Exam Databricks-Machine-Learning-Associate Topic 1 Question 56 Discussion

Actual exam question for Databricks's Databricks-Machine-Learning-Associate exam
Question #: 56
Topic #: 1
Which of the following tools can be used to distribute large-scale feature engineering without the use of a UDF or pandas Function API for machine learning pipelines?

Suggested Answer: D Vote an answer

Spark ML (Machine Learning Library) is designed specifically for handling large-scale data processing and machine learning tasks directly within Apache Spark. It provides tools and APIs for large-scale feature engineering without the need to rely on user-defined functions (UDFs) or pandas Function API, allowing for more scalable and efficient data transformations directly distributed across a Spark cluster. Unlike Keras, pandas, PyTorch, and scikit-learn, Spark ML operates natively in a distributed environment suitable for big data scenarios.
Reference:
Spark MLlib documentation (Feature Engineering with Spark ML).

by Jocelyn at Oct 16, 2025, 08:51 PM

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