Two users share a virtual warehouse named wh dev 01. When one of the users loads data, the other one experiences performance issues while querying data. How does Snowflake recommend resolving this…

The correct answer is C. Create separate warehouses for each workload. Snowflake's best practice is to separate workloads into dedicated warehouses (C). Data loading (ELT/ETL) and interactive querying have very different resource profiles and query patterns. Mixing them on the same warehouse causes resource contention and query queuing. Creating a…

Performance Management

Question

Two users share a virtual warehouse named wh dev 01. When one of the users loads data, the other one experiences performance issues while querying data. How does Snowflake recommend resolving this issue?

Options

AScale up the existing warehouse.
BCreate separate warehouses for each user.
CCreate separate warehouses for each workload.
DStop loading and querying data at the same time.

How the community answered

(59 responses)

A
10% (6)
B
5% (3)
C
81% (48)
D
3% (2)

Explanation

Snowflake's best practice is to separate workloads into dedicated warehouses (C). Data loading (ELT/ETL) and interactive querying have very different resource profiles and query patterns. Mixing them on the same warehouse causes resource contention and query queuing. Creating a warehouse for loading and a separate one for querying ensures each workload gets predictable, isolated compute resources. Scaling up the shared warehouse (A) would help temporarily but doesn't eliminate contention. Separating by user (B) is less precise than separating by workload type.

Topics

#Virtual Warehouses#Workload Isolation#Performance Optimization#Concurrency

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