Why Snowflake separates compute from storage - Test Your Understanding

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a virtual warehouse in Snowflake.

Snowflake

CREATE WAREHOUSE [1] WITH WAREHOUSE_SIZE = 'SMALL';

Drag options to blanks, or click blank then click option'

Amy_warehouse

Bstorage_account

Cdatabase_name

Duser_role

Attempts:

3 left

💡 Hint

Common Mistakes

Using storage or database names instead of warehouse name.

The warehouse name identifies the compute resource in Snowflake.

2fill in blank

medium

Complete the code to create a database in Snowflake.

Snowflake

CREATE DATABASE [1];

Drag options to blanks, or click blank then click option'

Asales_db

Bcompute_cluster

Cwarehouse_size

Duser_role

Attempts:

3 left

💡 Hint

Common Mistakes

Using compute or role names instead of database name.

The database stores data separately from compute in Snowflake.

3fill in blank

hard

Fix the error in the command to start a warehouse.

Snowflake

ALTER WAREHOUSE [1] RESUME;

Drag options to blanks, or click blank then click option'

Astorage_account

Bsales_db

Cmy_warehouse

Duser_role

Attempts:

3 left

💡 Hint

Common Mistakes

Trying to resume a database or storage instead of warehouse.

Only a warehouse (compute) can be resumed, not a database or storage.

4fill in blank

hard

Fill both blanks to create a warehouse with auto suspend and resume enabled.

Snowflake

CREATE WAREHOUSE my_warehouse WITH AUTO_SUSPEND = [1] AUTO_RESUME = [2];

Drag options to blanks, or click blank then click option'

A300

BTRUE

CFALSE

D0

Attempts:

3 left

💡 Hint

Common Mistakes

Using FALSE for auto resume disables it.

Using 0 disables auto suspend.

Auto suspend time is in seconds (300 = 5 minutes), and auto resume is enabled with TRUE.

5fill in blank

hard

Fill all three blanks to query data using a warehouse and database.

Snowflake

USE WAREHOUSE [1];
USE DATABASE [2];
SELECT * FROM [3].customers LIMIT 5;

Drag options to blanks, or click blank then click option'

Amy_warehouse

Bsales_db

Cpublic

Duser_role

Attempts:

3 left

💡 Hint

Common Mistakes

Using role instead of schema.

Mixing warehouse and database names.

You select the warehouse (compute), then the database (storage), then the schema (public) to query data.

Practice

1. Why does Snowflake separate compute from storage?

easy

A. To combine compute and storage for faster processing

B. To store data only on local machines

C. To allow independent scaling of compute and storage resources

D. To limit the number of users accessing data

Solution

1. Step 1: Understand Snowflake's architecture

   Snowflake separates compute (processing power) and storage (data saved) so they can work independently.

2. Step 2: Identify the benefit of separation

   This separation allows users to scale compute resources up or down without affecting stored data, improving flexibility and cost.

3. Final Answer:

   To allow independent scaling of compute and storage resources -> Option C

4. Quick Check:

   Separation means independent scaling = A [OK]

Hint: Think: compute and storage can grow separately [OK]

Common Mistakes:

• Confusing separation with combining compute and storage
• Thinking data is stored only locally
• Believing separation limits user access

2. Which of the following is the correct way to describe Snowflake's compute and storage separation?

easy

A. Compute resources can be paused without affecting stored data

B. Storage automatically scales with compute usage

C. Compute and storage are tightly coupled in one system

D. Compute and storage must always scale together

Solution

1. Step 1: Review compute and storage behavior

   Snowflake allows compute (warehouses) to be paused or resized without impacting stored data.

2. Step 2: Match the correct description

   Compute resources can be paused without affecting stored data correctly states compute can be paused independently, which is a key feature.

3. Final Answer:

   Compute resources can be paused without affecting stored data -> Option A

4. Quick Check:

   Compute pause independent of storage = C [OK]

Hint: Remember: compute can pause, storage stays safe [OK]

Common Mistakes:

• Thinking compute and storage are tightly linked
• Assuming storage scales automatically with compute
• Believing compute and storage must scale together

3. Consider this scenario: You run multiple queries on Snowflake using different virtual warehouses. What is the main advantage of Snowflake's compute-storage separation in this case?

medium

A. Queries run slower because compute and storage are separate

B. Each warehouse can scale independently without data duplication

C. Data must be copied for each warehouse to run queries

D. Storage costs increase with each warehouse

Solution

1. Step 1: Analyze multiple warehouses running queries

   Snowflake allows multiple compute clusters (warehouses) to access the same storage without copying data.

2. Step 2: Understand the benefit of independent scaling

   Each warehouse can scale or pause independently, improving performance and cost without duplicating data.

3. Final Answer:

   Each warehouse can scale independently without data duplication -> Option B

4. Quick Check:

   Independent scaling, no data copy = D [OK]

Hint: Multiple warehouses share storage, no copies needed [OK]

Common Mistakes:

• Assuming data is copied for each warehouse
• Thinking compute-storage separation slows queries
• Believing storage costs rise with more warehouses

4. You notice your Snowflake compute warehouse is running slowly. You try to scale up compute but the performance does not improve. What could be a reason related to compute-storage separation?

medium

A. Compute and storage must be scaled together to improve speed

B. Compute warehouses cannot be resized after creation

C. Scaling compute automatically scales storage too

D. Storage is the bottleneck, not compute, since they are separate

Solution

1. Step 1: Understand compute-storage bottlenecks

   Since compute and storage are separate, scaling compute won't help if storage speed limits performance.

2. Step 2: Identify the correct reason

   Storage is the bottleneck, not compute, since they are separate correctly points out storage could be the bottleneck even if compute is scaled.

3. Final Answer:

   Storage is the bottleneck, not compute, since they are separate -> Option D

4. Quick Check:

   Separate storage bottleneck limits speed = B [OK]

Hint: Slow queries? Check storage bottleneck, not just compute [OK]

Common Mistakes:

• Assuming compute and storage scale together
• Believing compute cannot be resized
• Thinking scaling compute always fixes performance

5. You want to optimize costs and performance in Snowflake by using multiple virtual warehouses for different teams. How does Snowflake's separation of compute and storage help you achieve this?

hard

A. You can pause or resize warehouses independently while sharing the same data storage

B. You must create separate copies of data for each warehouse to avoid conflicts

C. Storage costs increase with each warehouse you create

D. Compute and storage are combined, so scaling one scales the other automatically

Solution

1. Step 1: Understand cost and performance optimization

   Using multiple warehouses allows teams to work independently without interfering with each other.

2. Step 2: Apply compute-storage separation benefits

   Since compute and storage are separate, warehouses can be paused or resized independently while sharing the same data, saving costs.

3. Final Answer:

   You can pause or resize warehouses independently while sharing the same data storage -> Option A

4. Quick Check:

   Independent warehouse control with shared storage = A [OK]

Hint: Pause or resize warehouses without copying data [OK]

Common Mistakes:

• Thinking data must be copied for each warehouse
• Assuming storage costs rise with more warehouses
• Believing compute and storage always scale together