ExpertMedium1 markMultiple Choice
GCP PCA · Question 46 · Technical Requirements
Your data analytics team runs queries against a 100 TB BigQuery table containing 5 years of sales data. Most queries filter by the 'transaction_date' and group by 'store_id'. The queries are currently scanning the entire table, resulting in high costs and slow performance. Which TWO optimizations should you apply? (Select TWO)
Your data analytics team runs queries against a 100 TB BigQuery table containing 5 years of sales data. Most queries filter by the 'transaction_date' and group by 'store_id'. The queries are currently scanning the entire table, resulting in high costs and slow performance. Which TWO optimizations should you apply? (Select TWO)
Answer options:
A.
Partition the table by 'transaction_date'
B.
Cluster the table by 'store_id'
C.
Export the data to Cloud Storage and query it using external tables
D.
Change the BigQuery pricing model to flat-rate
E.
Create a separate BigQuery dataset for each store
How to approach this question
Identify the two primary methods for optimizing BigQuery table structure.
Full Answer
Partitioning and Clustering are the two most important performance and cost optimization techniques in BigQuery. Partitioning by date prevents the query engine from scanning data outside the requested time range. Clustering sorts that data, making aggregations (GROUP BY) much faster.
Common mistakes
Choosing flat-rate pricing (D) to solve a technical inefficiency.
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