Question 196 of 300
mediummultiple choiceObjective-mapped

GCDL Practice Question: A company currently uses Hadoop and Spark for…

This GCDL practice question tests your understanding of a company currently uses hadoop and spark for…. 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 company currently uses Hadoop and Spark for batch data processing on a large on-premises cluster. They want to migrate these workloads to Google Cloud with minimal rewriting of existing Spark and Hadoop jobs. Which Google Cloud service is the best fit?

Question 1mediummultiple choice
Full question →

A company currently uses Hadoop and Spark for batch data processing on a large on-premises cluster. They want to migrate these workloads to Google Cloud with minimal rewriting of existing Spark and Hadoop jobs. Which Google Cloud service is the best fit?

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 — it runs Spark SQL queries via BigQuery Spark stored procedures.

BigQuery supports Spark stored procedures but is primarily a SQL data warehouse. It's not a full Hadoop/Spark replacement for arbitrary batch processing jobs.

B

Best answer

Cloud Dataproc — managed Apache Spark and Hadoop with minimal code changes.

Dataproc runs native Spark, Hadoop, Hive, and Pig workloads. Existing jobs can be migrated with minimal changes by pointing them at Dataproc clusters and Cloud Storage instead of HDFS.

C

Distractor review

Cloud Dataflow — it runs all Spark and Hadoop jobs natively.

Dataflow runs Apache Beam pipelines, not native Spark or Hadoop jobs. Migrating to Dataflow requires rewriting jobs in the Beam programming model.

D

Distractor review

Google Kubernetes Engine — deploy Spark clusters on Kubernetes.

Spark can run on GKE (Spark on Kubernetes) but this requires managing Kubernetes and Spark configuration — more complex than Dataproc's managed service.

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 — managed Apache Spark and Hadoop with minimal code changes. — Cloud Dataproc is Google's managed Apache Spark and Hadoop service. Existing Spark and Hadoop jobs can run on Dataproc with minimal modification — the APIs are compatible. Dataproc clusters can be created on demand, used for a job, and deleted when done (paying only for processing time). This is more economical than maintaining always-on on-premises Hadoop clusters. Dataproc integrates natively with Cloud Storage, BigQuery, and other GCP services.

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.