What does a Databricks cluster consist of in terms of node types?

A Databricks cluster is structured to have a single driver node, which is responsible for orchestrating the processing tasks and managing the execution of distributed jobs. This driver node handles the main application code and coordinates the workers. Additionally, it can interact with various components of the data environment, such as the Spark engine and libraries.

In conjunction with the driver, a Databricks cluster can have zero or more worker nodes. These worker nodes perform the actual data processing tasks as instructed by the driver node. They handle the execution of computations and storage of data as necessary for running notebooks, jobs, and other tasks.

By design, the presence of a single driver node simplifies task management, while the scalability provided by multiple worker nodes allows for handling larger datasets and more complex processing tasks. This architecture effectively aids in the efficient execution of distributed computing tasks common in machine learning and data processing workflows.