See vignette("translation-function")
and vignette("translation-verb")
for
details of overall translation technology. Key differences for this backend
are:
SELECT
uses TOP
not LIMIT
Automatically prefixes #
to create temporary tables. Add the prefix
yourself to avoid the message.
Custom types for as.*
functions
Lubridate extraction functions, year()
, month()
, day()
etc
Semi-automated bit <-> boolean translation (see below)
Use simulate_mssql()
with lazy_frame()
to see simulated SQL without
converting to live access database.
simulate_mssql(version = "15.0")
SQL server uses two incompatible types to represent TRUE
and FALSE
values:
The BOOLEAN
type is the result of logical comparisons (e.g. x > y
)
and can be used WHERE
but not to create new columns in SELECT
.
https://docs.microsoft.com/en-us/sql/t-sql/language-elements/comparison-operators-transact-sql
The BIT
type is a special type of numeric column used to store
TRUE
and FALSE
values, but can't be used in WHERE
clauses.
https://learn.microsoft.com/en-us/sql/t-sql/data-types/bit-transact-sql?view=sql-server-ver15
dbplyr does its best to automatically create the correct type when needed, but can't do it 100% correctly because it does not have a full type inference system. This means that you many need to manually do conversions from time to time.
To convert from bit to boolean use x == 1
To convert from boolean to bit use as.logical(if(x, 0, 1))
library(dplyr, warn.conflicts = FALSE)
lf <- lazy_frame(a = TRUE, b = 1, c = 2, d = "z", con = simulate_mssql())
lf %>% head()
#> <SQL>
#> SELECT TOP 6 `df`.*
#> FROM `df`
lf %>% transmute(x = paste(b, c, d))
#> <SQL>
#> SELECT `b` + ' ' + `c` + ' ' + `d` AS `x`
#> FROM `df`
# Can use boolean as is:
lf %>% filter(c > d)
#> <SQL>
#> SELECT `df`.*
#> FROM `df`
#> WHERE (`c` > `d`)
# Need to convert from boolean to bit:
lf %>% transmute(x = c > d)
#> <SQL>
#> SELECT CAST(IIF(`c` > `d`, 1, 0) AS BIT) AS `x`
#> FROM `df`
# Can use boolean as is:
lf %>% transmute(x = ifelse(c > d, "c", "d"))
#> <SQL>
#> SELECT IIF(`c` > `d`, 'c', 'd') AS `x`
#> FROM `df`