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Google Professional Data Engineer

Google Professional Data Engineer

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Your company's BigQuery table, customer_order, contains order history for 10 million customers, totaling 10 PB in size. To enhance the support team's dashboard performance with filters on country_name and username, how should you optimize the table design?

Real Exam



Explanation:

Clustering the table by the country and username fields is the optimal strategy for improving dashboard query performance. This approach groups rows with similar values in these columns together, enhancing query efficiency when filtering on these fields.

  • Option A (Incorrect): Partitioning by _PARTITIONTIME is beneficial for time-based queries but irrelevant for filtering by country and username.
  • Option C (Incorrect): Partitioning alone by country and username does not optimize query performance for filtering operations.
  • Option D (Incorrect): Clustering by country and partitioning by username may not sufficiently improve performance for queries filtering on both fields.
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