Which type of workload is recommended for Snowpark-optimized virtual warehouses?

The correct answer is B. Workloads that have large memory requirements. Snowpark-optimized warehouses provide significantly more memory per compute node (up to 16x more than standard warehouses), making them ideal for memory-intensive workloads such as training machine learning models, large-scale data transformations using Snowpark DataFrames, or…

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Question

Options

AWorkloads with ad hoc analytics
BWorkloads that have large memory requirements
CWorkloads with unpredictable data volumes for each query
DWorkloads that are queried with small table scans and selective filters

How the community answered

(41 responses)

A
7% (3)
B
88% (36)
C
2% (1)
D
2% (1)

Explanation

Snowpark-optimized warehouses provide significantly more memory per compute node (up to 16x more than standard warehouses), making them ideal for memory-intensive workloads such as training machine learning models, large-scale data transformations using Snowpark DataFrames, or executing UDFs that process large datasets. Ad hoc analytics (A), unpredictable data volumes (C), and small table scans with selective filters (D) are typical candidates for standard virtual warehouses and do not require the elevated memory profile.

Topics

#Snowpark-optimized warehouses#Virtual warehouses#Memory optimization#Workload management

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