Use Case 1: Executing First AWS SageMaker Model with Scala on Qubole Analyze

The script uses MNIST data provided by SageMaker to build a Machine learning model. This model can be used to predict the output for Mnist test data.

Prerequisites

Ensure that the instructions mentioned under Configuring a Qubole Spark Cluster and Configuring AWS SageMaker sections are completed.

Executing First AWS SageMaker Model with Scala on Qubole Analyze

1. Navigate to the Analyze page on the QDS UI.

2. On the Analyze page, select Spark Command as the Command Type in the query editor. Select the Spark cluster that you have configured under Configuring a Qubole Spark Cluster section. Ensure that the language is set as Scala.

3. Copy and paste the program mentioned under Appendix 2: For Scala in the query editor. Enter the required information in the region and role ARN (as configured under Step 3 of Configuring AWS SageMaker) for the Scala program.

4. Use the following code under Spark Submit Command Line Operations section:

   --packages com.amazonaws:sagemaker-spark_2.11:spark_2.1.1-1.0
   

5. Click Run. It starts training a job and creates an endpoint to host the model. At the end, it runs the Test Data and displays the result, as shown below.