You can use a AWS Lambda function to process records in a Amazon DynamoDB Streams stream. With DynamoDB Streams, you can trigger a Lambda function to perform additional work each time a DynamoDB table is updated.
Lambda reads records from the stream and invokes your function synchronously with an event that contains stream records. Lambda reads records in batches and invokes your function to process records from the batch.
Example DynamoDB Streams Record Event
{
"Records": [
{
"eventID": "1",
"eventVersion": "1.0",
"dynamodb": {
"Keys": {
"Id": {
"N": "101"
}
},
"NewImage": {
"Message": {
"S": "New item!"
},
"Id": {
"N": "101"
}
},
"StreamViewType": "NEW_AND_OLD_IMAGES",
"SequenceNumber": "111",
"SizeBytes": 26
},
"awsRegion": "us-west-2",
"eventName": "INSERT",
"eventSourceARN": eventsourcearn,
"eventSource": "aws:dynamodb"
},
{
"eventID": "2",
"eventVersion": "1.0",
"dynamodb": {
"OldImage": {
"Message": {
"S": "New item!"
},
"Id": {
"N": "101"
}
},
"SequenceNumber": "222",
"Keys": {
"Id": {
"N": "101"
}
},
"SizeBytes": 59,
"NewImage": {
"Message": {
"S": "This item has changed"
},
"Id": {
"N": "101"
}
},
"StreamViewType": "NEW_AND_OLD_IMAGES"
},
"awsRegion": "us-west-2",
"eventName": "MODIFY",
"eventSourceARN": sourcearn,
"eventSource": "aws:dynamodb"
}
Lambda polls shards in your DynamoDB Streams stream for records at a base rate of 4 times per second. When records are available, Lambda invokes your function and waits for the result. If processing succeeds, Lambda resumes polling until it receives more records.
If your function returns an error, Lambda retries the batch until processing succeeds or the data expires. Until the issue is resolved, no data in the shard is processed. Handle and record processing errors in your code to avoid stalled shards and potential data loss.
Topics
- Creating an Event Source Mapping
- Execution Role Permissions
- Tutorial: Using AWS Lambda with Amazon DynamoDB Streams
- Sample Function Code
- AWS SAM Template for a DynamoDB Application
Create an event source mapping to tell Lambda to send records from your stream to a Lambda function. You can create multiple event source mappings to process the same data with multiple Lambda functions, or process items from multiple streams with a single function.
To configure your function to read from DynamoDB Streams in the Lambda console, create a DynamoDB trigger.
To create a trigger
-
Open the Lambda console Functions page.
-
Choose a function.
-
Under Designer, choose a trigger type to add a trigger to your function.
-
Under Configure triggers, configure the required options and then choose Add.
-
Choose Save.
Event Source Options
-
DynamoDB table – The DynamoDB table from which to read records.
-
Batch size – The number of records to read from a shard in each batch, up to 1,000. Lambda passes all of the records in the batch to the function in a single call, as long as the total size of the events doesn't exceed the payload limit of 6 MB.
-
Starting position – Process only new records, or all existing records.
- Latest – Process new records added to the stream.
- Trim horizon – Process all records in the stream.
After processing any existing records, the function is caught up and continues to process new records.
-
Enabled – Disable the event source to stop processing records. Lambda keeps track of the last record processed and resumes processing from that point when re-enabled.
To manage the event source configuration later, choose the trigger in the designer.
Lambda needs the following permissions to manage resources related to your DynamoDB Streams stream. Add them to your function's execution role.
The AWSLambdaDynamoDBExecutionRole managed policy includes these permissions. For more information, see Manage Permissions: Using an IAM Role (Execution Role).