PDE Ingesting and Processing the Data Practice Question
You need to copy a 3 TB dataset from an on-premises Hadoop Distributed File System (HDFS) cluster to Cloud Storage over a 1 Gbps dedicated interconnect. The data is a one-time historical backfill and must be transferred with integrity verification. You want to minimize operational overhead and avoid writing custom transfer code. Which service should you use?
⚠ Common exam trap
The trap here is assuming that any tool that can read HDFS is equally suited for bulk transfer, when transfer-specific managed services provide integrity and retry behavior that pipeline tools do not.
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
✓
Storage Transfer Service with an HDFS source
Storage Transfer Service is purpose-built for moving large datasets from on-premises sources including HDFS into Cloud Storage. It handles parallelism, retries, integrity verification, and monitoring without custom code, which matches the requirement to minimize operational overhead for a one-time backfill over a dedicated interconnect.
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 Data Fusion with an HDFS source plugin
Why it's wrong here
Cloud Data Fusion is a managed data integration UI that can read HDFS, but it is designed for transformation pipelines rather than bulk file movement. Using it here adds pipeline design, runtime provisioning, and monitoring overhead that a simple transfer does not require. It also does not provide the same transfer-specific retry and integrity reporting.
- ✗
gcloud storage cp with parallel composite uploads
Why it's wrong here
The gcloud storage cp command copies files from a local or mounted file system, not directly from HDFS. It would require first exporting data to a local staging area, adding time and storage overhead. Parallel composite uploads optimize large single files, but they do not address the HDFS source or bulk dataset transfer management.
- ✗
DistCp job writing directly to a Cloud Storage bucket
Why it's wrong here
DistCp copies between Hadoop-compatible file systems, but writing to Cloud Storage requires the Cloud Storage connector and careful configuration. It does not natively verify object integrity or provide managed retry and logging. This approach also requires operating a Hadoop cluster for the duration of the transfer, increasing operational burden.
- ✓
Storage Transfer Service with an HDFS source
Why this is correct
Storage Transfer Service natively supports on-premises HDFS as a source and Cloud Storage as a destination. It performs parallel transfers, integrity checks, and retries without custom code, which fits the one-time historical backfill over a dedicated interconnect. It also handles the large file set efficiently and provides transfer logs and monitoring out of the box.
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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.