A company is implementing a machine learning use case on a very large dataset that will need high volumes of memory and compute resources.
How should this Snowflake architecture be designed to satisfy these requirements?
Snowpark-optimized virtual warehouses are designed for Snowpark workloads with large memory requirements and are specifically suitable for machine learning training that needs substantial memory and compute resources. Multi-cluster warehouses primarily scale for concurrency, whereas search optimization and query acceleration target SQL query performance rather than high-memory ML workloads.
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