Google Professional Data Engineer

Explanation

Option B is correct because:

• Partition by create_date: Date-based partitioning is ideal for time-series data as it allows BigQuery to scan only relevant partitions during queries
• Cluster by location_id and device_version: Clustering organizes data within partitions, enabling efficient filtering and sorting
• Cost optimization: Partitioning reduces the amount of data scanned, directly lowering query costs
• Performance optimization: Clustering improves query performance by organizing data for common filter patterns

Why other options are incorrect:

• Option A: You cannot partition by multiple columns in BigQuery - only one partition column is allowed
• Option C: Clustering alone doesn't provide the same cost benefits as partitioning for time-based queries
• Option D: This has incorrect syntax (locationed instead of location_id) and partitions by non-date columns which is less efficient

This combination of partitioning and clustering follows BigQuery best practices for optimizing both cost and performance.