Answer: To transfer one data frame to another data frame.

In Spark's MLlib, transformers are essential for data manipulation and feature engineering within machine learning pipelines. Their primary role is to transform one DataFrame into another, enabling operations like feature scaling, encoding categorical features, handling missing values, feature selection or extraction, and vectorizing text data. This process prepares the data for machine learning algorithms. The other options do not accurately describe the main purpose of transformers: training models and implementing the .fit() method are tasks for estimators, not transformers. While transformers do result in a new DataFrame, their core function is data modification, not creation. Combining transformers and estimators is a feature of Spark MLlib pipelines, not a primary role of transformers themselves.

Author: LeetQuiz Editorial Team