Answer: Spark Structured Streaming

## Explanation Auto Loader uses **Spark Structured Streaming** to process data incrementally. Here's why: **Key Points:** 1. **Auto Loader Architecture**: Auto Loader is built on top of Spark Structured Streaming, which provides the incremental processing capabilities. 2. **How Auto Loader Works**: - Auto Loader monitors cloud storage locations for new files - It uses Structured Streaming's micro-batch processing to incrementally load new data - The process tracks which files have been processed using checkpointing 3. **Checkpointing Role**: While checkpointing (Option A) is used by Auto Loader to track processed files and maintain state, it's not the primary tool for incremental processing. Checkpointing is a supporting mechanism. 4. **Data Explorer**: This is a Databricks tool for exploring and visualizing data, not related to incremental data processing. **Correct Answer**: **B. Spark Structured Streaming** - This is the underlying engine that enables Auto Loader's incremental processing capabilities. **Additional Context**: - Auto Loader provides optimized file discovery and schema inference on top of Structured Streaming - It's designed specifically for incremental data ingestion from cloud storage - The incremental processing happens through Structured Streaming's micro-batch architecture

Author: Keng Suppaseth