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You are tasked with optimizing the structure of IoT sensor data stored in BigQuery for queries that frequently filter by location_id
and device_version
. Which data structuring strategy would best enhance both cost efficiency and performance?
You are tasked with optimizing the structure of IoT sensor data stored in BigQuery for queries that frequently filter by location_id
and device_version
. Which data structuring strategy would best enhance both cost efficiency and performance?
Real Exam
Explanation:
The correct answer is B. Partitioning the table by create_date
reduces the data scanned for date-specific queries, while clustering by location_id
and device_version
groups related data together, improving query performance by minimizing irrelevant data reads.
- Option A suggests clustering by all three fields, which may not be as efficient due to potential over-segmentation.
- Option C proposes partitioning by all three fields, which is less optimal for fields not frequently used in filters.
- Option D incorrectly orders clustering and partitioning, which could hinder performance.