Warehouse sizes and scaling in Snowflake - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is a Snowflake warehouse size?

A Snowflake warehouse size determines the compute power available for queries. Sizes range from X-Small to 6X-Large, with bigger sizes providing more compute resources.

beginner

How does scaling a warehouse affect query performance?

Scaling a warehouse increases the number of servers working in parallel, which can speed up query processing and handle more concurrent users.

intermediate

What is the difference between scaling up and scaling out in Snowflake warehouses?

Scaling up means increasing the size of a single warehouse (more power per server). Scaling out means adding more clusters to handle more queries at the same time.

intermediate

What is multi-cluster warehouse scaling in Snowflake?

Multi-cluster warehouses automatically add or remove clusters based on workload, helping to manage high concurrency without slowing down queries.

beginner

Why should you choose the smallest warehouse size that meets your needs?

Choosing the smallest warehouse size saves cost because Snowflake charges based on compute usage. You can always scale up or out later if needed.

What happens when you increase the size of a Snowflake warehouse?

A It gets more compute power per server

B It adds more clusters automatically

C It reduces storage costs

D It decreases query concurrency

Increasing warehouse size means more compute power per server, speeding up queries.

What does multi-cluster warehouse scaling help with?

A Increasing data retention

B Reducing storage size

C Handling more concurrent queries

D Improving network speed

Multi-cluster scaling adds clusters to handle many queries at once, improving concurrency.

Which warehouse size is the smallest in Snowflake?

A Large

B Small

C Medium

D X-Small

X-Small is the smallest warehouse size in Snowflake.

Scaling out a warehouse means:

A Increasing the size of one server

B Adding more clusters to handle workload

C Reducing the number of queries

D Decreasing compute power

Scaling out means adding more clusters to handle more queries simultaneously.

Why is it best to start with a smaller warehouse size?

A It costs less and can be scaled later

B It has more compute power

C It automatically adds clusters

D It stores more data

Starting small saves cost and you can increase size or clusters as needed.

Explain how warehouse size affects performance and cost in Snowflake.

Think about how bigger sizes mean faster queries but higher cost.

Describe the difference between scaling up and scaling out in Snowflake warehouses.

One changes size, the other adds more clusters.

Practice

1. What does the size of a Snowflake warehouse primarily determine?

easy

A. The storage capacity for data

B. The amount of computing power available for queries

C. The number of users who can access the database

D. The network bandwidth for data transfer

Solution

1. Step 1: Understand warehouse size meaning

   Warehouse size in Snowflake controls the compute resources allocated.

2. Step 2: Differentiate from storage and network

   Storage and network bandwidth are managed separately, not by warehouse size.

3. Final Answer:

   The amount of computing power available for queries -> Option B

4. Quick Check:

   Warehouse size = compute power [OK]

Hint: Warehouse size means compute power, not storage or users [OK]

Common Mistakes:

• Confusing warehouse size with storage capacity
• Thinking warehouse size limits user access
• Assuming network bandwidth depends on warehouse size

2. Which Snowflake warehouse size is correctly written in a SQL command to create a warehouse?

easy

A. CREATE WAREHOUSE mywh WAREHOUSE_SIZE = 'LARGE';

B. CREATE WAREHOUSE mywh WAREHOUSE_SIZE = 'medium';

C. CREATE WAREHOUSE mywh WITH WAREHOUSE_SIZE = 'XSMALL';

D. CREATE WAREHOUSE mywh SET SIZE = 'SMALL';

Solution

1. Step 1: Check correct syntax for warehouse size

   The correct syntax uses WAREHOUSE_SIZE = 'SIZE' with uppercase size names.

2. Step 2: Validate option correctness

   CREATE WAREHOUSE mywh WAREHOUSE_SIZE = 'LARGE'; uses correct syntax and valid size 'LARGE'. Others have syntax or size errors.

