Merging a sum by reference with data.table - r

Question

Let's say I have two data.table, dt_a and dt_b defined as below.
library(data.table)
set.seed(20201111L)
dt_a <- data.table(
foo = c("a", "b", "c")
)
dt_b <- data.table(
bar = sample(c("a", "b", "c"), 10L, replace=TRUE),
value = runif(10L)
)
dt_b[]
## bar value
## 1: c 0.4904536
## 2: c 0.9067509
## 3: b 0.1831664
## 4: c 0.0203943
## 5: c 0.8707686
## 6: a 0.4224133
## 7: a 0.6025349
## 8: b 0.4916672
## 9: a 0.4566726
## 10: b 0.8841110
I want to left join dt_b on dt_a by reference, summing over the multiple match. A way to do so would be to first create a summary of dt_b (thus solving the multiple match issue) and merge if afterwards.
dt_b_summary <- dt_b[, .(value=sum(value)), bar]
dt_a[dt_b_summary, value_good:=value, on=c(foo="bar")]
dt_a[]
## foo value_good
## 1: a 1.481621
## 2: b 1.558945
## 3: c 2.288367
However, this will allow memory to the object dt_b_summary, which is inefficient.
I would like to have the same result by directly joining on dt_b and summing multiple match. I'm looking for something like below, but that won't work.
dt_a[dt_b, value_bad:=sum(value), on=c(foo="bar")]
dt_a[]
## foo value_good value_bad
## 1: a 1.481621 5.328933
## 2: b 1.558945 5.328933
## 3: c 2.288367 5.328933
Anyone knows if there is something possible?

Answer 1

We can use .EACHI with by
library(data.table)
dt_b[dt_a, .(value = sum(value)), on = .(bar = foo), by = .EACHI]
# bar value
#1: a 1.481621
#2: b 1.558945
#3: c 2.288367
If we want to update the original object 'dt_a'
dt_a[, value := dt_b[.SD, sum(value), on = .(bar = foo), by = .EACHI]$V1]
dt_a
# foo value
#1: a 1.481621
#2: b 1.558945
#3: c 2.288367
For multiple columns
dt_b$value1 <- dt_b$value
nm1 <- c('value', 'value1')
dt_a[, (nm1) := dt_b[.SD, lapply(.SD, sum),
on = .(bar = foo), by = .EACHI][, .SD, .SDcols = nm1]]