Created
November 12, 2023 08:13
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Exploring duckplyr
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# dataset: https://zenodo.org/records/2594012 | |
df = arrow::read_parquet("personal/Avazu/test.parquet") |> | |
tibble::as_tibble() | |
dim(df) # 4,218,938 X 24 | |
res = | |
bench::mark( | |
# using `duckplyr` | |
duckplyr = { | |
df |> | |
duckplyr::as_duckplyr_df() |> | |
duckplyr::summarise(msp = median(click), | |
.by = c(site_id, device_model, app_domain) | |
) |> | |
duckplyr::arrange(site_id, device_model, app_domain) | |
} | |
, | |
# using `dplyr` | |
dplyr = { | |
df |> | |
dplyr::summarise(msp = median(click), | |
.by = c(site_id, device_model, app_domain) | |
) |> | |
dplyr::arrange(site_id, device_model, app_domain) | |
} | |
, | |
# using `tidytable` (internally uses `data.table`) | |
tidytable = { | |
df |> | |
tidytable::summarise(msp = median(click), | |
.by = c(site_id, device_model, app_domain) | |
) |> | |
tidytable::arrange(site_id, device_model, app_domain) | |
} | |
, | |
iterations = 10, | |
check = FALSE | |
) | |
res |> | |
dplyr::select(min, median, iter_per_sec = `itr/sec`) |> | |
dplyr::mutate(backend = c("duckplyr", "dplyr", "tidytable")) |> | |
dplyr::relocate(backend) | |
# on my laptop: | |
# # A tibble: 3 × 4 | |
# backend min median iter_per_sec | |
# <chr> <bch:tm> <bch:tm> <dbl> | |
# 1 duckplyr 3.99ms 4.76ms 215. | |
# 2 dplyr 3.89s 4.52s 0.225 | |
# 3 tidytable 380.64ms 395.7ms 2.40 | |
sessionInfo() |
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