Databricks Machine Learning Professional exam dumps

Databricks Machine Learning Professional practice question 168 of 280

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

Databricks Machine Learning Professional Question 168

Select 3

A data engineering team is building an ETL pipeline to process real-time sensor data from IoT devices and load it into a Delta Lake table for downstream machine learning tasks. The team decides to use Structured Streaming in Databricks. Which of the following reasons justify using Structured Streaming for this use case?

  1. A

    Structured Streaming provides incremental processing capabilities, allowing the pipeline to process data as it arrives in micro-batches or in continuous mode.

  2. B

    Structured Streaming automatically handles late-arriving data and supports watermarking to define event-time windows.

  3. C

    Structured Streaming can only process batch data and is unsuitable for real-time ETL pipelines.

  4. D

    Structured Streaming enables schema enforcement and evolution, ensuring the data is consistently formatted in the Delta Lake table.

  5. E

    Structured Streaming is designed for real-time streaming but requires manual checkpointing for fault tolerance.

Show answer and explanation

Correct answers: A, B, D

Explanation

Structured Streaming is a powerful tool for building real-time ETL pipelines due to its ability to process data incrementally, handle late-arriving data with watermarking, and enforce schema consistency in Delta Lake integrations. These features make it ideal for scenarios like processing IoT sensor data in real-time. Incorrect options either misrepresent Structured Streaming's capabilities or describe features it does not require, such as manual checkpointing.

  • A. Correct.

    Correct. Structured Streaming processes data incrementally, which is essential for real-time ETL pipelines where data is constantly arriving. This makes it suitable for IoT data processing.

  • B. Correct.

    Correct. Structured Streaming supports late-arriving data and watermarking, which are critical for handling real-world streaming scenarios with event-time windows.

  • C. Incorrect.

    Incorrect. Structured Streaming is specifically designed for both real-time and micro-batch processing, making it ideal for real-time ETL pipelines.

  • D. Correct.

    Correct. Structured Streaming integrates with Delta Lake and supports schema enforcement and evolution, ensuring that the data ingested into the table adheres to a consistent format.

  • E. Incorrect.

    Incorrect. Structured Streaming includes automatic checkpointing to ensure fault tolerance; manual checkpointing is not required.

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