Analyze Amazon Athena Data in Looker

Looker is a business intelligence and big data analytics platform that helps you explore, analyze and share real-time business analytics. When paired with CData Connect AI, you get instant, cloud-to-cloud access to Amazon Athena data for business applications. This article shows how to connect to Amazon Athena in Connect AI and then connect to Amazon Athena data in Looker.

CData Connect AI provides a pure cloud-to-cloud interface for Amazon Athena, allowing you to build reports from live Amazon Athena data in Looker — without replicating the data to a natively supported database. As you create applications to work with data, Looker generates SQL queries to gather data. Using optimized data processing out of the box, CData Connect AI pushes all supported SQL operations (filters, JOINs, etc.) directly to Amazon Athena, leveraging server-side processing to quickly return the requested Amazon Athena data.

Getting Started

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Configure Amazon Athena Connectivity for Looker

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

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

2. Select "Amazon Athena" from the Add Connection panel
👁 Selecting a data source

3. Enter the necessary authentication properties to connect to Amazon Athena.

   Authenticating to Amazon Athena

   To authorize Amazon Athena requests, provide the credentials for an administrator account or for an IAM user with custom permissions: Set to the access key Id. Set to the secret access key.

   Note: Though you can connect as the AWS account administrator, it is recommended to use IAM user credentials to access AWS services.

   Obtaining the Access Key

   To obtain the credentials for an IAM user, follow the steps below:

   1. Sign into the IAM console.
   2. In the navigation pane, select Users.
   3. To create or manage the access keys for a user, select the user and then select the Security Credentials tab.

   To obtain the credentials for your AWS root account, follow the steps below:

   1. Sign into the AWS Management console with the credentials for your root account.
   2. Select your account name or number and select My Security Credentials in the menu that is displayed.
   3. Click Continue to Security Credentials and expand the Access Keys section to manage or create root account access keys.

   Authenticating from an EC2 Instance

   If you are using the CData Data Provider for Amazon Athena 2018 from an EC2 Instance and have an IAM Role assigned to the instance, you can use the IAM Role to authenticate. To do so, set to true and leave and empty. The CData Data Provider for Amazon Athena 2018 will automatically obtain your IAM Role credentials and authenticate with them.

   Authenticating as an AWS Role

   In many situations it may be preferable to use an IAM role for authentication instead of the direct security credentials of an AWS root user. An AWS role may be used instead by specifying the . This will cause the CData Data Provider for Amazon Athena 2018 to attempt to retrieve credentials for the specified role. If you are connecting to AWS (instead of already being connected such as on an EC2 instance), you must additionally specify the and of an IAM user to assume the role for. Roles may not be used when specifying the and of an AWS root user.

   Authenticating with MFA

   For users and roles that require Multi-factor Authentication, specify the and connection properties. This will cause the CData Data Provider for Amazon Athena 2018 to submit the MFA credentials in a request to retrieve temporary authentication credentials. Note that the duration of the temporary credentials may be controlled via the (default 3600 seconds).

   Connecting to Amazon Athena

   In addition to the and properties, specify , and . Set to the region where your Amazon Athena data is hosted. Set to a folder in S3 where you would like to store the results of queries.

   If is not set in the connection, the data provider connects to the default database set in Amazon Athena.

   👁 Configuring a connection (Salesforce is shown)
   
4. Click Save & Test
5. Navigate to the Permissions tab in the Add Amazon Athena Connection page and update the User-based permissions. 👁 Updating 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. 👁 Creating a new PAT
   
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 Amazon Athena data from Looker.

Connect to Amazon Athena in Looker

The steps below outline connecting to CData Connect AI from Looker to create a new Amazon Athena data source.

1. Log-in to Looker
2. In the navigation pane, select Admin. 👁 Selecting Admin
   
3. Under the Database category, select Connections. 👁 Selecting connections
   
4. On the Connections page, click Add Connection. 👁 Adding a new connection
   
5. Enter the connection settings:
   • Name: the name for the connection in models.
   • Dialect: select Microsoft SQL Server 2017+.
   • SSH Server: leave this disabled.
   • Remote Host:Port: enter tds.cdata.com in the first field and 14333 in the second field.
   • Database: enter the Connection Name of the CData Connect AI data source you want to connect to (for example, QuickBooksOnline1).
   • Username: enter your CData Connect AI username. This is displayed in the top-right corner of the CData Connect AI interface. For example, [email protected]
   • Password: enter the PAT you generated on the Settings page
   Leave the rest of the connection settings at their default values unless you need to modify them. 👁 Configuring connection settings
   
6. At the bottom of the page, click Test These Settings to ensure that you can connect to CData Connect AI.
7. Click Add Connection to create the connection and return to the Connections page. 👁 New connection added.
   

Your connection is now available for use in Looker. To connect to additional data sources from your CData Connect AI account, repeat the setup steps above, changing the value for Database for each data source.

Creating A Looker Visualization From The SQL Runner and Explore Features

To create a visualization in Looker using the SQL Runner, follow these steps:

1. In the Looker interface, select Develop -> SQL Runner from the left navigation pane. 👁 Select SQL Runner.
   
2. On the SQL Runner interface, select the connection you made in the previous steps. 👁 Entering name for new dashboard.
   
3. Now, click the gear symbol next to a table and then select Explore Table. 👁 Entering name for new dashboard.
   
4. Next, on the left menu, select fields from the table and click Run. You can now expand the Visualization accordion, and see a bar chart, by default. 👁 Entering name for new dashboard.
   

   We have now created a visualization of Amazon Athena data in Looker using CData Connect AI!

Get CData Connect AI

To get live data access to hundreds of SaaS, Big Data, and NoSQL sources directly from your cloud applications, try CData Connect AI today!