splitting a data.table, then modifying by reference - r

Question

I have a use-case where I need to split a data.table, then apply different modify-by-reference operations to each partition. However, splitting forces copying of each table.
Here's a toy example on the iris dataset:
#split the data
DT <- data.table(iris)
out <- split(DT, DT$Species)
#assign partitions to global environment
NAMES <- as.character(unique(DT$Species))
lapply(seq_along(out), function(x) {
assign(NAMES[x], out[[x]], envir=.GlobalEnv)})
#modify by reference, same function applied to different columns for different partitions
#would do this programatically in real use case
virginica[ ,summ:=sum(Petal.Length)]
setosa[ ,summ:=sum(Petal.Width)]
#rbind all (again, programmatic)
do.call(rbind, list(virginica, setosa))
Then I get the following warning:
Warning message:
In `[.data.table`(out$virginica, , `:=`(cumPedal, cumsum(Petal.Width))) :
Invalid .internal.selfref detected and fixed by taking a copy of the whole table so that := can add this new column by reference.
I know this is related to putting data.tables in lists. Is there any workaround for this use case, or a way to avoid using split? Note that in the real case, I want to modify by reference programatically, so hardcoding a solution won't work.

Answer 1

Here's an example of using .EACHI to achieve what it sounds like you're trying to do:
## Create a data.table that indicates the pairs of keys to columns
New <- data.table(
Species = c("virginica", "setosa", "versicolor"),
FunCol = c("Petal.Length", "Petal.Width", "Sepal.Length"))
## Set the key of your original data.table
setkey(DT, Species)
## Now use .EACHI
DT[New, temp := cumsum(get(FunCol)), by = .EACHI][]
# Sepal.Length Sepal.Width Petal.Length Petal.Width Species temp
# 1: 5.1 3.5 1.4 0.2 setosa 0.2
# 2: 4.9 3.0 1.4 0.2 setosa 0.4
# 3: 4.7 3.2 1.3 0.2 setosa 0.6
# 4: 4.6 3.1 1.5 0.2 setosa 0.8
# 5: 5.0 3.6 1.4 0.2 setosa 1.0
# ---
# 146: 6.7 3.0 5.2 2.3 virginica 256.9
# 147: 6.3 2.5 5.0 1.9 virginica 261.9
# 148: 6.5 3.0 5.2 2.0 virginica 267.1
# 149: 6.2 3.4 5.4 2.3 virginica 272.5
# 150: 5.9 3.0 5.1 1.8 virginica 277.6
## Basic verification
head(cumsum(DT["setosa", ]$Petal.Width), 5)
# [1] 0.2 0.4 0.6 0.8 1.0
tail(cumsum(DT["virginica", ]$Petal.Length), 5)