Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

gsum works on int64 column, closes #1647 #3464 #3737

Merged
merged 3 commits into from
Aug 14, 2019
Merged
Show file tree
Hide file tree
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 2 additions & 0 deletions NEWS.md
Original file line number Diff line number Diff line change
Expand Up @@ -226,6 +226,8 @@

26. Column binding of zero column `data.table` will now work as expected, [#3334](https://github.com/Rdatatable/data.table/issues/3334). Thanks to @kzenstratus for the report.

27. `integer64` sum-by-group is now properly optimized, [#1647](https://github.com/Rdatatable/data.table/issues/1647), [#3464](https://github.com/Rdatatable/data.table/issues/3464). Thanks to @mlandry22-h2o for the report.

#### NOTES

1. `rbindlist`'s `use.names="check"` now emits its message for automatic column names (`"V[0-9]+"`) too, [#3484](https://github.com/Rdatatable/data.table/pull/3484). See news item 5 of v1.12.2 below.
Expand Down
14 changes: 14 additions & 0 deletions inst/tests/tests.Rraw
Original file line number Diff line number Diff line change
Expand Up @@ -15657,6 +15657,20 @@ test(2076.02, X[on=Y], data.table(a=2:3, b=c(2L,NA_integer_), d=2:1))
test(2076.03, X[on=3], error="When on= is provided but not i=, on= must be a named list or data.table|frame, and a natural join")
test(2076.04, X[on=list(3)], error="When on= is provided but not i=, on= must be a named list or data.table|frame, and a natural join")

# gsum int64 support #1647, #3464
if (test_bit64) {
d = data.table(g=1:2, i32=c(2L,-1L,3L,4L), i64=as.integer64(c(2L,-1L,3L,4L)))
int64_int32_match = function(x, y) isTRUE(all.equal(lapply(x, as.integer), lapply(y, as.integer)))
test(2077.01, int64_int32_match(d[, sum(i32), g], d[, sum(i64), g]))
test(2077.02, int64_int32_match(d[, sum(i32, na.rm=TRUE), g], d[, sum(i64, na.rm=TRUE), g]))
d[3L, c("i32","i64") := list(NA_integer_, as.integer64(NA))] # some NA group
test(2077.03, int64_int32_match(d[, sum(i32), g], d[, sum(i64), g]))
test(2077.04, int64_int32_match(d[, sum(i32, na.rm=TRUE), g], d[, sum(i64, na.rm=TRUE), g]))
d[1L, c("i32","i64") := list(NA_integer_, as.integer64(NA))] # all NA group
test(2077.05, int64_int32_match(d[, sum(i32), g], d[, sum(i64), g]))
test(2077.06, int64_int32_match(d[, sum(i32, na.rm=TRUE), g], d[, sum(i64, na.rm=TRUE), g]))
}


