Data Engineering Associate with Databricks Practice Exam

What is required for a structured streaming computation in Databricks?

1. Pre-specified user permissions

2. Continuous reading of batch files

3. Express computations on streaming data

4. Manual data tracking

The correct answer is: Express computations on streaming data

For a structured streaming computation in Databricks, expressing computations on streaming data is essential. This approach allows users to define transformations and actions on the data as it arrives, enabling real-time data processing. Structured streaming provides a unified API for processing both batch and streaming data, allowing developers to build pipelines that can handle continuous data flows seamlessly. The framework ensures that the operations applied to data streams are maintained in a structured manner, allowing for scalability and fault tolerance. As data comes in, the system processes it incrementally and continuously, making it possible to deliver insights and updates in near real-time. This ability to express computations directly on streaming data is foundational for implementing effective and responsive data pipelines in Databricks. Other choices focus on elements that are not core requirements for structured streaming. Pre-specified user permissions may be a part of access control in a Databricks environment, but they are not specifically necessary for the operation of structured streaming itself. The notion of continuously reading batch files describes a different data processing paradigm, one that does not align with the real-time capabilities of structured streaming. Lastly, while manual data tracking can be part of some workflows, structured streaming automates the data handling processes, reducing the need for manual interventions. Thus, expressing computations on