Views and materialized views in Snowflake - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a simple view named employee_view that selects all columns from the employees table.

Snowflake

CREATE VIEW employee_view AS SELECT * FROM [1];

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

Adepartments

Bemployees

Csalaries

Dlocations

Attempts:

3 left

💡 Hint

Common Mistakes

Choosing a table unrelated to employees like departments or locations.

Forgetting to use the correct table name.

The view employee_view should select from the employees table to show employee data.

2fill in blank

medium

Complete the code to create a materialized view named sales_summary that sums the amount column from the sales table.

Snowflake

CREATE MATERIALIZED VIEW sales_summary AS SELECT SUM([1]) AS total_amount FROM sales;

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

Aamount

Bquantity

Cprice

Ddiscount

Attempts:

3 left

💡 Hint

Common Mistakes

Summing the wrong column like quantity or discount.

Using a column that does not exist in the sales table.

The materialized view sums the amount column to get total sales.

3fill in blank

hard

Fix the error in the code to create a view named dept_view that selects department_id and department_name from the departments table.

Snowflake

CREATE VIEW dept_view AS SELECT department_id, [1] FROM departments;

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

Adepartment_name

Bdepartment

Cdept_name

Dname

Attempts:

3 left

💡 Hint

Common Mistakes

Using abbreviated or incorrect column names like dept_name or name.

Using a column that does not exist.

The correct column name is department_name to match the table schema.

4fill in blank

hard

Fill both blanks to create a materialized view named active_customers that selects customer_id and customer_name from customers where status is 'active'.

Snowflake

CREATE MATERIALIZED VIEW active_customers AS SELECT [1], [2] FROM customers WHERE status = 'active';

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

Acustomer_id

Bcustomer_name

Cstatus

Dcustomer_status

Attempts:

3 left

💡 Hint

Common Mistakes

Selecting the status column instead of customer_name.

Using incorrect column names like customer_status.

The materialized view selects customer_id and customer_name to show active customers.

5fill in blank

hard

Fill all three blanks to create a view named order_details_view that selects order_id, product_id, and quantity from the order_details table where quantity is greater than 10.

Snowflake

CREATE VIEW order_details_view AS SELECT [1], [2], [3] FROM order_details WHERE quantity > 10;

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

Aorder_id

Bproduct_id

Cquantity

Dprice

Attempts:

3 left

💡 Hint

Common Mistakes

Including columns not requested like price.

Missing one of the required columns.

The view selects order_id, product_id, and quantity to show orders with quantity over 10.

Practice

1. What is the main difference between a view and a materialized view in Snowflake?

easy

A. A view does not store data, while a materialized view stores query results.

B. A view stores data permanently, but a materialized view does not.

C. A materialized view updates automatically with every query, but a view does not.

D. A view can only be used once, while a materialized view can be reused multiple times.

Solution

1. Step 1: Understand what a view does

   A view saves a query for reuse but does not store the actual data; it runs the query each time.

2. Step 2: Understand what a materialized view does

   A materialized view stores the results of the query physically, so it can return data faster without rerunning the query.

3. Final Answer:

   A view does not store data, while a materialized view stores query results. -> Option A

4. Quick Check:

   View = no stored data, Materialized view = stored data [OK]

Hint: Remember: views save queries, materialized views save data [OK]

Common Mistakes:

• Thinking views store data permanently
• Believing materialized views update instantly with every query
• Confusing reuse capability between views and materialized views

2. Which of the following is the correct syntax to create a materialized view in Snowflake?

easy

A. CREATE VIEW my_view MATERIALIZED AS SELECT * FROM my_table;

B. CREATE MATERIALIZED VIEW my_view AS SELECT * FROM my_table;

C. CREATE MATERIALIZED my_view VIEW AS SELECT * FROM my_table;

D. CREATE VIEW MATERIALIZED my_view AS SELECT * FROM my_table;

Solution

1. Step 1: Recall Snowflake syntax for materialized views

   The correct syntax starts with CREATE MATERIALIZED VIEW followed by the view name and query.