###################################
# Add new tests above this line #
Expand Down
115 changes: 87 additions & 28 deletions src/gsumm.c
Original file line number Diff line number Diff line change
Expand Up @@ -426,37 +426,96 @@ SEXP gsum(SEXP x, SEXP narmArg)
}
} break;
case REALSXP: {
const double *restrict gx = gather(x, &anyNA);
ans = PROTECT(allocVector(REALSXP, ngrp));
double *restrict ansp = REAL(ans);
memset(ansp, 0, ngrp*sizeof(double));
if (!narm || !anyNA) {
#pragma omp parallel for num_threads(getDTthreads())
for (int h=0; h<highSize; h++) {
double *restrict _ans = ansp + (h<<shift);
for (int b=0; b<nBatch; b++) {
const int pos = counts[ b*highSize + h ];
const int howMany = ((h==highSize-1) ? (b==nBatch-1?lastBatchSize:batchSize) : counts[ b*highSize + h + 1 ]) - pos;
const double *my_gx = gx + b*batchSize + pos;
const uint16_t *my_low = low + b*batchSize + pos;
for (int i=0; i<howMany; i++) {
_ans[my_low[i]] += my_gx[i]; // let NA propagate when !narm
if (!INHERITS(x, char_integer64)) {
const double *restrict gx = gather(x, &anyNA);
ans = PROTECT(allocVector(REALSXP, ngrp));
double *restrict ansp = REAL(ans);
memset(ansp, 0, ngrp*sizeof(double));
if (!narm || !anyNA) {
#pragma omp parallel for num_threads(getDTthreads())
for (int h=0; h<highSize; h++) {
double *restrict _ans = ansp + (h<<shift);
for (int b=0; b<nBatch; b++) {
const int pos = counts[ b*highSize + h ];
const int howMany = ((h==highSize-1) ? (b==nBatch-1?lastBatchSize:batchSize) : counts[ b*highSize + h + 1 ]) - pos;
const double *my_gx = gx + b*batchSize + pos;
const uint16_t *my_low = low + b*batchSize + pos;
for (int i=0; i<howMany; i++) {
_ans[my_low[i]] += my_gx[i]; // let NA propagate when !narm
}
}
}
} else {
// narm==true and anyNA==true
#pragma omp parallel for num_threads(getDTthreads())
for (int h=0; h<highSize; h++) {
double *restrict _ans = ansp + (h<<shift);
for (int b=0; b<nBatch; b++) {
const int pos = counts[ b*highSize + h ];
const int howMany = ((h==highSize-1) ? (b==nBatch-1?lastBatchSize:batchSize) : counts[ b*highSize + h + 1 ]) - pos;
const double *my_gx = gx + b*batchSize + pos;
const uint16_t *my_low = low + b*batchSize + pos;
for (int i=0; i<howMany; i++) {
const double elem = my_gx[i];
if (!ISNAN(elem)) _ans[my_low[i]] += elem;
}
}
}
}
} else {
// narm==true and anyNA==true
#pragma omp parallel for num_threads(getDTthreads())
for (int h=0; h<highSize; h++) {
double *restrict _ans = ansp + (h<<shift);
for (int b=0; b<nBatch; b++) {
const int pos = counts[ b*highSize + h ];
const int howMany = ((h==highSize-1) ? (b==nBatch-1?lastBatchSize:batchSize) : counts[ b*highSize + h + 1 ]) - pos;
const double *my_gx = gx + b*batchSize + pos;
const uint16_t *my_low = low + b*batchSize + pos;
for (int i=0; i<howMany; i++) {
const double elem = my_gx[i];
if (!ISNAN(elem)) _ans[my_low[i]] += elem;
} else { // int64
const int64_t *restrict gx = gather(x, &anyNA);
ans = PROTECT(allocVector(REALSXP, ngrp));
int64_t *restrict ansp = (int64_t *)REAL(ans);
memset(ansp, 0, ngrp*sizeof(int64_t));
if (!anyNA) {
#pragma omp parallel for num_threads(getDTthreads())
for (int h=0; h<highSize; h++) {
int64_t *restrict _ans = ansp + (h<<shift);
for (int b=0; b<nBatch; b++) {
const int pos = counts[ b*highSize + h ];
const int howMany = ((h==highSize-1) ? (b==nBatch-1?lastBatchSize:batchSize) : counts[ b*highSize + h + 1 ]) - pos;
const int64_t *my_gx = gx + b*batchSize + pos;
const uint16_t *my_low = low + b*batchSize + pos;
for (int i=0; i<howMany; i++) {
_ans[my_low[i]] += my_gx[i]; // does not propagate INT64 for !narm
}
}
}
} else { // narm==true/false and anyNA==true
if (!narm) {
#pragma omp parallel for num_threads(getDTthreads())
for (int h=0; h<highSize; h++) {
int64_t *restrict _ans = ansp + (h<<shift);
for (int b=0; b<nBatch; b++) {
const int pos = counts[ b*highSize + h ];
const int howMany = ((h==highSize-1) ? (b==nBatch-1?lastBatchSize:batchSize) : counts[ b*highSize + h + 1 ]) - pos;
const int64_t *my_gx = gx + b*batchSize + pos;
const uint16_t *my_low = low + b*batchSize + pos;
for (int i=0; i<howMany; i++) {
const int64_t elem = my_gx[i];
if (elem!=INT64_MIN) {
_ans[my_low[i]] += elem;
} else {
_ans[my_low[i]] = INT64_MIN;
break;
}
}
}
}
} else {
#pragma omp parallel for num_threads(getDTthreads())
for (int h=0; h<highSize; h++) {
int64_t *restrict _ans = ansp + (h<<shift);
for (int b=0; b<nBatch; b++) {
const int pos = counts[ b*highSize + h ];
const int howMany = ((h==highSize-1) ? (b==nBatch-1?lastBatchSize:batchSize) : counts[ b*highSize + h + 1 ]) - pos;
const int64_t *my_gx = gx + b*batchSize + pos;
const uint16_t *my_low = low + b*batchSize + pos;
for (int i=0; i<howMany; i++) {
const int64_t elem = my_gx[i];
if (elem!=INT64_MIN) _ans[my_low[i]] += elem;
}
}
}
}
}
Expand Down