Databricks Machine Learning Associate Question 32
Select 3You are tasked with building a machine learning pipeline in Databricks to preprocess data, train a model, and evaluate the results. You decide to use Databricks Jobs to orchestrate this workflow. Which of the following steps must you take to ensure the workflow executes correctly and sequentially?
- A
Define each step as a separate task in the Databricks Job and set task dependencies.
- B
Use the Databricks REST API to manually trigger each task in sequence.
- C
Configure the correct cluster settings for each task in the workflow.
- D
Ensure that the output of one task is stored in a location accessible by subsequent tasks.
- E
Manually monitor each step of the workflow to transition to the next task.
Show answer and explanation
Correct answers: A, C, D
Explanation
When orchestrating multi-task machine learning workflows in Databricks Jobs, it is essential to define each step as a separate task, configure dependencies between tasks for proper execution order, and ensure that data outputs are accessible to subsequent tasks. Additionally, configuring the correct cluster settings is crucial for task execution, as different tasks may require different computational resources. Databricks automates task execution, so manual intervention or triggering is unnecessary.
- A. Correct.
Correct. In Databricks Jobs, each step in the workflow should be defined as a separate task, and task dependencies must be configured to ensure proper execution order.
- B. Incorrect.
Incorrect. While the Databricks REST API can trigger jobs, it is not necessary to manually trigger each task in sequence when using Databricks Jobs. Task dependencies handle this automatically.
- C. Correct.
Correct. Each task in the Databricks workflow must have an appropriate cluster configuration, as different tasks (e.g., preprocessing, training) may have different resource requirements.
- D. Correct.
Correct. The output of one task (e.g., a preprocessed dataset) must be stored in a location that subsequent tasks can access to ensure proper data flow through the pipeline.
- E. Incorrect.
Incorrect. Databricks Jobs are designed to automate workflows, so manually monitoring and transitioning between tasks is not required. The system handles execution based on task dependencies.