Which statement is true regarding Spark configuration on the Databricks platform?

The statement that configuration properties set in the Clusters UI impact all notebooks attached to that cluster is correct. In the Databricks environment, when you configure Spark settings through the Clusters user interface, those configurations are applied at the cluster level. This means that any notebooks or jobs running on that particular cluster will inherit those settings.

This capability is particularly useful for ensuring consistency across various notebooks that share the same cluster, as it allows for standardized resource allocation, performance tuning, and other important configuration controls without the need to specify them repeatedly in each notebook. It centralizes the configuration management, making it easier to maintain and adjust settings when necessary, thus promoting best practices in collaborative data engineering tasks.

Other options, while touching on aspects of configuration management, do not convey the same level of accurate detail regarding the scope of impact on notebooks running in Databricks.