The answer is that the ORDER BY clause forces sorting of the entire dataset in memory on a single worker. This is the most likely cause of an out-of-memory error in BigQuery because, in a massively parallel processing (MPP) system, sorting is not a distributable operation by default—all rows must be collected and sorted on one node, which can exceed that node’s memory limit when the dataset is large. On the Google Professional Cloud Database Engineer exam, this concept tests your understanding of how distributed SQL engines handle non-distributable operations; a common trap is assuming BigQuery automatically parallelizes all operations, but ORDER BY without explicit partitioning or window functions creates a single-node bottleneck. To remember this: think “ORDER BY = one worker’s burden,” and if you need to sort large data, use a window function with PARTITION BY to distribute the load.
PCDE Practice Question: Define data structures and implement SQL for Business Intelligence
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.
-- BigQuery error:
Query error: Resources exceeded during query execution: Out of memory while processing this query.
-- Query:
SELECT
product_id,
SUM(sales) AS total_sales
FROM
`project.dataset.sales`
ORDER BY
total_sales DESC;
A user runs the query above on a large table and receives an out-of-memory error. What is the most likely cause?
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.
Refer to the exhibit.
-- BigQuery error:
Query error: Resources exceeded during query execution: Out of memory while processing this query.
-- Query:
SELECT
product_id,
SUM(sales) AS total_sales
FROM
`project.dataset.sales`
ORDER BY
total_sales DESC;
A
The table is a materialized view that cannot handle ORDER BY
Why wrong: Materialized views are not relevant; the error is about query execution resources.
B
The query uses COUNT(*) without a GROUP BY
Why wrong: COUNT(*) alone does not cause memory exhaustion; the issue is the ORDER BY.
C
The ORDER BY clause forces sorting of the entire dataset in memory on a single worker
Sorting large datasets requires memory proportional to the data size; if it exceeds available memory, the query fails.
D
The table is not partitioned, so full table scan causes memory overflow
Why wrong: Full table scan uses columnar storage and streaming, not memory; OOM is due to sorting.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
The ORDER BY clause forces sorting of the entire dataset in memory on a single worker
Option C is correct because the ORDER BY clause in a distributed SQL engine like Snowflake or BigQuery forces all data to be sent to a single worker node for sorting, which can exceed the memory limit of that node when the dataset is large. This is a common cause of out-of-memory errors in MPP (Massively Parallel Processing) systems, as sorting is not a distributable operation by default without explicit partitioning or window functions.
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 table is a materialized view that cannot handle ORDER BY
Why it's wrong here
Materialized views are not relevant; the error is about query execution resources.
✗
The query uses COUNT(*) without a GROUP BY
Why it's wrong here
COUNT(*) alone does not cause memory exhaustion; the issue is the ORDER BY.
✓
The ORDER BY clause forces sorting of the entire dataset in memory on a single worker
Why this is correct
Sorting large datasets requires memory proportional to the data size; if it exceeds available memory, the query fails.
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.
✗
The table is not partitioned, so full table scan causes memory overflow
Why it's wrong here
Full table scan uses columnar storage and streaming, not memory; OOM is due to sorting.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google Cloud often tests the misconception that any full table scan causes memory errors, but the real trap is that ORDER BY is a blocking operation that centralizes data, making it the primary culprit for out-of-memory errors in distributed systems.
Detailed technical explanation
How to think about this question
In distributed SQL engines like Snowflake, ORDER BY without a LIMIT or window function triggers a global sort that requires all data to be shuffled to a single compute node, where it is sorted in memory. This is distinct from a local sort within partitions, which can be distributed. A common mitigation is to use a LIMIT clause or a window function with PARTITION BY to enable distributed sorting, or to increase the warehouse size in Snowflake to allocate more memory per node.
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 ORDER BY clause forces sorting of the entire dataset in memory on a single worker — Option C is correct because the ORDER BY clause in a distributed SQL engine like Snowflake or BigQuery forces all data to be sent to a single worker node for sorting, which can exceed the memory limit of that node when the dataset is large. This is a common cause of out-of-memory errors in MPP (Massively Parallel Processing) systems, as sorting is not a distributable operation by default without explicit partitioning or window functions.
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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Question Discussion
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