Databricks Data Engineer Professional exam dumps

Databricks Data Engineer Professional practice question 47 of 313

Databricks Certified Data Engineer Professional. Professional level, Databricks. Free question with the correct answer and a full explanation.

Databricks Data Engineer Professional Question 47

Select 2

You are tasked with designing a data pipeline to process clickstream data collected from a web application. The data is stored in a Delta table and updated every few minutes. The business requires both historical trend analysis and near real-time insights. Which approach should you use to efficiently process the data while minimizing resource usage?

  1. A

    Use batch processing to periodically process the entire Delta table for historical insights and incremental processing to handle new data for real-time reports.

  2. B

    Use only batch processing to process the entire Delta table periodically for both historical and near real-time insights.

  3. C

    Use a streaming query with structured streaming to continuously process new data into an aggregation table for real-time insights while maintaining a separate batch process for historical analysis.

  4. D

    Use only a streaming query with structured streaming to process both historical and new data for all insights.

  5. E

    Implement a caching mechanism to store intermediate results from the Delta table for faster query execution and avoid incremental processing.

Show answer and explanation

Correct answers: A, C

Explanation

The optimal approach to meet the business requirements of both historical trend analysis and near real-time insights is to use a combination of batch processing for historical data and incremental processing via structured streaming for real-time updates. This ensures efficient resource utilization and timely insights without overcomplicating the pipeline or incurring unnecessary compute costs.

  • A. Correct.

    Correct: Combining batch processing for historical insights with incremental processing for real-time data is an efficient and practical solution that balances resource usage and performance.

  • B. Incorrect.

    Incorrect: Solely relying on batch processing is inefficient for near real-time insights, as it processes the entire dataset repeatedly, leading to unnecessary resource consumption.

  • C. Correct.

    Correct: Using structured streaming for incremental updates ensures that new data is processed in near real-time, while batch processing handles historical data separately, aligning with the business requirements.

  • D. Incorrect.

    Incorrect: Relying solely on streaming for both historical and new data processing is unnecessarily complex and resource-intensive, especially for historical trend analysis.

  • E. Incorrect.

    Incorrect: While caching can improve query performance, it does not replace the need for incremental processing or appropriately designed batch workflows.

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