Stream processing patterns in DynamoDB - Step-by-Step Execution

Concept Flow - Stream processing patterns

Data Change in DynamoDB Table

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DynamoDB Streams Capture Change

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Stream Processing Lambda Triggered

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Process Record: Filter/Transform/Enrich

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Write Results to Target (DB, Analytics, etc)

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End

Data changes in DynamoDB tables create stream records, which trigger processing functions that handle each record and write results to targets.

Execution Sample

DynamoDB

1. Insert item into DynamoDB table
2. Stream captures INSERT event
3. Lambda triggered with stream record
4. Lambda processes record (e.g., filter)
5. Lambda writes processed data to another table

Shows how a data insert triggers a stream event, which a Lambda function processes and writes results elsewhere.

Execution Table

Step	Event	Stream Record Captured	Lambda Triggered	Processing Action	Output Action
1	Insert item in table	Yes (INSERT event)	Triggered	Filter record (passes filter)	Write to target table
2	Update item in table	Yes (MODIFY event)	Triggered	Transform record (change attribute)	Write updated data
3	Delete item in table	Yes (REMOVE event)	Triggered	Log deletion	No write (optional)
4	No change	No event	No trigger	No processing	No output

💡 Execution stops when no new stream records are available or Lambda finishes processing all records.

Variable Tracker

Variable	Start	After Step 1	After Step 2	After Step 3	Final
Stream Record	Empty	INSERT event captured	MODIFY event captured	REMOVE event captured	Empty after processing
Lambda Trigger	Inactive	Active	Active	Active	Inactive
Processed Output	None	Written new item	Written updated item	Logged deletion	None

Key Moments - 3 Insights

Why does the Lambda trigger only when there is a data change?

Because DynamoDB Streams only capture changes (INSERT, MODIFY, REMOVE), so Lambda triggers only when a stream record exists, as shown in execution_table rows 1-3.

What happens if the record does not pass the filter in processing?

The Lambda skips writing output for that record, so no new data is written, which can be seen as no output action in the processing step.

Can the stream capture multiple types of events?

Yes, it captures INSERT, MODIFY, and REMOVE events, each triggering Lambda with different processing actions as shown in the execution_table.

Visual Quiz - 3 Questions

Look at the execution_table, at which step does the Lambda write updated data?

A Step 3

B Step 1

C Step 2

D Step 4

💡 Hint

Check the 'Output Action' column for each step in the execution_table.

According to variable_tracker, what is the state of 'Lambda Trigger' after Step 3?

A Inactive

B Active

C Error

D Unknown

💡 Hint

Look at the 'Lambda Trigger' row and the column 'After Step 3' in variable_tracker.

If no data change occurs, what happens to the stream and Lambda trigger?

A No stream event, Lambda does not trigger

B Stream captures event, Lambda does not trigger

C Stream captures event, Lambda triggers

D No stream event, Lambda triggers

💡 Hint

Refer to execution_table row 4 for no change scenario.

Concept Snapshot

DynamoDB Streams capture table data changes (INSERT, MODIFY, REMOVE).
Each change creates a stream record.
Lambda functions trigger on these records.
Lambda processes records (filter, transform).
Processed data can be written to other targets.
No change means no stream event and no Lambda trigger.

Full Transcript

In DynamoDB, when data changes in a table, these changes are captured as stream records. These records represent events like inserts, updates, or deletes. A Lambda function can be set to trigger automatically when these stream records appear. The Lambda processes each record, for example by filtering or transforming the data, and then writes the results to another database or system. If there is no data change, no stream record is created, so the Lambda does not trigger. This flow ensures that processing happens only when data changes, making it efficient and event-driven.

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