You need to ensure that processes for the bronze and silver layers run in isolation. How should you configure the Apache Spark settings?

High concurrency in Spark allows multiple users or jobs to share the same cluster, which can lead to resource contention and lack of isolation. Disabling high concurrency ensures that each job or process (e.g., for bronze or silver layers) gets its own dedicated Spark session, thereby achieving better isolation.

Creating a custom pool can define resource limits but does not inherently guarantee isolation between distinct processes running within the same workspace if high concurrency is enabled.

Modifying the number of executors primarily tunes performance for a single job or application but does not provide isolation between distinct processes or layers.

Setting the default environment configures shared settings for notebooks/jobs but does not specifically enforce execution isolation for different processing layers.