sqlmlutils/R

sqlmlutils

sqlmlutils is an R package to help execute R code on a SQL database (SQL Server or Azure SQL Database).

Installation

Windows

From command prompt, run

R.exe -e "install.packages('odbc')"
R.exe CMD INSTALL dist/sqlmlutils_1.0.0.zip

OR To build a new package file and install, run

.\buildandinstall.cmd

Linux

R.exe -e "install.packages('odbc')"
R.exe CMD INSTALL dist/sqlmlutils_1.0.0.tar.gz

Getting started

Shown below are the important functions sqlmlutils provides:

connectionInfo                      # Create a connection string for connecting to the SQL database

executeFunctionInSQL                # Execute an R function inside the SQL database
executeScriptInSQL                  # Execute an R script inside the SQL database
executeSQLQuery                     # Execute a SQL query on the database and return the resultant table

createSprocFromFunction             # Create a stored procedure based on a R function inside the SQL database
createSprocFromScript               # Create a stored procedure based on a R script inside the SQL database
checkSproc                          # Check whether a stored procedure exists in the SQL database
dropSproc                           # Drop a stored procedure in the SQL database
executeSproc                        # Execute a stored procedure in the SQL database

sql_install.packages                # Install packages in the SQL database
sql_remove.packages                 # Remove packages from the SQL database
sql_installed.packages              # Enumerate packages that are installed on the SQL database

Examples

Execute In SQL

Execute an R function in database using sp_execute_external_script

library(sqlmlutils)

# For Linux SQL Server, you must specify the ODBC Driver and the username/password because there is no Trusted_Connection/Implied Authentication support yet.
# connection <- connectionInfo(driver= "ODBC Driver 13 for SQL Server", database="AirlineTestDB", uid = "username", pwd = "password")

connection <- connectionInfo()

funcWithArgs <- function(arg1, arg2)
{
    return(c(arg1, arg2))
}
result <- executeFunctionInSQL(connection, funcWithArgs, arg1="result1", arg2="result2")

Generate a linear model without the data leaving the machine

library(sqlmlutils)

# For Linux SQL Server, you must specify the ODBC Driver and the username/password because there is no Trusted_Connection/Implied Authentication support yet.
# connection <- connectionInfo(driver= "ODBC Driver 13 for SQL Server", database="AirlineTestDB", uid = "username", pwd = "password")

connection <-  connectionInfo(database="AirlineTestDB")

linearModel <- function(in_df, xCol, yCol) 
{
    lm(paste0(yCol, " ~ ", xCol), in_df)
}

model <- executeFunctionInSQL(connectionString = connection, func = linearModel, xCol = "CRSDepTime", yCol = "ArrDelay", 
                                inputDataQuery = "SELECT TOP 100 * FROM airline5000")
model

Execute a SQL Query from R

library(sqlmlutils)

# For Linux SQL Server, you must specify the ODBC Driver and the username/password because there is no Trusted_Connection/Implied Authentication support yet.
# connection <- connectionInfo(driver= "ODBC Driver 13 for SQL Server", database="AirlineTestDB", uid = "username", pwd = "password")

connection <-  connectionInfo(database="AirlineTestDB")

dataTable <- executeSQLQuery(connectionString = connection, sqlQuery="SELECT TOP 100 * FROM airline5000")
stopifnot(nrow(dataTable) == 100)
stopifnot(ncol(dataTable) == 30)

Stored Procedures (Sproc)

Create and call a T-SQL stored procedure based on a R function

library(sqlmlutils)

spPredict <- function(inputDataFrame) 
{
    library(RevoScaleR)
    model <- rxLinMod(ArrDelay ~ CRSDepTime, inputDataFrame)
    rxPredict(model, inputDataFrame)
}

# For Linux SQL Server, you must specify the ODBC Driver and the username/password because there is no Trusted_Connection/Implied Authentication support yet.
# connection <- connectionInfo(driver= "ODBC Driver 13 for SQL Server", database="AirlineTestDB", uid = "username", pwd = "password")

connection <- connectionInfo(database="AirlineTestDB")
inputParams <- list(inputDataFrame = "Dataframe")

name = "prediction"

createSprocFromFunction(connectionString = connection, name = name, func = spPredict, inputParams = inputParams)
stopifnot(checkSproc(connectionString = connection, name = name))

predictions <- executeSproc(connectionString = connection, name = name, inputDataFrame = "select ArrDelay, CRSDepTime, DayOfWeek from airline5000")
stopifnot(nrow(predictions) == 5000)

dropSproc(connectionString = connection, name = name)

Package Management

Package management with sqlmlutils is supported in SQL Server 2019 CTP 2.4 and later.

Install and remove packages from the SQL database

library(sqlmlutils)

# For Linux SQL Server, you must specify the ODBC Driver and the username/password because there is no Trusted_Connection/Implied Authentication support yet.
# connection <- connectionInfo(driver= "ODBC Driver 13 for SQL Server", database="AirlineTestDB", uid = "username", pwd = "password")

connection <- connectionInfo(database="AirlineTestDB")

# install glue on sql database
pkgs <- c("glue")
sql_install.packages(connectionString = connection, pkgs, verbose = TRUE, scope="PUBLIC")

# confirm glue is installed on sql database
r <- sql_installed.packages(connectionString = connection, fields=c("Package", "LibPath", "Attributes", "Scope"))
View(r)

# use glue on sql database
useLibraryGlueInSql <- function()
{
    library(glue)

    name <- "Fred"
    age <- 50
    anniversary <- as.Date("1991-10-12")
    glue('My name is {name},',
         'my age next year is {age + 1},',
         'my anniversary is {format(anniversary, "%A, %B %d, %Y")}.')
}

result <- executeFunctionInSQL(connectionString = connection, func = useLibraryGlueInSql)
print(result)

# remove glue from sql database
sql_remove.packages(connectionString = connection, pkgs, scope="PUBLIC")

Install using a local file (instead of from CRAN)

To install from a local file, add "repos=NULL" to sql_install.packages. Testing and uninstall can be done the same way as above.

library(sqlmlutils)

# For Linux SQL Server, you must specify the ODBC Driver and the username/password because there is no Trusted_Connection/Implied Authentication support yet.
# connection <- connectionInfo(driver= "ODBC Driver 13 for SQL Server", database="AirlineTestDB", uid = "username", pwd = "password")

connection <- connectionInfo(database="AirlineTestDB")

# install glue on sql database
pkgPath <- "C:\\glue_1.3.0.zip"
sql_install.packages(connectionString = connection, pkgPath, verbose = TRUE, scope="PUBLIC", repos=NULL)

Notes for Developers

Running the tests on a local machine

1. Make sure a SQL database with an updated ML Services R is running on localhost.
2. Restore the AirlineTestDB from the .bak file in this repo
3. Make sure Trusted (Windows) authentication works for connecting to the database

Notable TODOs and open issues

1. Output Parameter execution did not work with RODBCext. Check whether they work with odbc package.