GCP-ADP Data Preparation And Ingestion Practice Question
You are running a Dataflow job that joins two large datasets. Which join strategy should you avoid to prevent OOM errors?
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
✓
Side Input Join with a large dataset
Broadcasting a large dataset to all workers (Side Inputs) can lead to Out of Memory (OOM) errors.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Side Input Join with a large dataset
Why this is correct
Side inputs are loaded into memory and should not be used for very large datasets.
- ✗
Flatten
Why it's wrong here
Flatten is for merging PCollections.
- ✗
CoGroupByKey
Why it's wrong here
This is the standard, scalable way to join datasets.
- ✗
ParDo
Why it's wrong here
ParDo is for mapping, not joining.
About these practice questions
Courseiva writes every GCP-ADP question from scratch — 205 in total, each with an explanation and a wrong-answer breakdown. None are copied from real exams or dumps. Learn why practice questions differ from exam dumps →
JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed August 2026 · checked against the official Google Cloud exam blueprint
This GCP-ADP 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 GCP-ADP exam.