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add GForce support for outer transformations #7600

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0534ed2
add support for outer transformations
ben-schwen Jan 15, 2026
7b853ba
add examples from issue
ben-schwen Jan 15, 2026
0b8220c
refine accepted transformations
ben-schwen Jan 15, 2026
409f454
fix test num
ben-schwen Jan 15, 2026
903e800
adjust test of now optimized fun
ben-schwen Jan 15, 2026
5ca7e41
add rounding functions
ben-schwen Jan 16, 2026
597040e
be more specific about functions
ben-schwen Jan 16, 2026
151dc90
add gamma functions
ben-schwen Jan 16, 2026
851ce78
fix commas
ben-schwen Jan 16, 2026
b40b684
escape GForce for old test
ben-schwen Jan 16, 2026
89f93f9
add test for nesting non-GForce call
ben-schwen Jan 16, 2026
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20 changes: 16 additions & 4 deletions R/data.table.R
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Original file line number Diff line number Diff line change
Expand Up @@ -3410,6 +3410,18 @@ is_constantish = function(q, check_singleton=FALSE) {

.gforce_ops = c("+", "-", "*", "/", "^", "%%", "%/%")

# Outer transformations that can wrap GForce-optimizable expressions
# e.g., sqrt(min(x)) should be optimized to sqrt(gmin(x))
# for the moment we only include unary elementwise functions
.gforce_outer_trans = c("sqrt", "abs", "sign", "floor", "ceiling",
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@MichaelChirico MichaelChirico Jan 15, 2026

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what goes wrong if we just let any generic foo() through here? As long as the "innermost" function is GForce-able

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@ben-schwen ben-schwen Jan 15, 2026

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Things like min(min(x)) should already be quite problematic...

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@ben-schwen ben-schwen Jan 15, 2026

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Our own test suite dislikes e.g. .Internal(mean(x))

"log", "log10", "log2", "log1p", "exp", "expm1",
"cos", "sin", "tan", "acos", "asin", "atan",
"cospi", "sinpi", "tanpi",
"cosh", "sinh", "tanh", "acosh", "asinh", "atanh",
"gamma", "lgamma", "digamma", "trigamma",
"is.na", "is.nan", "is.finite", "is.infinite",
"trunc", "round", "signif")

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@rikivillalba rikivillalba Jan 16, 2026

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Hello:
By setdiff(methods::getGroupMembers("Math"), .gforce_outer_trans) you can add:

"trunc" "cummax" "cummin" "cumprod" "cumsum"
"cospi" "sinpi" "tanpi"
"gamma" "lgamma" "digamma" "trigamma"

Note "log" can take "base = ..." as first argument. trunc can take ... also.

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@ben-schwen ben-schwen Jan 16, 2026

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The cumulative functions won't work. Maybe unary functions was too unprecise. I have added an "elementwise".

Binary functions will optimize as long ppl provide constantish parameters and not variables for the parameters, e.g. log(min(x), 2) works while t<-2; log(min(x), 2) does not

.unwrap_conversions = function(expr) {
while (.is_type_conversion(expr) && length(expr) >= 2L) expr = expr[[2L]]
expr
Expand All @@ -3435,8 +3447,8 @@ is_constantish = function(q, check_singleton=FALSE) {
))
}

# check if arithmetic operator -> recursively validate ALL branches (like in AST)
if (is.symbol(q[[1L]]) && q[[1L]] %chin% .gforce_ops) {
# check if arithmetic operator or outer transformation -> recursively validate ALL branches (like in AST)
if (is.symbol(q[[1L]]) && q[[1L]] %chin% c(.gforce_ops, .gforce_outer_trans)) {
for (i in 2:length(q)) {
if (!.gforce_ok(q[[i]], x, envir)) return(FALSE)
}
Expand Down Expand Up @@ -3467,8 +3479,8 @@ is_constantish = function(q, check_singleton=FALSE) {
return(q)
}

