Streams for change data capture in Snowflake - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ service_behavior

intermediate

Understanding Stream Behavior on Table Updates

You have a Snowflake table users and a stream users_stream defined on it. After performing an UPDATE on some rows in users, what will SELECT * FROM users_stream return?

Snowflake

UPDATE users SET email = '[e-mail]' WHERE user_id = 123;

A It returns the changed rows with both old and new values for the updated columns.

B It returns only the new values of the updated rows without old values.

C It returns all rows from the users table regardless of changes.

D It returns an empty result because streams do not capture updates.

💡 Hint

Think about what a stream captures when rows are updated.

Snowflake streams capture change data including both old and new values for updated rows, allowing you to see what changed.

❓ Architecture

intermediate

Choosing Stream Type for CDC

You want to capture all changes (inserts, updates, deletes) on a Snowflake table for downstream processing. Which stream type should you create?

A A standard stream on the table.

B A materialized view on the table.

C A change tracking stream on the table.

D A transient table with triggers.

💡 Hint

Consider which stream type captures all DML changes.

Standard streams capture inserts, updates, and deletes for CDC. Change tracking streams only track row-level changes without old values.

❓ security

advanced

Stream Access Control

Which Snowflake privilege is required for a user to read data from a stream?

A SELECT privilege on the underlying table only.

B CREATE STREAM privilege on the database.

C USAGE privilege on the stream and SELECT privilege on the underlying table.

D OWNERSHIP privilege on the stream only.

💡 Hint

Think about what permissions are needed to access both the stream and its data source.

To read from a stream, a user needs USAGE privilege on the stream itself and SELECT privilege on the underlying table.

❓ Configuration

advanced

Stream Behavior After Consuming Changes

What happens to the data in a Snowflake stream after you run SELECT * FROM stream_name without using DELETE or MERGE to consume the changes?

A The stream data is cleared automatically after the SELECT.

B The stream resets and starts capturing changes from scratch.

C The stream data is lost and cannot be recovered.

D The stream continues to show the same changes until they are consumed by DML statements.

💡 Hint

Consider how streams track consumption of changes.

Streams retain change data until it is consumed by DML operations like DELETE or MERGE. A simple SELECT does not consume changes.

✅ Best Practice

expert

Optimizing Stream Usage for Large Tables

You have a very large table with frequent changes and a stream defined on it. To minimize storage costs and improve performance, which practice is best when consuming stream data?

A Run <code>SELECT * FROM stream</code> multiple times before consuming changes.

B Consume stream data frequently using MERGE statements to clear changes promptly.

C Drop and recreate the stream daily to reset change tracking.

D Disable the stream when not in use to save storage.

💡 Hint

Think about how to keep stream data size manageable.

Frequent consumption of stream data using MERGE or DELETE clears the change data, reducing storage and improving performance.

Practice

1. What is the main purpose of a stream in Snowflake for change data capture?

easy

A. To automatically delete old data from a table

B. To create a full backup of the table data every hour

C. To track only the changes (inserts, updates, deletes) on a table without copying all data

D. To replicate data to another database in real-time

Solution

1. Step 1: Understand the role of streams

   Streams in Snowflake track changes like inserts, updates, and deletes on a table without copying the entire data.

2. Step 2: Compare options with stream purpose

   Options A, B, and D describe deletion, backup, and replication, which are not the main function of streams.

3. Final Answer:

   To track only the changes (inserts, updates, deletes) on a table without copying all data -> Option C

4. Quick Check:

   Streams track changes = C [OK]

Hint: Streams track only changes, not full data copies [OK]

Common Mistakes:

• Thinking streams copy full table data
• Confusing streams with backups
• Assuming streams delete data automatically

2. Which of the following is the correct syntax to create a stream on a table named orders in Snowflake?

easy

A. CREATE STREAM orders_stream ON TABLE orders;

B. CREATE STREAM orders_stream FOR TABLE orders;

C. CREATE STREAM orders_stream ON orders;

D. CREATE STREAM orders_stream FROM orders;

Solution

1. Step 1: Recall Snowflake stream creation syntax

   The correct syntax uses CREATE STREAM <name> ON TABLE <table_name>.

