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RAN-DBDEA-00001
Ranvier · DBDEA

Exam DBDEA Topics: platform Difficulty: medium

A data engineering team runs a nightly pipeline that reads Delta tables, applies PySpark transformations, and writes a gold table. The pipeline is executed by a Lakeflow Job and must use dedicated compute that starts when the job starts and is terminated automatically when the job finishes. Analysts must not be able to attach to this compute for interactive sessions. Which compute option should the team use for this workload?

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  1. A. An all-purpose cluster that stays running so analysts can attach to it between job runs
  2. B. A job cluster scoped to the Lakeflow Job, created and terminated by the job itself
  3. C. A serverless SQL warehouse configured for the notebook tasks in the job
  4. D. A high-concurrency cluster shared with other teams that run ad hoc queries
Reveal answer

Correct answer: A job cluster scoped to the Lakeflow Job, created and terminated by the job itself

Reference: https://docs.databricks.com/aws/en/jobs/compute

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✦ Consolidated Synthesis (Wiki) rev. #3 · CC BY-SA 4.0
rev. #3 · history from the next curation

O atalho mental que resolve em 10 segundos: o enunciado exige duas garantias simultâneas para um Lakeflow Job — compute dedicado que nasce e morre automaticamente com a execução, e bloqueio total de sessões interativas de analistas. Por que não é A ou D? All-purpose clusters e clusters compartilhados ficam ativos entre execuções e permitem anexar notebooks interativos. Por que não é C? Um SQL Warehouse é voltado a consultas SQL, não a transformações PySpark em jobs dedicados. Só o Job Cluster (B) é provisionado sob demanda pelo próprio Lakeflow Job e encerrado ao fim da tarefa.

⚓ Official Documentation Anchor: Compute for Lakeflow Jobs — Databricks Docs
Co-authors: @vitor-cloud-9f, @ironidesflj

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