2. Step 2: Check each option's order and keywords

   Only CREATE MATERIALIZED VIEW my_view AS SELECT * FROM my_table; uses the correct order and keywords: CREATE MATERIALIZED VIEW my_view AS SELECT * FROM my_table;

3. Final Answer:

   CREATE MATERIALIZED VIEW my_view AS SELECT * FROM my_table; -> Option B

4. Quick Check:

   Correct syntax = CREATE MATERIALIZED VIEW [OK]

Hint: Materialized view syntax starts with CREATE MATERIALIZED VIEW [OK]

Common Mistakes:

• Mixing order of keywords
• Placing MATERIALIZED after VIEW
• Using incorrect keyword sequences

3. Given the following Snowflake SQL code:

CREATE TABLE sales (id INT, amount FLOAT);
INSERT INTO sales VALUES (1, 100.0), (2, 200.0);
CREATE MATERIALIZED VIEW sales_mv AS SELECT SUM(amount) AS total FROM sales;
INSERT INTO sales VALUES (3, 300.0);
SELECT * FROM sales_mv;

What will the SELECT query return?

medium

A. total = 600.0

B. total = 300.0 (only new rows)

C. total = 300.0 plus previous sums

D. total = 300.0

Solution

1. Step 1: Understand materialized view refresh behavior

   Materialized views in Snowflake do not automatically update after data changes; they show data as of last refresh.

2. Step 2: Analyze the timing of inserts and query

   The materialized view was created after inserting two rows (100.0 + 200.0 = 300.0). The third row (300.0) was inserted after the view creation but before the select.

3. Final Answer:

   total = 300.0 -> Option D

4. Quick Check:

   Materialized view shows data at last refresh, not latest inserts [OK]

Hint: Materialized views show data as of last refresh, not latest inserts [OK]

Common Mistakes:

• Assuming materialized views auto-update instantly
• Adding new rows to materialized view results without refresh
• Confusing materialized views with normal views

4. You created a materialized view in Snowflake but it returns outdated data after table updates. What is the best way to fix this?

medium

A. Use a normal view instead of a materialized view to get fresh data.

B. Drop and recreate the materialized view every time data changes.

C. Manually refresh the materialized view using ALTER MATERIALIZED VIEW ... REFRESH.

D. Restart the Snowflake warehouse to update the materialized view.

Solution

1. Step 1: Identify how to update materialized views

   Materialized views do not update automatically; they require manual refresh to show latest data.

2. Step 2: Choose the correct refresh method

   Snowflake supports manual refresh with ALTER MATERIALIZED VIEW ... REFRESH to update the stored data.

3. Final Answer:

   Manually refresh the materialized view using ALTER MATERIALIZED VIEW ... REFRESH. -> Option C

4. Quick Check:

   Manual refresh updates materialized view data [OK]

Hint: Use ALTER MATERIALIZED VIEW ... REFRESH to update data [OK]

Common Mistakes:

• Dropping and recreating instead of refreshing
• Restarting warehouse has no effect on view data
• Confusing materialized views with normal views for freshness

5. You want to speed up queries that aggregate large sales data but also need the most current totals. Which approach best balances speed and freshness using Snowflake views?

hard

A. Use a materialized view and schedule frequent refreshes to keep data updated.

B. Use a normal view only, since it always shows fresh data but may be slower.

C. Create a materialized view and never refresh it to save compute costs.

D. Use both a normal view and a materialized view simultaneously in the same query.

Solution

1. Step 1: Understand trade-offs between views and materialized views

   Normal views provide fresh data but can be slow on large data; materialized views are fast but need refresh to update.

2. Step 2: Find a balanced solution

   Scheduling frequent refreshes of materialized views keeps data reasonably fresh while improving query speed.

3. Final Answer:

   Use a materialized view and schedule frequent refreshes to keep data updated. -> Option A

4. Quick Check:

   Materialized view + refresh = speed + freshness balance [OK]

Hint: Schedule refreshes on materialized views for fresh and fast data [OK]

Common Mistakes:

• Not refreshing materialized views and expecting fresh data
• Using only normal views and ignoring performance
• Trying to combine views in one query without refresh strategy