Crucial Exams

Microsoft Fabric Data Engineer Associate DP-700 Practice Question

You are onboarding several data scientists to a Microsoft Fabric workspace that is configured for a capacity in the F64 SKU. During test runs, they notice that each new notebook session starts a Spark cluster that uses a driver size of Small (4 v-cores, 32 GB) and a maximum of two executor nodes, which is insufficient for the planned machine-learning workloads. You need to change the default Spark resource allocation so that every new interactive notebook session in the workspace starts with a Medium driver (8 v-cores, 64 GB) and allows up to eight executor nodes. The change must not require users to modify the session settings manually each time they create a notebook.

In the Fabric Admin portal, which blade should you use, and what two parameters must you modify?

  • Capacity settings > Scale - increase the capacity size and enable autoscale

  • Security center > Access control - grant data scientists the Fabric Data Engineering workload role

  • Workspace settings > General - raise the workspace size and enable Enhanced compute

  • Workspace settings > Data engineering (Spark) - set Driver size to Medium and Maximum executor nodes to 8

Microsoft Fabric Data Engineer Associate DP-700
Implement and manage an analytics solution
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