Use the CData ODBC Driver for Redshift in SAS for Real-Time Reporting and Analytics



Connect to real-time Redshift data in SAS for reporting, analytics, and visualizations using the CData ODBC Driver for Redshift.

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 Redshift, you gain database-like access to live Redshift data from SAS, expanding your reporting and analytics capabilities. This articles walks through creating a library for Redshift in SAS and creating a simple report based on real-time Redshift data.

The CData ODBC Driver offers unmatched performance for interacting with live Redshift data in SAS due to optimized data processing built into the driver. When you issue complex SQL queries from SAS to Redshift, the driver pushes supported SQL operations, like filters and aggregations, directly to Redshift 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 Redshift data in SAS.

Connect to Redshift as an ODBC Data Source

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

To connect to Redshift, set the following:

  • Server: Set this to the host name or IP address of the cluster hosting the Database you want to connect to.
  • Port: Set this to the port of the cluster.
  • Database: Set this to the name of the database. Or, leave this blank to use the default database of the authenticated user.
  • User: Set this to the username you want to use to authenticate to the Server.
  • Password: Set this to the password you want to use to authenticate to the Server.

You can obtain the Server and Port values in the AWS Management Console:

  1. Open the Amazon Redshift console (http://console.aws.amazon.com/redshift).
  2. On the Clusters page, click the name of the cluster.
  3. On the Configuration tab for the cluster, copy the cluster URL from the connection strings displayed.

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 Redshift 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 Redshift Sys] Driver = CData ODBC Driver for Redshift Description = My Description User = admin Password = admin Database = dev Server = examplecluster.my.us-west-2.redshift.amazonaws.com Port = 5439

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

Create a Redshift Library in SAS

Connect to Redshift in SAS by adding a library based on the CData ODBC Driver for Redshift.

  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.

Create a View from a Redshift 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 Redshift 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.
  3. Select columns and right-click to add filtering, ordering, grouping, etc.
  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.

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 orders_view as
      select 
        shipname, 
        shipcity 
      from 
        odbclib.orders 
      where 
        ShipCountry = 'USA';
    quit;
    
  3. Click Run -> Submit to execute the query and create a local view.

Report On or Visualize Redshift Data in SAS

With a local view created, you can report, visualize, or otherwise analyze Redshift 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 Redshift Orders data.
    proc print data=orders;
      title "Redshift Orders Data";
    run;
    

Print a Chart

  1. In SAS, navigate to the Editor window.
  2. Use PROC GCHART to create a chart for the Orders data.
    proc gchart data=orders;
      pie shipname / sumvar=shipcity
          value=arrow
          percent=arrow
          noheading
          percent=inside plabel=(height=12pt)
          slice=inside value=none
          name='OrdersChart';
    run;
    

Ready to get started?

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Amazon Redshift Icon Amazon Redshift ODBC Driver

The Amazon Redshift ODBC Driver is a powerful tool that allows you to connect with live Amazon Redshift data, directly from any applications that support ODBC connectivity.

Read, write, and update Amazon Redshift data through a standard ODBC Driver interface.