Cartesian Product using data.table package

Question

Using the data.table package in R, I am trying to create a cartesian product of two data.tables using the merge method as one would do in base R.

In base the following w

Answer 1

The solution from @JoshO'Brien uses merge but below is a similar alternative that does not (AFAIK).

If I understand the documentation in ?data.table::merge correctly, X[Y] should be slightly faster than data.table::merge(X,Y) (as of version 1.8.7). It refers to FAQ 2.12 to address this question, but the FAQ is a little confusing. First, the correct reference should be 1.12, not 2.12. And they don't indicate whether they are referring to the base version of merge or the data.table one, or both. So, this might just end up being a messier-looking solution that is equivalent, or it might be faster.

[Edit from Matthew] Thanks : now improved in v1.8.7 (?merge.data.table, FAQ 1.12 and added new FAQ 2.24)

DT_orders<-data.table(date=as.POSIXct(c('2012-08-28','2012-08-29','2012-08-29','2012-09-01')),
                      first.name=as.character(c('John','John','George','Henry')),
                      last.name=as.character(c('Doe','Doe','Smith','Smith')),
                      qty=c(10,2,50,6),
                      key="first.name,last.name")

# Note that I added a second record to the orders table for John Doe, to make sure it could handle duplicate first/last name combinations.

DT_dates<-data.table(date=seq(from=as.POSIXct('2012-08-28'),
                              to=as.POSIXct('2012-09-07'),by='day'),
                     key="date")

DT_custdates<-data.table(k=1,unique(DT_dates),key="k")[unique(DT_orders)[,list(k=1,first.name,last.name)]][,k:=NULL]