DEA-C02 Exam Dumps | You're tasked with optimizing a Snowflake data pipeline that transforms and loads data into a target

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Question 10/149

You're tasked with optimizing a Snowflake data pipeline that transforms and loads data into a target table. The pipeline uses a series of complex SQL queries with multiple joins and aggregations. After analyzing the query execution plans, you identify a few key bottlenecks. Which of the following optimization techniques would MOST directly address common performance bottlenecks in such a data pipeline within Snowflake?

A. Increasing the virtual warehouse size to the largest available option (e.g., X-Large). The bigger the warehouse, the faster all queries will run.

B. Applying appropriate clustering keys to the target table, ensuring that commonly used filter columns are included in the clustering key definition.

C. Converting all SQL queries to use stored procedures for improved performance and security. Stored procedures execute faster than ad-hoc SQL.

D. Utilizing materialized views to pre-compute and store the results of expensive aggregations, and ensuring the query optimizer rewrites queries to use the materialized views where applicable.

E. Disabling the query result cache to ensure that the most up-to-date data is always used.

Correct Answer: B,D

Options B and D are the most effective. Clustering keys optimize data retrieval based on filter conditions, significantly improving query performance, and materialized views reduce compute costs by storing pre-computed data and the optimizer rewrites to use it where possible, reducing processing time for queries that require those aggregations. Option A is a brute force approach that may not be cost effective. Option C is generally incorrect because it is not the most cost effecient method. Option E would negatively affect performance.

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