Build AI/ML Models with Live Amazon Athena Data using Dataiku

Dataiku is a data science and machine learning platform used for data preparation, analysis, visualization, and AI/ML model deployment, enabling collaborative and efficient data-driven decision-making. When paired with the CData JDBC Driver for Amazon Athena, Dataiku enhances data integration, preparation, real-time analysis, and reliable model deployment for Amazon Athena data.

With built-in optimized data processing, the CData JDBC Driver offers unmatched performance for interacting with live Amazon Athena data. When you issue complex SQL queries to Amazon Athena, the driver pushes supported SQL operations, like filters and aggregations, directly to Amazon Athena and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations). Its built-in dynamic metadata querying allows you to work with and analyze Amazon Athena data using native data types.

This article shows how you can easily integrate to Amazon Athena using CData JDBC Driver for Amazon Athena in Dataiku DSS (Data Science Studio) platform, allowing you to prepare the data and build custom AI/ML models.

Getting Started

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Preparing the Dataiku DSS environment

In this section, we will explore how to set up Dataiku, as previously introduced, with Amazon Athena data. Be sure to install Dataiku DSS (On-Prem version) for your preferred operating system, beforehand.

Install the CData JDBC Driver for Amazon Athena

First, install the CData JDBC Driver for Amazon Athena on the same machine as Dataiku. The JDBC Driver will be installed in the following path:

Connecting the JDBC Driver in Dataiku DSS

To use the CData JDBC driver in Dataiku, you must create a new SQL database connection and add the JDBC Driver JAR file in the DSS connection settings.

1. Log into Dataiku DSS platform. It should open locally in your browser (e.g. localhost:11200)
2. Click on Navigate to other sections of Dataiku menu on the top right section of the platform and select Administration.
3. Select the Connections tab.
4. In Connections, click on New Connections button.
5. Now, scroll down and select Other SQL databases.

6. Generate a JDBC URL for connecting to Amazon Athena, beginning with jdbc:amazonathena: followed by a series of semicolon-separated connection string properties.

   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 AccessKey to the access key Id. Set SecretKey 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 UseEC2Roles to true and leave AccessKey and SecretKey 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 RoleARN. 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 AccessKey and SecretKey of an IAM user to assume the role for. Roles may not be used when specifying the AccessKey and SecretKey of an AWS root user.

   Authenticating with MFA

   For users and roles that require Multi-factor Authentication, specify the MFASerialNumber and MFAToken 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 TemporaryTokenDuration (default 3600 seconds).

   Connecting to Amazon Athena

   In addition to the AccessKey and SecretKey properties, specify Database, S3StagingDirectory and Region. Set Region to the region where your Amazon Athena data is hosted. Set S3StagingDirectory to a folder in S3 where you would like to store the results of queries.

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

   Built-in Connection String Designer

   For assistance in constructing the JDBC URL, use the connection string designer built into the Amazon Athena JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.

   java -jar cdata.jdbc.amazonathena.jar

   Fill in the connection properties and copy the connection string to the clipboard.

   A typical JDBC URL is given below:

   jdbc:amazonathena:AWSAccessKey='a123';AWSSecretKey='s123';AWSRegion='IRELAND';Database='sampledb';S3StagingDirectory='s3://bucket/staging/';
7. On the New SQL database (JDBC) connection screen, enter a name in the New connection name field and specify the basic parameters:
   • JDBC Driver Class: cdata.jdbc.amazonathena.AmazonAthenaDriver
   • JDBC URL: JDBC connection URL obtained in the previous step
   • Driver jars directory: the folder path where the JAR file is installed on your system

   Next, select the SQL dialect of your choice. Here, we have selected 'SQL Server' as the preferred dialect. Click on Create. If the connection is successful, a prompt will display, saying 'Connection OK'.

8. The Data Catalog window will appear. Select the desired connection, catalog, and schema from the Connection to browse, Restrict to catalog, and Restrict to schema dropdowns, then click on List Tables. The Dataiku platform will list all the required tables.
9. Select any table from the list and click Preview to view the table data. Click Close to exit the window.

Creating a new project

To prepare data flows, create dashboards, analyze the Amazon Athena data, and build AI and ML models in the Dataiku DSS platform, you need to first create a new project.

1. Select Projects from the Navigate to other sections of Dataiku menu.
2. In the Projects screen, click New Project and select + Blank Project.
3. In the New Project window, assign a Name and Project Key. Click Create. The new project dashboard opens up.
4. Select Notebooks from the menu at the top of the project screen.
5. Click on + Create Your First Notebook dropdown menu and select Write your own option.
6. In the New Notebook window, select SQL.
7. Now, select the required connection from the Connection dropdown and enter a name in the Notebook Name field.

Testing the connection

To test the Amazon Athena connection and analyze the Amazon Athena data, write a query in the query compiler and click Run. The queried/filtered Amazon Athena data results will then appear on the screen.

Get Started Today

Download a free, 30-day trial of the CData JDBC Driver for Amazon Athena to integrate with Dataiku, and effortlessly build custom AI/ML models from Amazon Athena data.

Reach out to our Support Team if you have any questions.