PDE Designing data processing systems Practice Question
This PDE practice question tests your understanding of designing data processing systems. 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 stores IoT sensor data in BigQuery. Queries that filter on a timestamp column and a device_id column are slow even though the table is partitioned by day. What should the data engineer do to improve query performance?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Cluster the table on device_id
Clustering on device_id organizes the data within each day partition by device_id, allowing BigQuery to prune blocks during queries that filter on that column. This reduces the amount of data scanned and improves query performance without changing the partitioning scheme. Partitioning alone only limits scans by time range; clustering adds intra-partition sorting for non-time-based filters.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✗
Increase the partition size to monthly
Why it's wrong here
Smaller partitions are usually better for pruning.
✗
Switch to ingestion-time partitioning instead of column-based
Why it's wrong here
Similar performance, not a significant improvement.
✗
Enable automatic query rewriting with BI Engine
Why it's wrong here
BI Engine accelerates dashboards, not general queries.
✓
Cluster the table on device_id
Why this is correct
Clustering organizes data within partitions, improving filter performance.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google Cloud often tests the distinction between partitioning (which prunes by time) and clustering (which prunes by non-time columns), and the trap here is assuming that partitioning alone is sufficient for all filter columns, leading candidates to choose an option that changes the partition strategy rather than adding clustering.
Trap categories for this question
Similar concept trap
Similar performance, not a significant improvement.
Detailed technical explanation
How to think about this question
BigQuery clustering sorts data based on the values of one or more columns and creates blocks of approximately 100 MB that share the same cluster values. When a query filters on a clustered column, BigQuery uses the clustered metadata to skip entire blocks that do not match the filter, reducing the number of bytes read. This is especially effective when combined with partitioning because the partition pruning eliminates time-based blocks first, and then clustering eliminates device_id blocks within the remaining partitions.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Designing data processing systems — This question tests Designing data processing systems — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Cluster the table on device_id — Clustering on device_id organizes the data within each day partition by device_id, allowing BigQuery to prune blocks during queries that filter on that column. This reduces the amount of data scanned and improves query performance without changing the partitioning scheme. Partitioning alone only limits scans by time range; clustering adds intra-partition sorting for non-time-based filters.
What should I do if I get this PDE question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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