R/translate-sql-string.R
, R/translate-sql-paste.R
, R/translate-sql-helpers.R
, and 2 more
sql_variant.Rd
When creating a package that maps to a new SQL based src, you'll often want to provide some additional mappings from common R commands to the commands that your tbl provides. These three functions make that easy.
sql_substr(f = "SUBSTR")
sql_str_sub(subset_f = "SUBSTR", length_f = "LENGTH", optional_length = TRUE)
sql_paste(default_sep, f = "CONCAT_WS")
sql_paste_infix(default_sep, op, cast)
sql_variant(
scalar = sql_translator(),
aggregate = sql_translator(),
window = sql_translator()
)
sql_translator(..., .funs = list(), .parent = new.env(parent = emptyenv()))
sql_infix(f, pad = TRUE)
sql_prefix(f, n = NULL)
sql_aggregate(f, f_r = f)
sql_aggregate_2(f)
sql_aggregate_n(f, f_r = f)
sql_not_supported(f)
sql_cast(type)
sql_try_cast(type)
sql_log()
sql_cot()
sql_runif(rand_expr, n = n(), min = 0, max = 1)
base_scalar
base_agg
base_win
base_no_win
base_odbc_scalar
base_odbc_agg
base_odbc_win
the name of the sql function as a string
The three families of functions than an SQL variant can supply.
named functions, used to add custom converters from standard
R functions to sql functions. Specify individually in ...
, or
provide a list of .funs
the sql variant that this variant should inherit from.
Defaults to base_agg
which provides a standard set of
mappings for the most common operators and functions.
If TRUE
, the default, pad the infix operator with spaces.
for sql_infix()
, an optional number of arguments to expect.
Will signal error if not correct.
the name of the r function being translated as a string
sql_infix()
and sql_prefix()
create default SQL infix and prefix
functions given the name of the SQL function. They don't perform any input
checking, but do correctly escape their input, and are useful for
quickly providing default wrappers for a new SQL variant.
win_over()
for helper functions for window functions.
sql()
for an example of a more customised sql
conversion function.
# An example of adding some mappings for the statistical functions that
# postgresql provides: http://bit.ly/K5EdTn
postgres_agg <- sql_translator(.parent = base_agg,
cor = sql_aggregate_2("CORR"),
cov = sql_aggregate_2("COVAR_SAMP"),
sd = sql_aggregate("STDDEV_SAMP", "sd"),
var = sql_aggregate("VAR_SAMP", "var")
)
# Next we have to simulate a connection that uses this variant
con <- simulate_dbi("TestCon")
sql_translation.TestCon <- function(x) {
sql_variant(
base_scalar,
postgres_agg,
base_no_win
)
}
translate_sql(cor(x, y), con = con, window = FALSE)
#> Error in cor(x, y): `cor()` is not available in this SQL variant.
translate_sql(sd(income / years), con = con, window = FALSE)
#> Error in sd(income/years): `sd()` is not available in this SQL variant.
# Any functions not explicitly listed in the converter will be translated
# to sql as is, so you don't need to convert all functions.
translate_sql(regr_intercept(y, x), con = con)
#> <SQL> regr_intercept(`y`, `x`)