Use the CData ODBC Driver for Azure Data Lake Storage in SAS for Real-Time Reporting and Analytics

SAS is a software suite developed for advanced analytics, multivariate analysis, business intelligence, data management, and predictive analytics. When you pair SAS with the CData ODBC Driver for Azure Data Lake Storage, you gain database-like access to live Azure Data Lake Storage data from SAS, expanding your reporting and analytics capabilities. This article explains how to create a library for Azure Data Lake Storage in SAS and create a simple report based on real-time Azure Data Lake Storage data.

The CData ODBC Driver offers unmatched performance for interacting with live Azure Data Lake Storage data in SAS due to optimized data processing built into the driver. When you issue complex SQL queries from SAS to Azure Data Lake Storage, the driver pushes supported SQL operations, like filters and aggregations, directly to Azure Data Lake Storage and utilizes the embedded SQL engine to process unsupported operations (often SQL functions and JOIN operations) client-side. With built-in dynamic metadata querying, you can easily visualize and analyze Azure Data Lake Storage data in SAS.

Connect to Azure Data Lake Storage as an ODBC Data Source

Information for connecting to Azure Data Lake Storage follows, along with different instructions for configuring a DSN in Windows and Linux environments (the ODBC Driver for Azure Data Lake Storage must be installed on the machine hosting the SAS System).

Authenticating to a Gen 1 DataLakeStore Account

Gen 1 uses OAuth 2.0 in Entra ID (formerly Azure AD) for authentication.

For this, an Active Directory web application is required. You can create one as follows:

1. Sign in to your Azure Account through the
2. Select "Entra ID" (formerly Azure AD).
3. Select "App registrations".
4. Select "New application registration".
5. Provide a name and URL for the application. Select Web app for the type of application you want to create.
6. Select "Required permissions" and change the required permissions for this app. At a minimum, "Azure Data Lake" and "Windows Azure Service Management API" are required.
7. Select "Key" and generate a new key. Add a description, a duration, and take note of the generated key. You won't be able to see it again.

To authenticate against a Gen 1 DataLakeStore account, the following properties are required:

• Schema: Set this to ADLSGen1.
• Account: Set this to the name of the account.
• OAuthClientId: Set this to the application Id of the app you created.
• OAuthClientSecret: Set this to the key generated for the app you created.
• TenantId: Set this to the tenant Id. See the property for more information on how to acquire this.
• Directory: Set this to the path which will be used to store the replicated file. If not specified, the root directory will be used.

Authenticating to a Gen 2 DataLakeStore Account

To authenticate against a Gen 2 DataLakeStore account, the following properties are required:

• Schema: Set this to ADLSGen2.
• Account: Set this to the name of the account.
• FileSystem: Set this to the file system which will be used for this account.
• AccessKey: Set this to the access key which will be used to authenticate the calls to the API. See the property for more information on how to acquire this.
• Directory: Set this to the path which will be used to store the replicated file. If not specified, the root directory will be used.

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 Lake Storage 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 ADLS Sys]
Driver = CData ODBC Driver for Azure Data Lake Storage
Description = My Description
Schema = ADLSGen2
Account = myAccount
FileSystem = myFileSystem
AccessKey = myAccessKey
InitiateOAuth = GETANDREFRESH

For specific information on using these configuration files, please refer to the help documentation (installed and found online).

Create a Azure Data Lake Storage Library in SAS

Connect to Azure Data Lake Storage in SAS by adding a library based on the CData ODBC Driver for Azure Data Lake Storage.

1. Open SAS and expand Libraries in the Explorer pane.
2. In the Active Libraries window, right-click and select New.
3. Name your library (odbclib), select ODBC as the Engine, and click to Enable at startup (if you want the library to persist between sessions).
4. Set Data Source to the DSN you previously configured and click OK. 👁 Creating a library for Azure Data Lake Storage in SAS.
   

Create a View from a Azure Data Lake Storage Query

SAS natively supports querying data either using a low-code, point-and-click Query tool or programmatically with PROC SQL and a custom SQL query. When you create a View in SAS, the defining query is executed each time the view is queried. This means that you always query live Azure Data Lake Storage data for reports, charts, and analytics.

Using the Query Tool

1. In SAS, click Tools -> Query
2. Select the table sources and the table(s) you wish to pull data from. Then, click OK. 👁 Selecting table(s) to visualize.
   
3. Select columns and right-click to add filtering, ordering, grouping, etc. 👁 Selecting columns(s) to visualize and configuring the query.
   
4. Create a local view to contain the query results by right-clicking the SQL Query Tool window, selecting Show Query, and clicking Create View. Name the View and click OK. 👁 Create a local view to work with Azure Data Lake Storage data.
   

Using PROC SQL

1. In SAS, navigate to the Editor window.
2. Use PROC SQL to query the data and create a local view.
   NOTE: This procedure creates a view in the Work library. You can optionally specify a library in the create view statement.

   proc sql;
    create view resources_view as
    select 
    fullpath, 
    permission 
    from 
    odbclib.resources 
    where 
    Type = 'FILE';
   quit;
   

3. Click Run -> Submit to execute the query and create a local view.

Report On or Visualize Azure Data Lake Storage Data in SAS

With a local view created, you can report, visualize, or otherwise analyze Azure Data Lake Storage data using the powerful SAS features. Print a simple report using PROC PRINT and create a basic graph based on the data using PROC GCHART.

Print an HTML Report

1. In SAS, navigate to the Editor window.
2. Use PROC PRINT to print an HTML report for the Azure Data Lake Storage Resources data.

   proc print data=resources;
    title "Azure Data Lake Storage Resources Data";
   run;
   

   👁 A simple Azure Data Lake Storage data report.
   

Print a Chart

1. In SAS, navigate to the Editor window.
2. Use PROC GCHART to create a chart for the Resources data.

   proc gchart data=resources;
    pie fullpath / sumvar=permission
    value=arrow
    percent=arrow
    noheading
    percent=inside plabel=(height=12pt)
    slice=inside value=none
    name='ResourcesChart';
   run;
   

   👁 A simple Azure Data Lake Storage data chart.