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. A key principle to apply: partitioned table. 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 TABLE mydataset.fact_sales (
sale_id INT64,
product_id INT64,
sale_date DATE,
amount FLOAT64
)
PARTITION BY DATE_TRUNC(sale_date, MONTH)
CLUSTER BY product_id
OPTIONS(require_partition_filter=true);
A BI team queries this table with a WHERE clause that filters on product_id but does not include a sale_date filter. What is the outcome?
Exhibit
Refer to the exhibit.
CREATE TABLE mydataset.fact_sales (
sale_id INT64,
product_id INT64,
sale_date DATE,
amount FLOAT64
)
PARTITION BY DATE_TRUNC(sale_date, MONTH)
CLUSTER BY product_id
OPTIONS(require_partition_filter=true);
A
The query fails with an error.
Why wrong: Option A is incorrect because without require_partition_filter, the query does not error. It only errors if the table has require_partition_filter enabled.
B
The query runs successfully and only scans partitions containing product_id values.
Why wrong: Option B is incorrect because partition pruning only works on the partition key column (sale_date), not on product_id.
C
The query runs successfully and scans only the latest partition.
Why wrong: Option C is incorrect because the query scans all partitions, not just the latest one.
D
The query runs successfully but scans all partitions.
Option D is correct: the query runs successfully and scans all partitions because no partition pruning is possible.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
The query runs successfully but scans all partitions.
In BigQuery, when a table is partitioned on sale_date but the WHERE clause filters only on product_id (without sale_date), the query cannot prune partitions. Without the require_partition_filter option, the query runs successfully but scans all partitions. Option D correctly describes this outcome.
Key principle: Partitioned table
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 query fails with an error.
Why it's wrong here
Option A is incorrect because without require_partition_filter, the query does not error. It only errors if the table has require_partition_filter enabled.
✗
The query runs successfully and only scans partitions containing product_id values.
Why it's wrong here
Option B is incorrect because partition pruning only works on the partition key column (sale_date), not on product_id.
✗
The query runs successfully and scans only the latest partition.
Why it's wrong here
Option C is incorrect because the query scans all partitions, not just the latest one.
✓
The query runs successfully but scans all partitions.
Why this is correct
Option D is correct: the query runs successfully and scans all partitions because no partition pruning is possible.
Related concept
Partitioned table
Common exam traps
Common exam trap: answer the scenario, not the keyword
Candidates often assume that any column filter enables partition pruning, but only the partition key can prune partitions. Without require_partition_filter, omitting the partition key results in a full scan, not an error.
Detailed technical explanation
How to think about this question
Under the hood, partition pruning is a performance optimization that uses the partition column's metadata to skip irrelevant files or directories. In systems like Apache Hive or Spark, if the partition column is missing from the WHERE clause, the engine must list all partition directories, which can be expensive but does not cause an error. However, in some cloud data warehouses (e.g., Google BigQuery with clustering but no partitioning on `sale_date`) or in strict SQL modes, the query may fail if the table is designed to require partition pruning for cost control. A real-world scenario is a partitioned fact table in a data lake where analysts must always filter by date to avoid scanning years of data, and the system is configured to reject queries without a partition filter to prevent runaway costs.
KKey Concepts to Remember
Partitioned table
Partition pruning
require_partition_filter
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
Partitioned table
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. Partitioned table 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.
Review partitioned table, then practise related PCDE questions on the same topic to reinforce the concept.
Define data structures and implement SQL for Business Intelligence — This question tests Define data structures and implement SQL for Business Intelligence — Partitioned table.
What is the correct answer to this question?
The correct answer is: The query runs successfully but scans all partitions. — In BigQuery, when a table is partitioned on sale_date but the WHERE clause filters only on product_id (without sale_date), the query cannot prune partitions. Without the require_partition_filter option, the query runs successfully but scans all partitions. Option D correctly describes this outcome.
What should I do if I get this PCDE question wrong?
Review partitioned table, then practise related PCDE questions on the same topic to reinforce the concept.
What is the key concept behind this question?
Partitioned table
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