Gforce grouping var class (#5568)

* copy classes to grouping vars

* add tests

* add different optimization levels to test

* add news

* add output

* fix news

* fix typo

* add NEWS info and tests about attributes

* hone NEWS

* hone comment

* Reframe test annotation

* tweak test

* Second call site

---------

Co-authored-by: Michael Chirico <[email protected]>
Co-authored-by: Michael Chirico <[email protected]>

Author: ben-schwen

NEWS.md

@@ -40,7 +40,7 @@
 
 12. `setDT` is faster for data with many columns, thanks @MichaelChirico for reporting and fixing the issue, [#5426](https://github.com/Rdatatable/data.table/issues/5426).
 
-13. `dcast`gains `value.var.in.dots`, `value.var.in.LHSdots` and `value.var.in.RHSdots` arguments, [#5824](https://github.com/Rdatatable/data.table/issues/5824). This allows the `value.var` variable(s) in `dcast` to be represented by `...` in the formula (if not otherwise mentioned). Thanks to @iago-pssjd for the report and PR.
+13. `dcast` gains `value.var.in.dots`, `value.var.in.LHSdots` and `value.var.in.RHSdots` arguments, [#5824](https://github.com/Rdatatable/data.table/issues/5824). This allows the `value.var` variable(s) in `dcast` to be represented by `...` in the formula (if not otherwise mentioned). Thanks to @iago-pssjd for the report and PR.
 
 14. `fread` loads `.bgz` files directly, [#5461](https://github.com/Rdatatable/data.table/issues/5461). Thanks to @TMRHarrison for the request with proposed fix, and Benjamin Schwendinger for the PR.
 
@@ -62,6 +62,8 @@
 
 8. Adding a list column to an empty `data.table` works consistently with other column types, [#5738](https://github.com/Rdatatable/data.table/issues/5738). Thanks to Benjamin Schwendinger for the report and the fix.
 
+9. In `DT[,j,by]`, `by` retains its attributes (e.g. class) when `j` is GForce optimized, [#5567](https://github.com/Rdatatable/data.table/issues/5567). Thanks to @danwwilson for the report, and @ben-schwen for the PR.
+
 ## NOTES
 
 1. `transform` method for data.table sped up substantially when creating new columns on large tables. Thanks to @OfekShilon for the report and PR. The implemented solution was proposed by @ColeMiller1.

R/data.table.R

@@ -1842,7 +1842,7 @@ replace_dot_alias = function(e) {
     if (use.I) assign(".I", seq_len(nrow(x)), thisEnv)
     ans = gforce(thisEnv, jsub, o__, f__, len__, irows) # irows needed for #971.
     gi = if (length(o__)) o__[f__] else f__
-    g = lapply(grpcols, function(i) groups[[i]][gi])
+    g = lapply(grpcols, function(i) .Call(CsubsetVector, groups[[i]], gi)) # use CsubsetVector instead of [ to preserve attributes #5567
 
     # returns all rows instead of one per group
     nrow_funs = c("gshift")

inst/tests/tests.Rraw

@@ -18585,3 +18585,12 @@ test(2262.5, null.data.table()[, c("a","b") := list(1:2, 3:4)], dt3)
 test(2262.6, set(null.data.table(), j=c("a","b"), value=list(1:2, 3:4)), dt3)
 test(2262.7, data.table(a=1, b=2)[, c("a", "b") := list(NULL, NULL)], null.data.table())
 test(2262.8, data.table(a=1, b=2)[, c("a", "b") := list(NULL)], null.data.table())
+
+# GForce retains attributes in by arguments #5567
+dt = data.table(a=letters[1:4], b=structure(1:4, class = c("class_b", "integer"), att=1), c=structure(c(1L,2L,1L,2L), class = c("class_c", "integer")))
+test(2263.1, options=list(datatable.verbose=TRUE, datatable.optimize=0L), dt[, .N, b], data.table(b=dt$b, N=1L), output="GForce FALSE")
+test(2263.2, options=list(datatable.verbose=TRUE, datatable.optimize=0L), dt[, .N, .(b,c)], data.table(b=dt$b, c=dt$c, N=1L), output="GForce FALSE")
+test(2263.3, options=list(datatable.verbose=TRUE, datatable.optimize=0L), names(attributes(dt[, .N, b]$b)), c("class", "att"), output="GForce FALSE")
+test(2263.4, options=list(datatable.verbose=TRUE, datatable.optimize=Inf), dt[, .N, b], data.table(b=dt$b, N=1L), output="GForce optimized j to")
+test(2263.5, options=list(datatable.verbose=TRUE, datatable.optimize=Inf), dt[, .N, .(b,c)], data.table(b=dt$b, c=dt$c, N=1L), output="GForce optimized j to")
+test(2263.6, options=list(datatable.verbose=TRUE, datatable.optimize=Inf), names(attributes(dt[, .N, b]$b)), c("class", "att"), output="GForce optimized j to")