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Answer: Use a Snowpark-optimized virtual warehouse.
The question focuses on accelerating machine learning model training in Snowflake. Based on the community discussion and Snowflake best practices, option C (Use a Snowpark-optimized virtual warehouse) is the optimal choice. Snowpark-optimized warehouses are specifically designed for memory-intensive workloads like ML training, providing up to 16× more memory and 10× more local cache per node compared to standard warehouses. This directly addresses the performance bottleneck in ML training. Option A (Increase warehouse size) may help but doesn't provide the specialized memory optimization. Option B (Add clusters) improves concurrency, not individual job performance. Option D (Query Acceleration Service) optimizes analytic queries, not ML training workloads. The community consensus strongly supports C with 83% of votes and detailed technical explanations.
Author: LeetQuiz Editorial Team
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A team is training a machine learning model using the latest Snowflake features, but the training process is taking significantly longer than anticipated.
Which action should be taken to speed up the model training?
A
Increase the size of the virtual warehouse.
B
Add additional clusters to the virtual warehouse.
C
Use a Snowpark-optimized virtual warehouse.
D
Enable the query acceleration service.
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