Stream processing patterns in DynamoDB

Introduction

Stream processing patterns help you react quickly to changes in your database. They let you handle data updates as they happen, like a real-time alert system.

You want to update a search index whenever data changes.

You need to send notifications when a new item is added.

You want to keep data in sync between different systems automatically.

You want to analyze data changes for trends or monitoring.

You want to archive or backup data changes continuously.

Syntax

DynamoDB

No direct query syntax; stream processing uses DynamoDB Streams with AWS Lambda functions to react to data changes.

DynamoDB Streams capture item-level changes in your table.

You connect a Lambda function to the stream to process these changes automatically.

Examples

This setup lets your Lambda function receive new or changed items as events.

DynamoDB

1. Enable DynamoDB Streams on your table with NEW_IMAGE option.
2. Create a Lambda function to process stream records.
3. Configure the Lambda trigger to listen to the DynamoDB Stream.

This code logs new items added to the table.

DynamoDB

Example Lambda event handler snippet (Node.js):
exports.handler = async (event) => {
  for (const record of event.Records) {
    if (record.eventName === 'INSERT') {
      console.log('New item added:', record.dynamodb.NewImage);
    }
  }
};

Sample Program

This query shows current data. Stream processing happens outside SQL by reacting to changes.

DynamoDB

-- DynamoDB Streams setup is done in AWS Console or CLI, no SQL query.
-- Example: Query to get current items from table:
SELECT * FROM YourTable;

Important Notes

Stream processing is event-driven, not a query you run directly.

Remember to handle retries and errors in your Lambda function to avoid data loss.

Streams keep data for 24 hours, so process events quickly.

Summary

Stream processing lets you react to data changes in real time.

Use DynamoDB Streams with Lambda functions to implement these patterns.

This helps automate tasks like notifications, syncing, and analytics.

Practice

1. What is the main purpose of using DynamoDB Streams in stream processing patterns?

easy

A. To capture and react to data changes in real time

B. To store large amounts of data permanently

C. To create backups of the database

D. To improve query speed by indexing

Solution

1. Step 1: Understand DynamoDB Streams role

   DynamoDB Streams capture data changes like inserts, updates, and deletes as they happen.

2. Step 2: Identify the purpose in stream processing

   Streams allow applications to react immediately to these changes, enabling real-time processing.

3. Final Answer:

   To capture and react to data changes in real time -> Option A

4. Quick Check:

   Streams = real-time data reaction [OK]

Hint: Streams track changes instantly for real-time reactions [OK]

Common Mistakes:

• Confusing Streams with data storage
• Thinking Streams create backups
• Assuming Streams speed up queries

2. Which of the following is the correct way to enable a DynamoDB Stream on a table?

easy

A. Create a global secondary index with Streams enabled

B. Add a Lambda trigger without enabling Streams

C. Set StreamSpecification with StreamEnabled = true and StreamViewType

D. Use the UpdateItem API to activate Streams

Solution

1. Step 1: Recall how to enable Streams

   Streams are enabled by setting the StreamSpecification property on the table with StreamEnabled set to true and choosing a StreamViewType.

2. Step 2: Evaluate options

   Set StreamSpecification with StreamEnabled = true and StreamViewType correctly describes enabling Streams. The other options do not enable Streams properly.

3. Final Answer:

   Set StreamSpecification with StreamEnabled = true and StreamViewType -> Option C

4. Quick Check:

   Enable Streams via StreamSpecification [OK]

Hint: Enable Streams in table settings, not via Lambda or indexes [OK]

Common Mistakes:

• Trying to enable Streams via Lambda triggers
• Confusing Streams with indexes
• Using UpdateItem API to enable Streams

3. Given a DynamoDB Stream enabled with NEW_IMAGE view type, what will a Lambda function receive when an item is updated?

medium

A. Only the old item image before the update

B. Only the new item image after the update

C. Both old and new item images

D. No item images, only keys

Solution

1. Step 1: Understand StreamViewType NEW_IMAGE

   NEW_IMAGE means the stream records contain the item as it appears after the change.

2. Step 2: Determine what Lambda receives on update

   Lambda gets the new item image only, not the old one or both.

3. Final Answer:

   Only the new item image after the update -> Option B

4. Quick Check:

   NEW_IMAGE = new item data only [OK]

Hint: NEW_IMAGE streams send updated item data only [OK]

Common Mistakes:

• Confusing NEW_IMAGE with OLD_IMAGE or BOTH_IMAGES
• Expecting both old and new images
• Assuming keys only are sent

4. A developer wrote a Lambda function triggered by DynamoDB Streams but it never processes any records. What is the most likely cause?

medium

A. The DynamoDB table does not have Streams enabled

B. The Lambda function code has a syntax error

C. The table has no data at all

D. The Lambda function timeout is too long

Solution

1. Step 1: Check Stream enablement

   If Streams are not enabled on the table, no events trigger Lambda.

2. Step 2: Evaluate other options

   Syntax errors cause failures but do not prevent invocation. No data means no changes, but usually there are some. Timeout too long does not stop invocation.

3. Final Answer:

   The DynamoDB table does not have Streams enabled -> Option A

4. Quick Check:

   Streams must be enabled for Lambda triggers [OK]

Hint: Check if Streams are enabled before debugging Lambda code [OK]

Common Mistakes:

• Assuming code errors stop Lambda from triggering
• Ignoring Streams enablement
• Thinking timeout affects event triggering

5. You want to build a system that sends notifications only when a specific attribute "status" changes in DynamoDB items. Which stream processing pattern best fits this requirement?

hard

A. Use Streams with OLD_IMAGE view type only

B. Disable Streams and poll the table periodically

C. Enable Streams with KEYS_ONLY view type and check keys in Lambda

D. Filter and transform stream records in Lambda to detect "status" changes

Solution

1. Step 1: Understand the need to detect attribute changes

   To detect changes in "status", you need both old and new values to compare.

2. Step 2: Choose the right pattern

   Filtering and transforming stream records in Lambda lets you compare old and new images and trigger notifications only on "status" changes.

3. Step 3: Evaluate other options

   OLD_IMAGE alone lacks new data, KEYS_ONLY lacks attribute data, polling is inefficient and not real-time.

4. Final Answer:

   Filter and transform stream records in Lambda to detect "status" changes -> Option D

5. Quick Check:

   Filter stream records in Lambda for attribute changes [OK]

Hint: Compare old and new images in Lambda to detect attribute changes [OK]

Common Mistakes:

• Using KEYS_ONLY which lacks attribute data
• Relying on OLD_IMAGE without new data
• Polling instead of using Streams