Slower `fsetdiff` vs `dplyr::setdiff`

[cgiachalis]

This came up after code profiling where a loop was calling fsetdiff in each pass among other things.

library(data.table)

olddt <- data.table::data.table(a = paste0(1:10000, "a"))
newdt <- data.table::data.table(a = paste0(1:10010, "a"))


bench::mark(DT = data.table::fsetdiff(newdt, olddt),
            DPLYR = dplyr::setdiff(newdt, olddt),
            min_iterations = 30,
            relative = TRUE)[, 1:5]
# A tibble: 2 × 5
  expression     min  median `itr/sec` mem_alloc
  <bch:expr>   <dbl>   <dbl>     <dbl>     <dbl>
1 DT         10.7859 11.0259    1        1.81242
2 DPLYR       1       1        10.0019   1  

bench::mark(DT = data.table::fsetdiff(newdt, olddt),
            DPLYR = dplyr::setdiff(newdt, olddt),
            min_iterations = 30,
            relative = FALSE)[, 1:5]

# A tibble: 2 × 5
  expression      min   median `itr/sec` mem_alloc
  <bch:expr> <bch:tm> <bch:tm>     <dbl> <bch:byt>
1 DT           4.77ms   5.66ms   171.193     763KB
2 DPLYR         432µs  505.4µs  1799.31      421KB

Session info

sessioninfo::session_info()
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#>  collate  English_United Kingdom.utf8
#>  ctype    English_United Kingdom.utf8
#>  date     2026-06-07
#> 
#> ─ Packages ───────────────────────────────────────────────────────────────────
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