The answer is to add a WHERE clause to filter out NULLs from the join key. This is correct because in standard SQL, NULL is not equal to anything, including another NULL, so attempting to join on a column with many NULL values forces the database to process these non-matching rows, dramatically increasing the cardinality of the join operation and often causing performance degradation or errors. On the Google Professional Cloud Database Engineer exam, this scenario tests your understanding of how BigQuery handles NULL semantics in joins, a common pitfall when working with high-cardinality columns that contain sparse data. The trap is assuming that NULL values will simply be ignored or matched to each other, when in reality they must be explicitly excluded. A useful memory tip: NULL is not a value, it is the absence of a value, so it cannot participate in an equality join—filter it out first.
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. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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.
Error log from BigQuery job: 'Query exceeded resource limits. In particular, the query used too many shuffles. Consider using a more selective filter or joining on more evenly distributed keys.'
A data analyst runs a query that joins two large tables on a high-cardinality column with many NULL values. Which action is most likely to resolve the error?
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.
Error log from BigQuery job: 'Query exceeded resource limits. In particular, the query used too many shuffles. Consider using a more selective filter or joining on more evenly distributed keys.'
A
Use a DISTINCT clause on the join key.
Why wrong: DISTINCT does not reduce shuffle for joins.
B
Increase the query timeout setting.
Why wrong: Timeout does not address resource exhaustion.
C
Add a WHERE clause to filter out NULLs from the join key.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Add a WHERE clause to filter out NULLs from the join key.
Option C is correct because filtering out NULLs from the join key with a WHERE clause prevents the database from attempting to match NULL values, which cannot be equated in a standard SQL join (since NULL != NULL). This reduces the cardinality of the join operation and avoids potential performance degradation or errors caused by the large number of NULLs being processed in a high-cardinality column.
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.
✗
Use a DISTINCT clause on the join key.
Why it's wrong here
DISTINCT does not reduce shuffle for joins.
✗
Increase the query timeout setting.
Why it's wrong here
Timeout does not address resource exhaustion.
✓
Add a WHERE clause to filter out NULLs from the join key.
Why this is correct
Filtering NULLs reduces row count and shuffle.
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.
✗
Use a UNION ALL to combine tables.
Why it's wrong here
UNION ALL increases data volume.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may think increasing the timeout (Option B) is a universal fix for any query error, when in reality the error is often due to resource exhaustion from NULL handling, not insufficient execution time.
Detailed technical explanation
How to think about this question
In SQL, NULL is not equal to any value, including another NULL, so a standard INNER JOIN or LEFT JOIN on a column with NULLs will never match those rows, but the database still must scan and process them, leading to unnecessary overhead. In Snowflake or similar platforms, high-cardinality columns with many NULLs can cause skewed join distributions, especially in hash joins, where NULLs are all sent to a single node, potentially causing out-of-memory errors. Filtering out NULLs early reduces the join input size and avoids this skew, improving query performance and stability.
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: Add a WHERE clause to filter out NULLs from the join key. — Option C is correct because filtering out NULLs from the join key with a WHERE clause prevents the database from attempting to match NULL values, which cannot be equated in a standard SQL join (since NULL != NULL). This reduces the cardinality of the join operation and avoids potential performance degradation or errors caused by the large number of NULLs being processed in a high-cardinality column.
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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