Medium1 markMultiple Choice
Subtask 5.3: Manage implementation and optimize costsBigQueryCost OptimizationData & Analytics

GCP PCA · Question 47 · Manage implementation and optimize costs

Your data analytics team is running complex SQL queries on a 100 TB BigQuery table. The queries are scanning the entire table every time, resulting in massive costs. The queries typically filter data by a transaction_date column and group results by a country_code column. Which TWO BigQuery features should you implement to reduce the amount of data scanned and lower costs? (Select TWO)

Answer options:

A.

Partition the table by transaction_date

B.

Cluster the table by country_code

C.

Change the BigQuery billing model from On-demand to Flat-rate

D.

Export the data to Cloud Storage and query it using external tables

E.

Create a materialized view for every possible country code

How to approach this question

Identify the two primary BigQuery table optimization techniques.

Full Answer

Partition the table by `transaction_date`, Cluster the table by `country_code`
Partitioning and Clustering are the two most powerful ways to optimize BigQuery costs and performance. Partitioning by date ensures queries only scan specific days/months. Clustering by frequently filtered columns (like country_code) organizes the data so BigQuery can skip irrelevant blocks during execution.

Common mistakes

Assuming changing the billing model (C) optimizes the queries. It only changes how you pay, not how efficiently the system runs.

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