if_else_block: Build a sequence of statements simulating an if/else block-`if(){}else{}`.

Description

This device uses expression-ifelse(,,) to simulate the more powerful per-row block-if(){}else{}. The difference is expression-ifelse(,,) can choose per-row what value to express, whereas block-if(){}else{} can choose per-row where to assign multiple values. By simulation we mean: a sequence of quoted mutate expressions are emitted that implement the transform. These expressions can then be optimized into a minimal number of no-dependency blocks by extend_se for efficient execution. The idea is the user can write legible code in this notation, and the translation turns it into safe and efficient code suitable for execution either on data.frames or at a big data scale using RPostgreSQL or sparklyr.

Usage

if_else_block(testexpr, ..., thenexprs = NULL, elseexprs = NULL)

Arguments

testexpr

character containing the test expression.

...

force later arguments to bind by name.

thenexprs

named character then assignments (altering columns, not creating).

elseexprs

named character else assignments (altering columns, not creating).

Value

sequence of statements for extend_se().

Details

Note: ifebtest_* is a reserved column name for this procedure.

Examples

Run this code

# NOT RUN {
if (requireNamespace("DBI", quietly = TRUE) && requireNamespace("RSQLite", quietly = TRUE)) {
  # Example: clear one of a or b in any row where both are set.
  # Land random selections early to avoid SQLite bug.
  my_db <- DBI::dbConnect(RSQLite::SQLite(), ":memory:")
  d <- rq_copy_to(
    my_db,
    'd',
    data.frame(i = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10),
               a = c(0, 0, 1, 1, 1, 1, 1, 1, 1, 1),
               b = c(0, 1, 0, 1, 1, 1, 1, 1, 1, 1),
               r = runif(10),
               edited = 0),
    temporary=TRUE, overwrite=TRUE)

  program <- if_else_block(
    testexpr = qe((a+b)>1),
    thenexprs = c(
      if_else_block(
        testexpr = qe(r >= 0.5),
        thenexprs = qae(a %:=% 0),
        elseexprs = qae(b %:=% 0)),
      qae(edited %:=% 1)))
  print(program)

  optree <- extend_se(d, program)
  cat(format(optree))

  sql <- to_sql(optree, my_db)
  cat(sql)

  print(DBI::dbGetQuery(my_db, sql))

  # Why we need to land the random selection early
  # for SQLIte:
  q <- "SELECT r AS r1, r AS r2 FROM (
          SELECT random() AS r FROM (
             SELECT * from ( VALUES(1),(2) )
          ) a
       ) b"
  print(DBI::dbGetQuery(my_db, q))

  DBI::dbDisconnect(my_db)
}

# }