Connect to Bitbucket Data as an External Data Source using PolyBase

PolyBase for SQL Server allows you to query external data by using the same Transact-SQL syntax used to query a database table. When paired with the CData ODBC Driver for Bitbucket, you get access to your Bitbucket data directly alongside your SQL Server data. This article describes creating an external data source and external tables to grant access to live Bitbucket data using T-SQL queries.

NOTE: PolyBase is only available on SQL Server 19 and above.

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.

Configure Bitbucket Connectivity for PolyBase

Connectivity to Bitbucket from PolyBase is made possible through CData Connect AI. To work with Bitbucket data from PolyBase, we start by creating and configuring a Bitbucket connection.

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 Polybase.

Create an External Data Source for Bitbucket Data

After configuring the connection, you need to create a credential database for the external data source.

Creating a Credential Database

Execute the following SQL command to create credentials for the external data source connected to Bitbucket data.

NOTE: Set IDENTITY to your Connect AI username and set SECRET to your Personal Access Token.

CREATE DATABASE SCOPED CREDENTIAL ConnectCloudCredentials
WITH IDENTITY = 'yourusername', SECRET = 'yourPAT';

Create an External Data Source for Bitbucket

Execute a CREATE EXTERNAL DATA SOURCE SQL command to create an external data source for Bitbucket with PolyBase:

CREATE EXTERNAL DATA SOURCE ConnectCloudInstance
WITH ( 
  LOCATION = 'sqlserver://tds.cdata.com:14333',
  PUSHDOWN = ON,
  CREDENTIAL = ConnectCloudCredentials
);

Create External Tables for Bitbucket

After creating the external data source, use CREATE EXTERNAL TABLE statements to link to Bitbucket data from your SQL Server instance. The table column definitions must match those exposed by CData Connect AI. You can use the Data Explorer in Connect AI to see the table definition.

Sample CREATE TABLE Statement

Execute a CREATE EXTERNAL TABLE SQL command to create the external table(s), using the collation and setting the LOCATION to three-part notation for the connection, catalog, and table. The statement to create an external table based on a Bitbucket Issues would look similar to the following.

CREATE EXTERNAL TABLE Issues(
  Title COLLATE [nvarchar](255) NULL,
  ContentRaw COLLATE [nvarchar](255) NULL,
  ...
) WITH ( 
  LOCATION='Bitbucket1.Bitbucket.Issues',
  DATA_SOURCE=ConnectCloudInstance
);

Having created external tables for Bitbucket in your SQL Server instance, you are now able to query local and remote data simultaneously. To get live data access to hundreds of SaaS, Big Data, and NoSQL sources directly from your SQL Server database, try CData Connect AI today!