2. Step 2: Match options with syntax

   CREATE STREAM orders_stream ON TABLE orders; matches the correct syntax exactly. Options B, C, and D use incorrect keywords or omit TABLE.

3. Final Answer:

   CREATE STREAM orders_stream ON TABLE orders; -> Option A

4. Quick Check:

   CREATE STREAM ... ON TABLE ... = A [OK]

Hint: Use ON TABLE keyword when creating streams [OK]

Common Mistakes:

• Omitting ON TABLE keywords
• Using FOR TABLE instead of ON TABLE
• Using FROM instead of ON TABLE

3. Given a stream orders_stream on table orders, what will the following query return?

SELECT * FROM orders_stream;

Assume some rows were inserted and updated since the last query.

medium

A. Only the rows that were inserted or updated since the last query

B. An error because streams cannot be queried directly

C. Only the rows that were deleted from the orders table

D. All rows from the orders table

Solution

1. Step 1: Understand what querying a stream returns

   Querying a stream returns the changed rows (inserts, updates, deletes) since the last time it was queried or consumed.

2. Step 2: Analyze the query behavior

   The query selects all changes from orders_stream, so it returns only inserted or updated rows since last read, not all rows or errors.

3. Final Answer:

   Only the rows that were inserted or updated since the last query -> Option A

4. Quick Check:

   Streams return changed rows = D [OK]

Hint: Streams return only changed rows since last read [OK]

Common Mistakes:

• Thinking streams return full table data
• Assuming streams return deleted rows only
• Believing streams cannot be queried

4. You created a stream on a table but notice it does not capture existing rows as inserts initially. What is the likely cause?

medium

A. The stream was created with the wrong table name

B. Streams only capture changes made to the table after the stream was created

C. Streams do not capture inserts, only updates and deletes

D. The table is empty, so no rows to capture

Solution

1. Step 1: Recall stream behavior for existing rows

   Streams in Snowflake track only DML changes made after the stream is created. Existing rows are not captured as inserts.

2. Step 2: Evaluate other options

   The stream was created with the wrong table name would cause errors, not missing initial rows. Streams do not capture inserts, only updates and deletes is false; streams capture inserts too. The table is empty, so no rows to capture is possible but less likely if table has data.

3. Final Answer:

   Streams only capture changes made to the table after the stream was created -> Option B

4. Quick Check:

   Streams capture post-creation changes only [OK]

Hint: Streams track post-creation changes only [OK]

Common Mistakes:

• Not realizing streams only track post-creation changes
• Assuming streams capture only updates and deletes
• Confusing stream creation errors with missing data

5. You want to process only new and changed rows from a large sales table daily. Which approach using streams is best to minimize resource use and ensure no data is missed?

hard

A. Create a stream and query the full sales table daily

B. Create multiple streams on sales for inserts, updates, and deletes separately

C. Create a stream and never consume it, just query the sales table directly

D. Create a stream on sales and consume the stream daily

Solution

1. Step 1: Understand efficient change capture

   Create a stream to track changes since creation, then consume it daily to process only new changes efficiently.

2. Step 2: Evaluate resource efficiency and correctness

   Consuming the stream daily processes only changes, saving resources. A queries full table daily, wasting resources. C never consumes but queries full table, missing stream benefits. D is unnecessary complexity.

3. Final Answer:

   Create a stream on sales and consume the stream daily -> Option D

4. Quick Check:

   Stream + daily consume = efficient change capture [OK]

Hint: Create stream and consume daily for efficiency [OK]

Common Mistakes:

• Querying full table instead of consuming stream
• Not consuming the stream regularly
• Creating multiple unnecessary streams