README

modelc is an R model object to SQL compiler. It generates SQL select statements from linear and generalized linear models.

Its interface currently consists of a single function, modelc, which takes a single input, namely an lm or glm model object.

It currently supports Gaussian and gamma family distributions using log or identity link functions.

To import linear models directly to your SQL Server database, consider using Castpack, which depends on modelc.

Usage

a <- 1:10
b <- 2*1:10 + runif(1) * 1.5
c <- as.factor(1:10)
df <- data.frame(a,b,c)
formula = b ~ a + c

linear_model <- lm(formula, data=df)
modelc(linear_model)

  0.231808555545287 + 2 * `a` + (
    CASE
      WHEN c = 2 THEN -0.00000000000000193216758587821 * c
      WHEN c = 3 THEN -0.000000000000000776180314897008 * c
      WHEN c = 4 THEN -0.000000000000000665297412768863 * c
      WHEN c = 5 THEN -0.00000000000000055441451064072 * c
      WHEN c = 6 THEN -0.000000000000000887620818362638 * c
      WHEN c = 7 THEN -0.000000000000000332648706384432 * c
      WHEN c = 8 THEN -0.00000000000000110994422395641 * c
      WHEN c = 9 THEN -0.00000000000000188723974152839 * c
      WHEN c = 10 THEN 0 * c
    END
  )

glm_model <- glm(formula, data=df, family=Gamma(link="log"))
modelc(glm_model)

  EXP(
    0.557874070609732 + 0.244938197625494 * `a` + (
      CASE
        WHEN c = 2 THEN 0.394878990324516 * c
        WHEN c = 3 THEN 0.536977925025217 * c
        WHEN c = 4 THEN 0.570378881020516 * c
        WHEN c = 5 THEN 0.542936294999294 * c
        WHEN c = 6 THEN 0.476536561025273 * c
        WHEN c = 7 THEN 0.383038044594683 * c
        WHEN c = 8 THEN 0.269593156578649 * c
        WHEN c = 9 THEN 0.140849942185343 * c
        WHEN c = 10 THEN 0 * c
      END
    )
  )

glm_model_idlink <- glm(formula, data=df, family=Gamma(link="identity"))
modelc(glm_model_idlink)

  0.231808555545287 + 2 * `a` + (
    CASE
      WHEN c = 2 THEN 0.00000000000000139594865689472 * c
      WHEN c = 3 THEN -0.000000000000000581567338978993 * c
      WHEN c = 4 THEN -0.00000000000000111588502938831 * c
      WHEN c = 5 THEN 0.000000000000000967650035758108 * c
      WHEN c = 6 THEN -0.00000000000000149265067586469 * c
      WHEN c = 7 THEN -0.000000000000000100985345060517 * c
      WHEN c = 8 THEN -0.0000000000000000673235633736781 * c
      WHEN c = 9 THEN 0.00000000000000199047558220559 * c
      WHEN c = 10 THEN 0 * c
    END
  )

In order to avoid generating invalid SQL, modelc temporarily sets your scipen option to 999.

Installing

install.packages("devtools")
install.packages("remotes")
remotes::install_github("sparkfish/modelc")

Precision

Note that you may encounter minor differences between the output of your R and generated SQL models depending on the precision with which your numeric types are represented in the database. To ensure parity between the two models, numeric types should have a precision of at least 17.

Tests

devtools::test()