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GCDL Practice Question: A healthcare company needs to run a large batch…

This GCDL practice question tests your understanding of a healthcare company needs to run a large batch…. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.

A healthcare company needs to run a large batch processing job that analyzes patient records using Apache Spark, transforming data from Cloud Storage and writing results to BigQuery. The job runs once daily and requires a large cluster that should exist only during the job. Which Google Cloud product best handles this ephemeral large-batch Spark workload?

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A healthcare company needs to run a large batch processing job that analyzes patient records using Apache Spark, transforming data from Cloud Storage and writing results to BigQuery. The job runs once daily and requires a large cluster that should exist only during the job. Which Google Cloud product best handles this ephemeral large-batch Spark workload?

Answer choices

Why each option matters

Good practice is not just finding the correct option. The wrong answers often show the exact trap the exam wants you to fall into.

A

Distractor review

BigQuery, by running the Spark transformation directly within BigQuery's execution engine

BigQuery executes SQL-based queries and BigQuery ML models, not Apache Spark code. While BigQuery can run Apache Spark through BigQuery Spark stored procedures (a newer feature), the standard managed Spark platform is Dataproc.

B

Distractor review

Cloud Dataflow, for running the Apache Spark code as a streaming pipeline

Cloud Dataflow runs Apache Beam (not Spark) pipelines. If the existing code is written in Spark (PySpark, Scala Spark), Dataproc is the appropriate managed platform. Migrating Spark to Beam requires significant code changes.

C

Best answer

Cloud Dataproc, which runs managed Apache Spark clusters that can be created for the job and deleted on completion — paying only during the processing window

Dataproc is the correct choice for managed Apache Spark. The ephemeral cluster pattern (create cluster → run Spark job → delete cluster) is the recommended cost-optimization approach for batch jobs. The cluster exists only while needed, minimizing cost.

D

Distractor review

Compute Engine VMs, by manually installing Apache Spark on a cluster of VMs each day before the job

Manually managing VM clusters with custom Spark installations requires significant operational effort and time for cluster setup. Dataproc automates cluster creation, Spark installation, and configuration in minutes.

Common exam trap

Common exam trap: NAT rules depend on direction and matching traffic

NAT is not only about the public address. The inside/outside interface roles and the ACL or rule that matches traffic are just as important.

Technical deep dive

How to think about this question

NAT questions usually test address translation, overload/PAT behaviour, static mappings and whether the right traffic is being translated. Read the interface direction and address terms carefully.

KKey Concepts to Remember

  • Static NAT maps one inside address to one outside address.
  • PAT allows many inside hosts to share one public address using ports.
  • Inside local and inside global describe the private and translated addresses.
  • NAT ACLs identify traffic for translation, not always security filtering.

TExam Day Tips

  • Identify inside and outside interfaces first.
  • Check whether the scenario needs static NAT, dynamic NAT or PAT.
  • Do not confuse NAT matching ACLs with normal packet-filtering intent.

Key takeaway

NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.

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FAQ

Questions learners often ask

What does this GCDL question test?

Static NAT maps one inside address to one outside address.

What is the correct answer to this question?

The correct answer is: Cloud Dataproc, which runs managed Apache Spark clusters that can be created for the job and deleted on completion — paying only during the processing window — Cloud Dataproc is Google Cloud's managed Apache Spark and Hadoop service. For ephemeral batch jobs, Dataproc clusters can be created at job start and deleted at job completion — paying only for the cluster during the processing window. This 'ephemeral cluster' pattern is a cost-efficient approach for daily batch Spark jobs that don't need a persistent cluster.

What should I do if I get this GCDL question wrong?

Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related GCDL NAT questions on configuration and troubleshooting.

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This GCDL practice question is part of Courseiva's free Google Cloud certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the GCDL exam.