Getting Started with Microsoft SQL Server on Azure

February 11, 2016

(This article was first published on Revolutions, and kindly contributed to R-bloggers)

by Joseph Rickert

If you are an R user and work for an enterprise where Microsoft SQL server is important, it is extremely helpful to have easy access to SQL Server databases. Over the past year, we have run several posts on this topic including a comprehensive four part series from Microsoft's Gregory Vandenbrouck on using various flavors of SQL with Azure as a data source (Part1, Part2, Part3 and Part4) as well as several posts on using the advanced features of Microsoft R Server (formerly Revolution R Enterprise) with SQL Server 2016. (See for example this recent post Credit Card Fraud Detection with SQL Server 2016 R Services). 

In this post, I would just like to describe how to connect to an Azure SQL database from your local R session. Setting up an Azure hosted database is the easiest way I know for an R user to get Azure_Portalstarted with Microsoft SQL server. You don't have to install the database, and very little SQL knowledge is necessary to begin working with a database.  All of the heavy lifting is done by the Azure platform.

The only prerequisite is to get an Azure account. If you don't already have an account, signing up for a free trial account which you can do here will give you enough credits to experiment with working with SQL Server from R.

The first step after getting an account is to login to the Azure portal. You should see a screen that looks like the figure at right.
From here, clicking on the SQL database icon and selecting "New" should bring you to a screen that looks similar to the one  below. The first time you create a database you will be asked to provide a server admin logon name and a password. Remember these because they will be necessary to form your complete connection string. 




Next, select a name for your database, and click on the tab "blank database". This will bring you to a screen that looks like the figure below. Copy the text in the the "ODBC" box. This is everything that you need to form a complete connection string except for the password you created above.  Note that text in the "ODBC" box will show your logon ID but not your password.



Now that the preliminaries are out of the way, you should be able to populate your database with the following code. The RODBC package is used to communicate with SQL Server. The nycflights13 package provides a convenient test data set with over 300,000 rows and 16 columns. The connection string is what I copied  from the Azure ODBC text box described above, except that I have replaced my login ID with the text "my_ID". (Let this serve as a gentle reminder not to store your credentials in the source code. ) The command odbcDriverConnect() opens the ODBC connection to the database, but the real work is done sqlSave() that populates the database with the flights data. This took about 40 minutes on running from my RStudio R script executing on my lenovo Thinkpad.

library(RODBC)           # Provides database connectivity
library(nycflights13)    # SOme sample data
library(dplyr)           # only used for nice format of Head() function here
# The Connection string comes from the Azure ODBC text box
connectionString <- "Driver={SQL Server Native Client 11.0};,1433;Database=Test_R2;[email protected];Pwd={your_password_here};Encrypt=yes;TrustServerCertificate=no;Connection Timeout=30;"
#Open your RODBC connection
myconn <- odbcDriverConnect(connectionString)
# Get some data
# We use the New York City 2013 Flight Data from thepackage nycflights12
#[1] 336776     16
# Source: local data frame [6 x 16]
# year month   day dep_time dep_delay arr_time arr_delay carrier tailnum
# (int) (int) (int)    (int)     (dbl)    (int)     (dbl)   (chr)   (chr)
# 1  2013     1     1      517         2      830        11      UA  N14228
# 2  2013     1     1      533         4      850        20      UA  N24211
# 3  2013     1     1      542         2      923        33      AA  N619AA
# 4  2013     1     1      544        -1     1004       -18      B6  N804JB
# 5  2013     1     1      554        -6      812       -25      DL  N668DN
# 6  2013     1     1      554        -4      740        12      UA  N39463
# Variables not shown: flight (int), origin (chr), dest (chr), air_time (dbl),
# distance (dbl), hour (dbl), minute (dbl)
# Save the table to the database
sqlSave(channel=myconn, dat=flights, tablename = "flightsTbl")

The following code executes a SQL query and displays some of the data returned. odbcCloseAll() closes the ODBC connection. 

# Fetch movies with ratings GT 3 from Azure SQL DB
sqlQuery_m1 <- "SELECT * FROM flightsTbl WHERE month < 3"
m1 <- sqlQuery(myconn, sqlQuery_m1)
# rownames year month day dep_time dep_delay arr_time arr_delay carrier
# 1        1 2013     1   1      517         2      830        11      UA
# 2        2 2013     1   1      533         4      850        20      UA
# 3        3 2013     1   1      542         2      923        33      AA
# 4        4 2013     1   1      544        -1     1004       -18      B6
# 5        5 2013     1   1      554        -6      812       -25      DL
# 6        6 2013     1   1      554        -4      740        12      UA
# tailnum flight origin dest air_time distance hour minute
# 1  N14228   1545    EWR  IAH      227     1400    5     17
# 2  N24211   1714    LGA  IAH      227     1416    5     33
# 3  N619AA   1141    JFK  MIA      160     1089    5     42
# 4  N804JB    725    JFK  BQN      183     1576    5     44
# 5  N668DN    461    LGA  ATL      116      762    5     54
# 6  N39463   1696    EWR  ORD      150      719    5     54
#51955    17

To go further, have a look at this tutorial on writing Microsoft SQL queries, or get a more in depth introduction to Microsoft SQL Server here.


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