Connect to Live SAS Data Sets Data in PostGresSQL Interface through CData Connect AI
There are a vast number of PostgreSQL clients available on the Internet. PostgreSQL is a popular interface for data access. When you pair PostgreSQL with CData Connect AI, you gain database-like access to live SAS Data Sets data from PostgreSQL. In this article, we walk through the process of connecting to SAS Data Sets data in Connect AI and establishing a connection between Connect AI and PostgreSQL using a TDS foreign data wrapper (FDW).
CData Connect AI provides a pure SQL Server interface for SAS Data Sets, allowing you to query data from SAS Data Sets without replicating the data to a natively supported database. Using optimized data processing out of the box, CData Connect AI pushes all supported SQL operations (filters, JOINs, etc.) directly to SAS Data Sets, leveraging server-side processing to return the requested SAS Data Sets data quickly.
Connect to SAS Data Sets in Connect AI
CData Connect AI uses a straightforward, point-and-click interface to connect to data sources.
- Log into Connect AI, click Sources, and then click Add Connection
- Select "SAS Data Sets" from the Add Connection panel
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Enter the necessary authentication properties to connect to SAS Data Sets.
Set the following connection properties to connect to your SAS DataSet files:
Connecting to Local Files
- Set the Connection Type to "Local." Local files support SELECT, INSERT, and DELETE commands.
- Set the URI to a folder containing SAS files, e.g. C:\PATH\TO\FOLDER\.
Connecting to Cloud-Hosted SAS DataSet Files
While the driver is capable of pulling data from SAS DataSet files hosted on a variety of cloud data stores, INSERT, UPDATE, and DELETE are not supported outside of local files in this driver.
Set the Connection Type to the service hosting your SAS DataSet files. A unique prefix at the beginning of the URI connection property is used to identify the cloud data store and the remainder of the path is a relative path to the desired folder (one table per file) or single file (a single table). For more information, refer to the Getting Started section of the Help documentation.
- Click Save & Test
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Navigate to the Permissions tab in the Add SAS Data Sets Connection page and update the User-based permissions.
Add a Personal Access Token
When connecting to Connect AI through the REST API, the OData API, or the Virtual SQL Server, a Personal Access Token (PAT) is used to authenticate the connection to Connect AI. It is best practice to create a separate PAT for each service to maintain granularity of access.
- Click on the Gear icon () at the top right of the Connect AI app to open the settings page.
- On the Settings page, go to the Access Tokens section and click Create PAT.
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Give the PAT a name and click Create.
- The personal access token is only visible at creation, so be sure to copy it and store it securely for future use.
With the connection configured and a PAT generated, you are ready to connect to SAS Data Sets data from PostgreSQL.
Build the TDS Foreign Data Wrapper
The Foreign Data Wrapper can be installed as an extension to PostgreSQL, without recompiling PostgreSQL. The tds_fdw extension is used as an example (https://github.com/tds-fdw/tds_fdw).
- You can clone and build the git repository via something like the following view source:
sudo apt-get install git git clone https://github.com/tds-fdw/tds_fdw.git cd tds_fdw make USE_PGXS=1 sudo make USE_PGXS=1 install
Note: If you have several PostgreSQL versions and you do not want to build for the default one, first locate where the binary for pg_config is, take note of the full path, and then append PG_CONFIG=after USE_PGXS=1 at the make commands. - After you finish the installation, then start the server:
sudo service postgresql start
- Then go inside the Postgres database
psql -h localhost -U postgres -d postgres
Note: Instead of localhost you can put the IP where your PostgreSQL is hosted.
Connect to SAS Data Sets data as a PostgreSQL Database and query the data!
After you have installed the extension, follow the steps below to start executing queries to SAS Data Sets data:
- Log into your database.
- Load the extension for the database:
CREATE EXTENSION tds_fdw;
- Create a server object for SAS Data Sets data:
CREATE SERVER "SASDataSets1" FOREIGN DATA WRAPPER tds_fdw OPTIONS (servername'tds.cdata.com', port '14333', database 'SASDataSets1');
- Configure user mapping with your email and Personal Access Token from your Connect AI account:
CREATE USER MAPPING for postgres SERVER "SASDataSets1" OPTIONS (username '[email protected]', password 'your_personal_access_token' );
- Create the local schema:
CREATE SCHEMA "SASDataSets1";
- Create a foreign table in your local database:
#Using a table_name definition: CREATE FOREIGN TABLE "SASDataSets1".restaurants ( id varchar, borough varchar) SERVER "SASDataSets1" OPTIONS(table_name 'SASDataSets.restaurants', row_estimate_method 'showplan_all'); #Or using a schema_name and table_name definition: CREATE FOREIGN TABLE "SASDataSets1".restaurants ( id varchar, borough varchar) SERVER "SASDataSets1" OPTIONS (schema_name 'SASDataSets', table_name 'restaurants', row_estimate_method 'showplan_all'); #Or using a query definition: CREATE FOREIGN TABLE "SASDataSets1".restaurants ( id varchar, borough varchar) SERVER "SASDataSets1" OPTIONS (query 'SELECT * FROM SASDataSets.restaurants', row_estimate_method 'showplan_all'); #Or setting a remote column name: CREATE FOREIGN TABLE "SASDataSets1".restaurants ( id varchar, col2 varchar OPTIONS (column_name 'borough')) SERVER "SASDataSets1" OPTIONS (schema_name 'SASDataSets', table_name 'restaurants', row_estimate_method 'showplan_all');
- You can now execute read/write commands to SAS Data Sets:
SELECT id, borough FROM "SASDataSets1".restaurants;
More Information & Free Trial
Now, you have created a simple query from live SAS Data Sets data. For more information on connecting to SAS Data Sets (and more than 200 other data sources), visit the Connect AI page. Sign up for a free trial and start working with live SAS Data Sets data in PostgreSQL.