CODEWITHSUNDEEP
rr-dbidbplyr
Display name
Display name

Reputation: 4481

How do I `View()` an in-memory table in R with dbplyr? without SQL queries

library(dplyr, warn.conflicts = FALSE)

con <- DBI::dbConnect(RSQLite::SQLite(), ":memory:")
copy_to(con, mtcars)

mtcars2 <- tbl(con, "mtcars")
mtcars2
#> # Source:   table<mtcars> [?? x 11]
#> # Database: sqlite 3.25.3 [: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
#>  6  18.1     6  225    105  2.76  3.46  20.2     1     0     3     1
#>  7  14.3     8  360    245  3.21  3.57  15.8     0     0     3     4
#>  8  24.4     4  147.    62  3.69  3.19  20       1     0     4     2
#>  9  22.8     4  141.    95  3.92  3.15  22.9     1     0     4     2
#> 10  19.2     6  168.   123  3.92  3.44  18.3     1     0     4     4
#> # … with more rows

How do I view a table that is in memory in R? I'm utilizing DBI and dbplyr packages. I'm looking for the spreadsheet view in R Studio that pops up when you issue a command such as View(mtcars). And I really want to only view the first 10 or 20 rows of a table. A lot of the SQL tables I work with are millions of rows, hundreds of columns, and I don't want all that data to display.

Things just seem different enough going from dplyr to dbplyr to slightly confuse me. And if you're wondering why I'm not happy with the console view presented above, because it usually cuts off at about a dozen variables, or however wide your console is. I need to browse all variables (columns), even when my tables are hundreds of columns wide.

# Doesn't really work
mtcars2 %>% View()

Let me also mention I want to avoid having to use direct SQL queries in the answer, if it's even possible. I'm somewhat open to utilizing the collect() function, but it seems very slow when the tables are around size 250K+ rows, 100+ columns.

Upvotes: 1

Views: 494

Answers (1)

Display name
Display name

Reputation: 4481

@DiceboyT pointed out the solution

mtcars2 %>% head(10) %>% collect() %>% View()

Upvotes: 2

Related Questions