Why a Logical View Processes Full Data Despite WHERE Clause
This PCDE practice question tests your understanding of define data structures and implement sql for business intelligence. 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.
Exhibit
Refer to the exhibit.
CREATE VIEW `myproject.mydataset.sales_summary` AS
SELECT region, SUM(sales) AS total_sales
FROM `myproject.mydataset.sales`
WHERE date >= '2023-01-01'
GROUP BY region;
Refer to the exhibit. The BI team creates a view to summarize sales. When they query the view with an additional WHERE clause on region, they notice that the underlying query still processes the same amount of data regardless of the filter. What is the most likely reason?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "most likely"
Why it matters: Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
Exhibit
Refer to the exhibit.
CREATE VIEW `myproject.mydataset.sales_summary` AS
SELECT region, SUM(sales) AS total_sales
FROM `myproject.mydataset.sales`
WHERE date >= '2023-01-01'
GROUP BY region;
A
The view is a materialized view that refreshes every 30 minutes.
Why wrong: A materialized view would store pre-aggregated data, but the exhibit shows a standard CREATE VIEW.
B
The view's WHERE clause on date is too restrictive, causing a full scan.
Why wrong: The date filter limits rows, but the outer filter on region does not push down.
C
The view uses authorized views, which prevent predicate pushdown.
Why wrong: Authorized views control access but do not affect query performance.
D
The view is a logical view, not a materialized view, so filters on the view do not reduce the scanned data.
Logical views execute the defining query each time; filters are applied after the view query.
The correct choice is that the view is a logical view, not a materialized view, so filters on the view do not reduce the scanned data. This happens because a logical view, also known as a standard view, does not store data; it merely stores the query definition. When you add an outer WHERE clause on region, the database engine cannot perform filter pushdown into the view’s internal logic, meaning the underlying query must still process the full dataset defined by the view before applying the outer filter. On the Google Professional Cloud Database Engineer exam, this concept tests your understanding of how BigQuery and other cloud databases handle view materialization versus query optimization. A common trap is assuming any WHERE clause will reduce data scanned, but with logical views, only filters inside the view definition itself limit the scan. Remember the mnemonic: “Logical views lock the scan; materialized views make the cut.”
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
✓
The view is a logical view, not a materialized view, so filters on the view do not reduce the scanned data.
Option D is correct because a logical view (also known as a standard or non-materialized view) in BigQuery does not store data; it merely stores the SQL query definition. When you query a logical view with an additional WHERE clause, BigQuery does not automatically push that filter down into the view's underlying query unless the view is defined with a specific optimization like a parameterized view or uses a scripting approach. By default, the view's query is executed first, and then the outer filter is applied to the result set, meaning the same amount of underlying data is scanned regardless of the outer filter.
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.
✗
The view is a materialized view that refreshes every 30 minutes.
Why it's wrong here
A materialized view would store pre-aggregated data, but the exhibit shows a standard CREATE VIEW.
✗
The view's WHERE clause on date is too restrictive, causing a full scan.
Why it's wrong here
The date filter limits rows, but the outer filter on region does not push down.
✗
The view uses authorized views, which prevent predicate pushdown.
Why it's wrong here
Authorized views control access but do not affect query performance.
✓
The view is a logical view, not a materialized view, so filters on the view do not reduce the scanned data.
Why this is correct
Logical views execute the defining query each time; filters are applied after the view query.
Clue confirmation
The clue word "most likely" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates confuse logical views with materialized views, assuming that any view automatically reduces scanned data when filtered, but in Google Cloud BigQuery, only materialized views or tables with partitioning/clustering support efficient predicate pushdown.
Trap categories for this question
Command / output trap
A materialized view would store pre-aggregated data, but the exhibit shows a standard CREATE VIEW.
Detailed technical explanation
How to think about this question
In BigQuery, logical views are essentially saved SQL queries that are expanded at query time. The query engine processes the view's SQL first, materializes an intermediate result (which may be large), and then applies any outer filters. This behavior contrasts with materialized views or table subqueries where predicate pushdown can occur if the view is defined with a WHERE clause that is compatible with the outer filter. A real-world scenario where this matters is when a BI team creates a view to summarize sales by region but then adds a region filter in the outer query; the view's full aggregation over all regions is computed first, wasting compute and cost.
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.
Define data structures and implement SQL for Business Intelligence — This question tests Define data structures and implement SQL for Business Intelligence — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: The view is a logical view, not a materialized view, so filters on the view do not reduce the scanned data. — Option D is correct because a logical view (also known as a standard or non-materialized view) in BigQuery does not store data; it merely stores the SQL query definition. When you query a logical view with an additional WHERE clause, BigQuery does not automatically push that filter down into the view's underlying query unless the view is defined with a specific optimization like a parameterized view or uses a scripting approach. By default, the view's query is executed first, and then the outer filter is applied to the result set, meaning the same amount of underlying data is scanned regardless of the outer filter.
What should I do if I get this PCDE question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Are there clue words in this question I should notice?
Yes — watch for: "most likely". Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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