3. Final Answer:

   CREATE WAREHOUSE mywh WAREHOUSE_SIZE = 'LARGE'; -> Option A

4. Quick Check:

   Correct syntax uses WAREHOUSE_SIZE = 'SIZE' [OK]

Hint: Use WAREHOUSE_SIZE = 'SIZE' with uppercase size [OK]

Common Mistakes:

• Using lowercase size names
• Using WITH keyword
• Using SET SIZE instead of WAREHOUSE_SIZE

3. Given a Snowflake warehouse set to size 'MEDIUM' with auto-suspend enabled at 5 minutes, what happens if no queries run for 6 minutes?

medium

A. The warehouse suspends automatically after 5 minutes of inactivity

B. The warehouse continues running indefinitely

C. The warehouse scales up to a larger size automatically

D. The warehouse deletes all cached data

Solution

1. Step 1: Understand auto-suspend behavior

   Auto-suspend pauses the warehouse after the specified inactivity time to save costs.

2. Step 2: Apply to given time

   Since no queries run for 6 minutes, which is more than 5 minutes, the warehouse suspends.

3. Final Answer:

   The warehouse suspends automatically after 5 minutes of inactivity -> Option A

4. Quick Check:

   Auto-suspend triggers after inactivity time [OK]

Hint: Auto-suspend pauses warehouse after set idle time [OK]

Common Mistakes:

• Thinking warehouse keeps running without queries
• Assuming warehouse scales automatically without manual setting
• Confusing auto-suspend with cache clearing

4. You configured a multi-cluster warehouse with MIN_CLUSTER_COUNT=1 and MAX_CLUSTER_COUNT=3, but queries queue up during peak times. What is the likely cause?

medium

A. The warehouse is suspended manually

B. Warehouse size is too large causing delays

C. Auto-suspend is set to zero minutes

D. Auto-scaling is not enabled or configured incorrectly

Solution

1. Step 1: Understand multi-cluster warehouse scaling

   Multi-cluster warehouses scale clusters between min and max counts automatically if auto-scaling is enabled.

2. Step 2: Identify cause of query queuing

   If queries queue despite max clusters > 1, auto-scaling might be off or misconfigured, preventing cluster addition.

3. Final Answer:

   Auto-scaling is not enabled or configured incorrectly -> Option D

4. Quick Check:

   Multi-cluster needs auto-scaling enabled to add clusters [OK]

Hint: Check auto-scaling enabled for multi-cluster warehouses [OK]

Common Mistakes:

• Assuming large warehouse size fixes queuing
• Confusing auto-suspend with scaling
• Not verifying if warehouse is suspended

5. A company wants to handle unpredictable spikes in query load without manual intervention. Which Snowflake warehouse configuration best supports this?

hard

A. Set warehouse size to X-LARGE and disable auto-suspend

B. Create multiple single-cluster warehouses and switch between them manually

C. Use a multi-cluster warehouse with auto-scaling enabled and set MIN_CLUSTER_COUNT=1, MAX_CLUSTER_COUNT=5

D. Set warehouse size to SMALL and rely on auto-resume only

Solution

1. Step 1: Identify need for handling spikes automatically

   The company wants automatic scaling to handle unpredictable query spikes without manual steps.

2. Step 2: Evaluate options for auto-scaling

   Multi-cluster warehouses with auto-scaling and a range of cluster counts allow dynamic scaling up and down.

3. Step 3: Compare other options

   Set warehouse size to X-LARGE and disable auto-suspend wastes resources by disabling suspend; B requires manual switching; D is too small and lacks scaling.

4. Final Answer:

   Use a multi-cluster warehouse with auto-scaling enabled and set MIN_CLUSTER_COUNT=1, MAX_CLUSTER_COUNT=5 -> Option C

5. Quick Check:

   Multi-cluster auto-scaling handles spikes best [OK]

Hint: Multi-cluster with auto-scaling handles spikes automatically [OK]

Common Mistakes:

• Choosing fixed large size wastes cost
• Relying on manual warehouse switching
• Ignoring cluster count settings