forward (which is what I did above), or roll it back or roll to the nearest observation - see ?data.table for a little more information.

Answer 2

Couldn't you remove the 2nd loop using,

j = intersect(which(ip1 < x[i]), which(ip2 > x[i]))
if  (length(j)==1){
         a$country[i]<-country[j]
         a$area1[i]<-area1[j]
         a$area2[i]<-area2[j]
}else{
         cat("Multiple matches found!\n")  
}

Answer 3

I would try findInterval :

#create example
set.seed(10)
a <- data.frame(ip=sample(16777216:16778751,10,replace=TRUE))
b <- read.table(sep=",",header=TRUE,text='Ip1, Ip2, Code, Country, Area1, Area2
"0","16777215","-","-","-","-"
"16777216","16777471","AU","AUSTRALIA","QUEENSLAND","SOUTH BRISBANE"
"16777472","16778239","CN","CHINA","FUJIAN","FUZHOU"
"16778240","16778495","AU","AUSTRALIA","VICTORIA","MELBOURNE"
"16778496","16778751","AU","AUSTRALIA","NEW SOUTH WALES","SYDNEY"')

b$Ip1 <-as.numeric(b$Ip1)
indices <- findInterval(a$ip,b$Ip1,rightmost.closed=FALSE,all.inside=FALSE)
a <- data.frame(a,b[indices,c("Country","Area1","Area2")])