Joining two data.tables in R based on multiple keys and duplicate entries

Question

I am trying to join two data.tables in R base don multiple setkeys and which have repeated entries. As an example

>DT1
ID  state Month Day Year
1   IL    Jan   3   2013 
1   IL    Jan   3   2014
1   IL    Jan   3   2014
1   IL    Jan   10  2014
1   IL    Jan   11  2013
1   IL    Jan   30  2013
1   IL    Jan   30  2013
1   IL    Feb   2   2013
1   IL    Feb   2   2014
1   IL    Feb   3   2013
1   IL    Feb   3   2014

>DT2
state Month   Day   Year  Tavg
  IL    Jan    1    2013    13
  IL    Jan    2    2013    19
  IL    Jan    3    2013    22
  IL    Jan    4    2013    23
  IL    Jan    5    2013    26
  IL    Jan    6    2013    24
  IL    Jan    7    2013    27
  IL    Jan    8    2013    32
  IL    Jan    9    2013    36
  ...   ...    ..   ...      ... 
  ...   ...    ..   ...      ... 
  IL    Dec 31  2013    33

I would like to add the "Tavg" values of DT2 to the corresponding dates in DT1 For example, all entries in DT1 that are on Jan 3 2013 need to have Tavg 13 in an additional column.

I tried the following setkey(DT1, state, Month, Day, Year) and same for DT2 followed by a Join operation DT1[DT2, nomatch=0, allow.cartesian=TRUE But it didn't work

Solution

Just helped a friend with this (he couldn't find a good Stack Overflow answer) so I figured this question needed a more complete "toy" answer.

Here's a couple of simple data tables with one mismatched key:

dt1 <- data.table(a = LETTERS[1:5],b=letters[1:5],c=1:5)
dt2 <- data.table(c = LETTERS[c(1:4,6)],b=letters[1:5],a=6:10)

And here's several multiple key merge options:

merge(dt1,dt2,by.x=c("a","b"),by.y=c("c","b")) #Inner Join
merge(dt1,dt2,by.x=c("a","b"),by.y=c("c","b"),all=T) #Outer Join

setkey(dt1,a,b)
setkey(dt2,c,b)

dt2[dt1] #Left Join (if dt1 is the "left" table)
dt1[dt2] #Right Join (if dt1 is the "left" table)