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Get the Report →Analyze Azure Data Catalog Data in R
Create data visualizations and use high-performance statistical functions to analyze Azure Data Catalog data in Microsoft R Open.
Access Azure Data Catalog data with pure R script and standard SQL. You can use the CData ODBC Driver for Azure Data Catalog and the RODBC package to work with remote Azure Data Catalog data in R. By using the CData Driver, you are leveraging a driver written for industry-proven standards to access your data in the popular, open-source R language. This article shows how to use the driver to execute SQL queries to Azure Data Catalog data and visualize Azure Data Catalog data in R.
Install R
You can complement the driver's performance gains from multi-threading and managed code by running the multithreaded Microsoft R Open or by running R linked with the BLAS/LAPACK libraries. This article uses Microsoft R Open (MRO).
Connect to Azure Data Catalog as an ODBC Data Source
Information for connecting to Azure Data Catalog follows, along with different instructions for configuring a DSN in Windows and Linux environments.
You can optionally set the following to read the different catalog data returned from Azure Data Catalog.
- CatalogName: Set this to the CatalogName associated with your Azure Data Catalog. To get your Catalog name, navigate to your Azure Portal home page > Data Catalog > Catalog Name
Connect Using OAuth Authentication
You must use OAuth to authenticate with Azure Data Catalog. OAuth requires the authenticating user to interact with Azure Data Catalog using the browser. For more information, refer to the OAuth section in the help documentation.
When you configure the DSN, you may also want to set the Max Rows connection property. This will limit the number of rows returned, which is especially helpful for improving performance when designing reports and visualizations.
Windows
If you have not already, first specify connection properties in an ODBC DSN (data source name). This is the last step of the driver installation. You can use the Microsoft ODBC Data Source Administrator to create and configure ODBC DSNs.
Linux
If you are installing the CData ODBC Driver for Azure Data Catalog in a Linux environment, the driver installation predefines a system DSN. You can modify the DSN by editing the system data sources file (/etc/odbc.ini) and defining the required connection properties.
/etc/odbc.ini
[CData AzureDataCatalog Source]
Driver = CData ODBC Driver for Azure Data Catalog
Description = My Description
For specific information on using these configuration files, please refer to the help documentation (installed and found online).
Load the RODBC Package
To use the driver, download the RODBC package. In RStudio, click Tools -> Install Packages and enter RODBC in the Packages box.
After installing the RODBC package, the following line loads the package:
library(RODBC)
Note: This article uses RODBC version 1.3-12. Using Microsoft R Open, you can test with the same version, using the checkpoint capabilities of Microsoft's MRAN repository. The checkpoint command enables you to install packages from a snapshot of the CRAN repository, hosted on the MRAN repository. The snapshot taken Jan. 1, 2016 contains version 1.3-12.
library(checkpoint)
checkpoint("2016-01-01")
Connect to Azure Data Catalog Data as an ODBC Data Source
You can connect to a DSN in R with the following line:
conn <- odbcConnect("CData AzureDataCatalog Source")
Schema Discovery
The driver models Azure Data Catalog APIs as relational tables, views, and stored procedures. Use the following line to retrieve the list of tables:
sqlTables(conn)
Execute SQL Queries
Use the sqlQuery function to execute any SQL query supported by the Azure Data Catalog API.
tables <- sqlQuery(conn, "SELECT DslAddressDatabase, Type FROM Tables WHERE Name = 'FactProductInventory'", believeNRows=FALSE, rows_at_time=1)
You can view the results in a data viewer window with the following command:
View(tables)
Plot Azure Data Catalog Data
You can now analyze Azure Data Catalog data with any of the data visualization packages available in the CRAN repository. You can create simple bar plots with the built-in bar plot function:
par(las=2,ps=10,mar=c(5,15,4,2))
barplot(tables$Type, main="Azure Data Catalog Tables", names.arg = tables$DslAddressDatabase, horiz=TRUE)