Question

I have two data.tables, DT and L:

> DT = data.table(x=rep(c("a","b","c"),each=3), y=c(1,3,6), v=1:9,key="x")
> L=data.table(yv=c(1L:8L,12L),lu=c(letters[8:1],letters[12]),key="yv")

> DT
   x y v
1: a 1 1
2: a 3 2
3: a 6 3
4: b 1 4
5: b 3 5
6: b 6 6
7: c 1 7
8: c 3 8
9: c 6 9

> L
   yv lu
1:  1  h
2:  2  g
3:  3  f
4:  4  e
5:  5  d
6:  6  c
7:  7  b
8:  8  a
9: 12  l

I would like to independently look up the corresponding value of lu from L for column y and for column v in DT. The following syntax provides the correct result, but is cumbersome to generate and then understand at a glance later:

> L[setkey(L[setkey(DT,y)],v)][,list(x,y=yv.1,v=yv,lu.1=lu.1,lu.2=lu)]
   x y v lu.1 lu.2
1: a 1 1    h    h
2: a 2 3    g    f
3: a 3 6    f    c
4: b 4 1    e    h
5: b 5 3    d    f
6: b 6 6    c    c
7: c 7 1    b    h
8: c 8 3    a    f
9: c 9 6   NA    c

(Edit: original post had L[setkey(L[setkey(DT,y)],v)][,list(x,y=yv,v=yv.1,lu.1=lu,lu.2=lu.1)] above, which incorrectly mixed up the y and v columns and looked up values.)

In SQL this would be simple/straightforward:

SELECT DT.*, L1.lu AS lu1, L2.lu AS lu2
FROM DT
LEFT JOIN L AS L1 ON DT.y = L1.yv
LEFT JOIN L AS L2 ON DT.v = L2.yv

Is there a more elegant way to use data.table to perform multiple joins? Note that I’m joining one table to another table twice in this example, but I am also interested in joining one table to multiple different tables.

Answer 1

Great question. One trick is that i doesn’t have to be keyed. Only x must be keyed.

There might be better ways. How about this:

> cbind( L[DT[,list(y)]], L[DT[,list(v)]], DT )
   yv lu yv lu x y v
1:  1  h  1  h a 1 1
2:  3  f  2  g a 3 2
3:  6  c  3  f a 6 3
4:  1  h  4  e b 1 4
5:  3  f  5  d b 3 5
6:  6  c  6  c b 6 6
7:  1  h  7  b c 1 7
8:  3  f  8  a c 3 8
9:  6  c  9 NA c 6 9

or, to illustrate, this is the same :

> cbind( L[J(DT$y)], L[J(DT$v)], DT )
   yv lu yv lu x y v
1:  1  h  1  h a 1 1
2:  3  f  2  g a 3 2
3:  6  c  3  f a 6 3
4:  1  h  4  e b 1 4
5:  3  f  5  d b 3 5
6:  6  c  6  c b 6 6
7:  1  h  7  b c 1 7
8:  3  f  8  a c 3 8
9:  6  c  9 NA c 6 9

merge could also be used, if the following feature request was implemented :

FR#2033 Add by.x and by.y to merge.data.table