Access Azure Data Lake Storage Data from MySQL in Amazon QuickSight

Amazon QuickSight gives you a way to quickly build visualizations, perform analytics, and get insights from AWS data sources, uploaded files, and other databases in the cloud. When paired with the CData SQL Gateway, you get the same functionality with access to 200+ Big Data, NoSQL, and SaaS sources, both on-premises and in the cloud. In this article, we use the SQL Gateway with the CData ODBC Driver for Azure Data Lake Storage to access Azure Data Lake Storage data through a MySQL connection in Amazon QuickSight, either in real time using direct queries, or by importing the data into SPICE.

Connect to Azure Data Lake Storage Data

If you have not already done so, provide values for the required connection properties in the data source name (DSN). You can use the built-in Microsoft ODBC Data Source Administrator to configure the DSN. This is also the last step of the driver installation. See the "Getting Started" chapter in the help documentation for a guide to using the Microsoft ODBC Data Source Administrator to create and configure a DSN.

Authenticating to a Gen 1 DataLakeStore Account

Gen 1 uses OAuth 2.0 in 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 "Azure Active Directory".
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.

Configure the SQL Gateway

See the SQL Gateway Overview to set up connectivity to Azure Data Lake Storage data as a virtual MySQL database. You will configure a MySQL remoting service that listens for MySQL requests from clients. The service can be configured in the SQL Gateway UI.

To connect to the SQL Gateway from QuickSight, you will need to run the SQL Gateway on a web-facing machine. After configuring the SQL Gateway, make note of the following information:

• The IP address or domain name of the machine hosting the SQL Gateway
• The data source name (likely CData ADLS Sys) of the MySQL service
• The port number of the MySQL service
• The credentials of a SQL Gateway user with access to the service

Configure Remote Access

If your ODBC Driver and the remoting service are installed on-premise (and not accessible from Amazon QuickSight), you can use the reverse SSH tunneling feature to enable remote access. For detailed instructions, read our Knowledge Base article: SQL Gateway SSH Tunneling Capabilities.

Connect to Azure Data Lake Storage in QuickSight

Once you have a MySQL Service configured for the Azure Data Lake Storage ODBC Driver, you are ready to connect to the data in QuickSight. Start by logging in to your QuickSight console. From there, click Manage Data, then click New Data Set and choose MySQL as the data source.

Configure the data set using the values for the MySQL service for Azure Data Lake Storage you configured in SQL Gateway (be sure to use the DSN for the database name). Validate your connection and click Create Data Source.

Visualize Azure Data Lake Storage Data in QuickSight

For this article, we will use a custom SQL query for our data visualization. To do so, click Edit/Preview Data and in the resulting Data Prep screen follow the steps below:

1. Name your data set (for example, Resources).
2. If you wish to import your data into QuickSight SPICE, click the SPICE option, otherwise QuickSight will query the data directly.
3. Under the Tables menu, click Switch to Custom SQL Tool.
   • Give your SQL query a name.
   • Enter your custom SQL query. For example:
     SELECT FullPath, Permission FROM Resources
   • Click Finish.
4. Click Save & Visualize.

After you have saved the data set, you can configure the visualization. Select the columns you wish to visualize and choose a visual type. Your visualization can be customized, from its name to the way that data is aggregated.

With the CData ODBC Driver for Azure Data Lake Storage and SQL Gateway, you are able to easily build data visualizations and perform analytics on Azure Data Lake Storage data in Amazon QuickSight. If you have any questions, such as needing to access your on-premises data from AWS QuickSight, let our Support Team know.