Which of the following describes the type of workloads that are always compatible with Auto Loader?

The correct answer is A. Streaming workloads. Auto Loader is Databricks' incremental file ingestion mechanism designed specifically for streaming workloads. It uses Structured Streaming under the hood, processing new files as they arrive in cloud storage. While it can be used in batch mode with .trigger(availableNow=True)…

Submitted by miguelv· Apr 18, 2026ELT with Spark SQL and Python

Question

Which of the following describes the type of workloads that are always compatible with Auto Loader?

Options

AStreaming workloads
BMachine learning workloads
CServerless workloads
DBatch workloads
EDashboard workloads

How the community answered

(58 responses)

A
91% (53)
B
2% (1)
D
5% (3)
E
2% (1)

Explanation

Auto Loader is Databricks' incremental file ingestion mechanism designed specifically for streaming workloads. It uses Structured Streaming under the hood, processing new files as they arrive in cloud storage. While it can be used in batch mode with .trigger(availableNow=True), its core design and guarantee of exactly-once processing are rooted in the Structured Streaming engine, making streaming workloads the always-compatible type. Machine learning, serverless, batch (in the traditional sense), and dashboard workloads are not inherently tied to Auto Loader's design.

Topics

#Auto Loader#Streaming data ingestion#Structured Streaming

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