Translate an expression to sql.

translate_sql(..., con = NULL, vars = character(), vars_group = NULL,
  vars_order = NULL, window = TRUE)

translate_sql_(dots, con = NULL, vars_group = NULL, vars_order = NULL,
  window = TRUE)

Arguments

..., dots

Expressions to translate. translate_sql() automatically quotes them for you. translate_sql_() expects a list of already quoted objects.

con

An optional database connection to control the details of the translation. The default, NULL, generates ANSI SQL.

vars

Deprecated. Now call partial_eval() directly.

vars_group, vars_order

Grouping and ordering variables used for windowed functions.

window

Use FALSE to suppress generation of the OVER statement used for window functions. This is necessary when generating SQL for a grouped summary.

Base translation

The base translator, base_sql, provides custom mappings for ! (to NOT), && and & to AND, || and | to OR, ^ to POWER, %>% to %, ceiling to CEIL, mean to AVG, var to VARIANCE, tolower to LOWER, toupper to UPPER and nchar to LENGTH. c() and : keep their usual R behaviour so you can easily create vectors that are passed to sql.

All other functions will be preserved as is. R's infix functions (e.g. %like%) will be converted to their SQL equivalents (e.g. LIKE). You can use this to access SQL string concatenation: || is mapped to OR, but %||% is mapped to ||. To suppress this behaviour, and force errors immediately when dplyr doesn't know how to translate a function it encounters, using set the dplyr.strict_sql option to TRUE.

You can also use sql() to insert a raw sql string.

SQLite translation

The SQLite variant currently only adds one additional function: a mapping from sd() to the SQL aggregation function STDEV.

Examples

# Regular maths is translated in a very straightforward way translate_sql(x + 1)
#> <SQL> "x" + 1.0
translate_sql(sin(x) + tan(y))
#> <SQL> SIN("x") + TAN("y")
# Note that all variable names are escaped translate_sql(like == "x")
#> <SQL> "like" = 'x'
# In ANSI SQL: "" quotes variable _names_, '' quotes strings # Logical operators are converted to their sql equivalents translate_sql(x < 5 & !(y >= 5))
#> <SQL> "x" < 5.0 AND NOT(("y" >= 5.0))
# xor() doesn't have a direct SQL equivalent translate_sql(xor(x, y))
#> <SQL> "x" OR "y" AND NOT ("x" AND "y")
# If is translated into case when translate_sql(if (x > 5) "big" else "small")
#> <SQL> CASE WHEN ("x" > 5.0) THEN ('big') ELSE ('small') END
# Infix functions are passed onto SQL with % removed translate_sql(first %like% "Had%")
#> <SQL> "first" LIKE 'Had%'
translate_sql(first %is% NULL)
#> <SQL> "first" IS
translate_sql(first %in% c("John", "Roger", "Robert"))
#> <SQL> "first" IN ('John', 'Roger', 'Robert')
# And be careful if you really want integers translate_sql(x == 1)
#> <SQL> "x" = 1.0
translate_sql(x == 1L)
#> <SQL> "x" = 1
# If you have an already quoted object, use translate_sql_: x <- quote(y + 1 / sin(t)) translate_sql_(list(x))
#> <SQL> "y" + 1.0 / SIN("t")
# Windowed translation -------------------------------------------- # Known window functions automatically get OVER() translate_sql(mpg > mean(mpg))
#> <SQL> "mpg" > avg("mpg") OVER ()
# Suppress this with window = FALSE translate_sql(mpg > mean(mpg), window = FALSE)
#> <SQL> "mpg" > AVG("mpg")
# vars_group controls partition: translate_sql(mpg > mean(mpg), vars_group = "cyl")
#> <SQL> "mpg" > avg("mpg") OVER (PARTITION BY "cyl")
# and vars_order controls ordering for those functions that need it translate_sql(cumsum(mpg))
#> Warning: Windowed expression 'sum("mpg")' does not have explicit order. #> Please use arrange() to make determinstic.
#> <SQL> sum("mpg") OVER (ROWS UNBOUNDED PRECEDING)
translate_sql(cumsum(mpg), vars_order = "mpg")
#> <SQL> sum("mpg") OVER (ORDER BY "mpg" ROWS UNBOUNDED PRECEDING)