Streams for change data capture in Snowflake - Mini Project: Build & Apply

Streams for change data capture

📖 Scenario: You work as a cloud data engineer. Your team wants to track changes in a customer orders table in Snowflake. They want to capture inserts, updates, and deletes to analyze order trends over time.

🎯 Goal: Create a Snowflake stream on the orders table to capture all changes (inserts, updates, deletes). This stream will help downstream processes detect data changes efficiently.

📋 What You'll Learn

Create a table called orders with columns order_id (integer), customer_id (integer), and order_status (string).

Create a stream called orders_stream on the orders table to capture all change data.

Use the stream to select all changed rows with metadata columns.

Add a final query to consume the stream data.

💡 Why This Matters

🌍 Real World

Streams in Snowflake help track data changes efficiently without scanning entire tables. This is useful for auditing, incremental data pipelines, and real-time analytics.

💼 Career

Data engineers and cloud architects use streams to build scalable, event-driven data workflows and maintain data consistency across systems.

1

Create the orders table

Create a table called orders with columns order_id as INTEGER, customer_id as INTEGER, and order_status as STRING.

Snowflake

# Your code here to create the orders table

Hint

Use CREATE OR REPLACE TABLE orders with the specified columns and types.

2

Create a stream on the orders table

Create a stream called orders_stream on the orders table to capture all changes including inserts, updates, and deletes.

Snowflake

CREATE OR REPLACE TABLE orders (
    order_id INTEGER,
    customer_id INTEGER,
    order_status STRING
);

# Your code here to create the orders_stream stream

Hint

Use CREATE OR REPLACE STREAM orders_stream ON TABLE orders; to create the stream.

3

Select changes from the orders_stream

Write a SELECT query to retrieve all columns and metadata columns from the orders_stream stream.

Snowflake

CREATE OR REPLACE TABLE orders (
    order_id INTEGER,
    customer_id INTEGER,
    order_status STRING
);

CREATE OR REPLACE STREAM orders_stream ON TABLE orders;

# Your code here to select all columns and metadata from orders_stream

Hint

Use SELECT *, METADATA$ACTION, METADATA$ISUPDATE FROM orders_stream; to get all changes with metadata.

4

Consume the stream data

Write a query to insert all changed rows from orders_stream into a new table called orders_changes. Create the orders_changes table first with the same columns as orders plus change_type as STRING.

Snowflake

CREATE OR REPLACE TABLE orders (
    order_id INTEGER,
    customer_id INTEGER,
    order_status STRING
);

CREATE OR REPLACE STREAM orders_stream ON TABLE orders;

SELECT *, METADATA$ACTION, METADATA$ISUPDATE FROM orders_stream;

# Your code here to create orders_changes table and insert changes from orders_stream

Hint

Create orders_changes table with a change_type column, then insert changes from orders_stream using METADATA$ACTION.

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