DEA-C02 Exam Dumps | You are tasked with optimizing a continuous data pipeline that loads data from an external stage into

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Question 4/149

You are tasked with optimizing a continuous data pipeline that loads data from an external stage into a Snowflake table using streams.
The pipeline is experiencing significant latency during peak hours. The stream is defined on a very large table with frequent updates and deletes. Which of the following strategies would be MOST effective in reducing the latency of the data pipeline, considering stream performance and cost implications?

A. Increase the size of the virtual warehouse used for loading data. This will provide more compute resources for processing the stream.

B. Implement a more aggressive pruning strategy on the base table to reduce the amount of data that the stream needs to track.

C. Create multiple streams on the same base table, each filtering for specific types of changes (e.g., INSERT, UPDATE, DELETE).

D. Reduce the RETENTION TIME of the stream. This will limit the amount of historical data tracked and improve performance.

E. Implement a materialized view on top of the stream to pre-aggregate the data.

Correct Answer: B

Pruning on the base table directly reduces the amount of data the stream has to track, therefore improving performance. Increasing warehouse size (A) might help but is not directly related to the stream's efficiency. Creating multiple streams (C) will likely increase the overhead. Reducing RETENTION _ TIME (D) might lead to data loss if changes are not consumed promptly. A materialized view (E) consumes credits and does not directly affect stream performance. The correct answer focuses on minimizing the workload for the stream itself.

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