# if arithmetic operator, recursively substitute its operands. we know what branches are valid from .gforce_ok
if (is.symbol(q[[1L]]) && q[[1L]] %chin% .gforce_ops) {
# if arithmetic operator or outer transformation, recursively substitute its operands. we know what branches are valid from .gforce_ok
if (is.symbol(q[[1L]]) && q[[1L]] %chin% c(.gforce_ops, .gforce_outer_trans)) {
for (i in 2:length(q)) {
q[[i]] = .gforce_jsub(q[[i]], names_x, envir)
}
Expand Down
19 changes: 17 additions & 2 deletions inst/tests/tests.Rraw
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Expand Up @@ -14743,7 +14743,7 @@ DT = data.table(
Date2 = .Date(c(17459.1561177987, 17451.1086757995, 17449.0820898537, 17443.1175238448, 17461.0463715783, 17448.1033968224))
)
DT[ , DiffTime := abs(difftime(Date1, Date2, units = 'days'))]
test(2042.4, DT[ , round(mean(DiffTime)), by=Group, verbose=TRUE],
test(2042.4, DT[ , base::round(mean(DiffTime)), by=Group, verbose=TRUE],
data.table(Group=c("A", "B", "C"), V1=structure(c(16, 8, 12), class="difftime", units="days")),
output="Old mean optimization is on, left j unchanged.*GForce.*FALSE")

Expand Down Expand Up @@ -21465,7 +21465,7 @@ test(2362.32, optimize=0:2, dt[, .((max(a) - min(a)) / (max(a) + min(a))), by=b,
test(2362.33, optimize=0:2, dt[, sum(a) / .N, b, verbose=TRUE], output=out)
test(2362.34, optimize=0:2, dt[, mean(a) * 2L + sum(a), b, verbose=TRUE], output=out)
test(2362.35, optimize=0:2, dt[, list(range=max(a)-min(a), avg=mean(a)), by=b, verbose=TRUE], output=out)
test(2362.36, optimize=0:2, dt[, .(max(a)-sqrt(min(a))), by=b, verbose=TRUE], output="GForce FALSE")
test(2362.36, optimize=0:2, dt[, .(max(a)-sqrt(min(a))), by=b, verbose=TRUE], output=out)
test(2362.37, optimize=0:2, dt[, sum(a) %% 2, b, verbose=TRUE], output=out)
test(2362.38, optimize=0:2, dt[, sum(a) %/% 2, b, verbose=TRUE], output=out)
test(2362.39, optimize=0:2, dt[, -sum(a), b, verbose=TRUE], output=out)
Expand All @@ -21484,3 +21484,18 @@ dt = data.table(a=1:4, b=1:2)
test(2362.51, optimize=0:2, dt[, c(list()), b, verbose=TRUE], data.table(b=integer(0L)), output="GForce FALSE")
test(2362.52, optimize=0:2, dt[, c(lapply(.SD, sum), list()), b, verbose=TRUE], output=out)
test(2362.53, optimize=0:2, dt[, list(lapply(.SD, sum), list()), b, verbose=TRUE], output="GForce FALSE")

# outer transformations with GForce, #7594
dt = data.table(x = 1:2, y = 1:10)
out = c('GForce FALSE', 'GForce TRUE')
test(2363.01, optimize=1:2, dt[, sqrt(min(y)), by=x, verbose=TRUE], output=out)
test(2363.02, optimize=1:2, dt[, mean(y)^2, by=x, verbose=TRUE], output=out)
test(2363.03, optimize=1:2, dt[, sqrt(abs(min(y))), by=x, verbose=TRUE], output=out)
test(2363.04, optimize=1:2, dt[, sqrt(min(y)) + 1, by=x, verbose=TRUE], output=out)
test(2363.05, optimize=1:2, dt[, floor(mean(y)), by=x, verbose=TRUE], output=out)
# Transformation around non-GForce expression should NOT optimize
test(2363.11, optimize=2L, dt[, sqrt(y), by=x, verbose=TRUE], output="GForce FALSE")
test(2363.12, optimize=2L, dt[, log1p(abs(y)), by=x, verbose=TRUE], output="GForce FALSE")
dt = data.table(x = 1:2, y = c(NA, NA, NaN, Inf, 1:4))
test(2363.21, optimize=1:2, dt[, is.na(sum(y)), by=x, verbose=TRUE], output=out)
test(2363.22, optimize=1:2, dt[, is.finite(sum(y, na.rm=TRUE)), by=x, verbose=TRUE], output=out)
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