Connect to Live Bitbucket 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 Bitbucket data from PostgreSQL. In this article, we walk through the process of connecting to Bitbucket 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 Bitbucket, allowing you to query data from Bitbucket 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 Bitbucket, leveraging server-side processing to return the requested Bitbucket data quickly.

Connect to Bitbucket in Connect AI

CData Connect AI uses a straightforward, point-and-click interface to connect to data sources.

1. Log into Connect AI, click Sources, and then click Add Connection

2. Select "Bitbucket" from the Add Connection panel

3. Enter the necessary authentication properties to connect to Bitbucket.

   For most queries, you must set the Workspace. The only exception to this is the Workspaces table, which does not require this property to be set, as querying it provides a list of workspace slugs that can be used to set Workspace. To query this table, you must set Schema to 'Information' and execute the query SELECT * FROM Workspaces>.

   Setting Schema to 'Information' displays general information. To connect to Bitbucket, set these parameters:

   • Schema: To show general information about a workspace, such as its users, repositories, and projects, set this to Information. Otherwise, set this to the schema of the repository or project you are querying. To get a full set of available schemas, query the sys_schemas table.
   • Workspace: Required if you are not querying the Workspaces table. This property is not required for querying the Workspaces table, as that query only returns a list of workspace slugs that can be used to set Workspace.

   Authenticating to Bitbucket

   Bitbucket supports OAuth authentication only. To enable this authentication from all OAuth flows, you must create a custom OAuth application, and set AuthScheme to OAuth.

   Be sure to review the Help documentation for the required connection properties for you specific authentication needs (desktop applications, web applications, and headless machines).

   Creating a custom OAuth application

   From your Bitbucket account:

   1. Go to Settings (the gear icon) and select Workspace Settings.
   2. In the Apps and Features section, select OAuth Consumers.
   3. Click Add Consumer.
   4. Enter a name and description for your custom application.
   5. Set the callback URL:
      • For desktop applications and headless machines, use http://localhost:33333 or another port number of your choice. The URI you set here becomes the CallbackURL property.
      • For web applications, set the callback URL to a trusted redirect URL. This URL is the web location the user returns to with the token that verifies that your application has been granted access.
   6. If you plan to use client credentials to authenticate, you must select This is a private consumer. In the driver, you must set AuthScheme to client.
   7. Select which permissions to give your OAuth application. These determine what data you can read and write with it.
   8. To save the new custom application, click Save.
   9. After the application has been saved, you can select it to view its settings. The application's Key and Secret are displayed. Record these for future use. You will use the Key to set the OAuthClientId and the Secret to set the OAuthClientSecret.
   
4. Click Save & Test
5. Navigate to the Permissions tab in the Add Bitbucket 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.

1. Click on the Gear icon () at the top right of the Connect AI app to open the settings page.
2. On the Settings page, go to the Access Tokens section and click Create PAT.
3. Give the PAT a name and click Create.
4. 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 Bitbucket 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).

1. 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.
2. After you finish the installation, then start the server:

   
   sudo service postgresql start
   

3. 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 Bitbucket data as a PostgreSQL Database and query the data!

After you have installed the extension, follow the steps below to start executing queries to Bitbucket data:

1. Log into your database.
2. Load the extension for the database:

   
   CREATE EXTENSION tds_fdw;
   

3. Create a server object for Bitbucket data:

   
   CREATE SERVER "Bitbucket1" FOREIGN DATA WRAPPER tds_fdw OPTIONS (servername'tds.cdata.com', port '14333', database 'Bitbucket1');
   

4. Configure user mapping with your email and Personal Access Token from your Connect AI account:

   
   CREATE USER MAPPING for postgres SERVER "Bitbucket1" OPTIONS (username '[email protected]', password 'your_personal_access_token' );
   

5. Create the local schema:

   
   CREATE SCHEMA "Bitbucket1";
   

6. Create a foreign table in your local database:

   
   #Using a table_name definition:
   
   CREATE FOREIGN TABLE "Bitbucket1".Issues  (      
   id varchar,      
   ContentRaw varchar)      
   SERVER "Bitbucket1"
   OPTIONS(table_name 'Bitbucket.Issues', row_estimate_method 'showplan_all');
   
   #Or using a schema_name and table_name definition:
   
   CREATE FOREIGN TABLE "Bitbucket1".Issues (      
   id varchar,      
   ContentRaw varchar)      
   SERVER "Bitbucket1"
   OPTIONS (schema_name 'Bitbucket', table_name 'Issues', row_estimate_method 'showplan_all');
   
   #Or using a query definition:
   
   CREATE FOREIGN TABLE  "Bitbucket1".Issues (
   id varchar,      
   ContentRaw varchar)      
   SERVER "Bitbucket1"
   OPTIONS (query 'SELECT * FROM Bitbucket.Issues', row_estimate_method 'showplan_all');
   
   #Or setting a remote column name:
   
   CREATE FOREIGN TABLE "Bitbucket1".Issues (
   id varchar,
   col2 varchar OPTIONS (column_name 'ContentRaw'))
   SERVER "Bitbucket1"
   OPTIONS (schema_name 'Bitbucket', table_name 'Issues', row_estimate_method 'showplan_all');
   

7. You can now execute read/write commands to Bitbucket:

   
   SELECT id, ContentRaw
   FROM "Bitbucket1".Issues;
   

More Information & Free Trial

Now, you have created a simple query from live Bitbucket data. For more information on connecting to Bitbucket (and more than 200 other data sources), visit the Connect AI page. Sign up for a free trial and start working with live Bitbucket data in PostgreSQL.