Joining two data.table I can specify the table I want the column from, like
X[Y, i.id] # `id` is taken from Y
My problem is that I have a big table with ~80 columns. Every night a data refresh happens and, according to some parameters, some rows get replaced by a new version of the table (same table, just new data).
current <- data.table(id=1:4, var=1:4, var2=1:4, key="id")
new <- data.table(id=1:4, var=11:14, var2=11:14, key="id")
current[new[c(1,3)], `:=`(var=i.var, var2=i.var2)]
> current
id var var2
1: 1 11 11
2: 2 2 2
3: 3 13 13
4: 4 4 4
As I said, in my real case, I have much more columns so (besides rbind()ing pieces of the two tables) I wonder how can I select all the columns of the data.table
used in a join as the i argument? I could spend an half an hour in hard coding all of them but it wouldn't be a maintainable code (in case new columns get added to the tables in future).
How about constructing the j-expression
and just eval
'ing it?
nc = names(current)[-1L]
nn = paste0("i.", nc)
expr = lapply(nn, as.name)
setattr(expr, 'names', nc)
expr = as.call(c(quote(`:=`), expr))
> current[new[c(1,3)], eval(expr)]
> current
## id var var2
## 1: 1 11 11
## 2: 2 2 2
## 3: 3 13 13
## 4: 4 4 4
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