PDE Designing Data Processing Systems Practice Question
Your company is migrating an on-premises Apache Hadoop cluster to Google Cloud. The cluster runs Hive for SQL-like queries and stores data in HDFS. You want a managed service that minimizes operational overhead while supporting existing Hive scripts. Which Google Cloud service should you choose?
⚠ Common exam trap
The trap here is assuming that a serverless data warehouse like BigQuery can run existing Hive scripts, overlooking that Dataproc is designed for Hadoop compatibility.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Cloud Dataproc
Cloud Dataproc is the correct choice because it is a managed Hadoop and Spark service that supports Hive, HDFS, and other ecosystem tools, allowing you to run existing Hive scripts with minimal changes. It reduces operational overhead by handling cluster provisioning, configuration, and scaling.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Cloud Dataflow
Why it's wrong here
Cloud Dataflow is a fully managed service for stream and batch processing using Apache Beam, but it does not support Hive or HDFS natively. It requires rewriting pipelines in Beam, which is not compatible with existing Hive scripts. It is not a drop-in replacement for Hadoop workloads.
- ✗
Cloud Bigtable
Why it's wrong here
Cloud Bigtable is a NoSQL database, not a Hadoop distribution. It does not support Hive or HDFS, and it is not designed for running MapReduce or Spark jobs. It is used as a storage backend for Hadoop, but it cannot replace the compute and query capabilities of a Hadoop cluster.
- ✓
Cloud Dataproc
Why this is correct
Cloud Dataproc is a managed Spark and Hadoop service that supports Hive, HDFS, and other Hadoop ecosystem tools. It allows you to run existing Hive scripts with minimal changes and provides cluster management, autoscaling, and integration with Cloud Storage. It is the ideal choice for migrating on-premises Hadoop workloads.
- ✗
BigQuery
Why it's wrong here
BigQuery is a serverless data warehouse that supports SQL, but it does not run Hive scripts or use HDFS. Migrating to BigQuery would require rewriting Hive queries into BigQuery SQL and moving data to BigQuery storage. It does not provide a Hadoop-compatible environment for existing scripts.
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Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Google Cloud exam blueprint
This PDE 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 PDE exam.