dbplyr, dplyr, and functions with no SQL equivalents [eg `slice()`] - sql

Question

library(tidyverse)
con <- DBI::dbConnect(RSQLite::SQLite(), ":memory:")
copy_to(con, mtcars)
mtcars2 <- tbl(con, "mtcars")
I can create this mock SQL database above. And it's very cool that I can perform standard dplyr functions on this "database":
mtcars2 %>%
group_by(cyl) %>%
summarise(mpg = mean(mpg, na.rm = TRUE)) %>%
arrange(desc(mpg))
#> # Source: lazy query [?? x 2]
#> # Database: sqlite 3.29.0 [:memory:]
#> # Ordered by: desc(mpg)
#> cyl mpg
#> <dbl> <dbl>
#> 1 4 26.7
#> 2 6 19.7
#> 3 8 15.1
It appears I'm unable to use dplyr functions that have no direct SQL equivalents, (eg dplyr::slice()). In the case of slice() I can use the alternative combination of filter() and row_number() to get the same results as just using slice(). But what happens when there's not such an easy workaround?
mtcars2 %>% slice(1:5)
#>Error in UseMethod("slice_") :
#> no applicable method for 'slice_' applied to an object of class
#> "c('tbl_SQLiteConnection', 'tbl_dbi', 'tbl_sql', 'tbl_lazy', 'tbl')"
When dplyr functions have no direct SQL equivalents can I force their use with dbplyr, or is the only option to get creative with dplyr verbs that do have SQL equivalents, or just write the SQL directly (which is not my preferred solution)?

Answer 1

I understood this question: How can I make slice() work for SQL databases? This is different from "forcing their use" but still might work in your case.
The example below shows how to implement a "poor man's" variant of slice() that works on the database. We still need to do the legwork and implement it with verbs that work on the database, but then we can use it similarly to data frames.
Read more about S3 classes in http://adv-r.had.co.nz/OO-essentials.html#s3.
library(tidyverse)
con <- DBI::dbConnect(RSQLite::SQLite(), ":memory:")
copy_to(con, mtcars)
mtcars2 <- tbl(con, "mtcars")
# mtcars2 has a class attribute
class(mtcars2)
#> [1] "tbl_SQLiteConnection" "tbl_dbi" "tbl_sql"
#> [4] "tbl_lazy" "tbl"
# slice() is an S3 method
slice
#> function(.data, ..., .preserve = FALSE) {
#> UseMethod("slice")
#> }
#> <bytecode: 0x560a03460548>
#> <environment: namespace:dplyr>
# we can implement a "poor man's" variant of slice()
# for the particular class. (It doesn't work quite the same
# in all cases.)
#' #export
slice.tbl_sql <- function(.data, ...) {
rows <- c(...)
.data %>%
mutate(...row_id = row_number()) %>%
filter(...row_id %in% !!rows) %>%
select(-...row_id)
}
mtcars2 %>%
slice(1:5)
#> # Source: lazy query [?? x 11]
#> # Database: sqlite 3.29.0 [:memory:]
#> mpg cyl disp hp drat wt qsec vs am gear carb
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4
#> 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4
#> 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1
#> 4 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1
#> 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2
Created on 2019-12-07 by the reprex package (v0.3.0)