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Batch Processing

The batch processing utility handles partial failures when processing batches from Amazon SQS, Amazon Kinesis Data Streams, and Amazon DynamoDB Streams.

stateDiagram-v2
    direction LR
    BatchSource: Amazon SQS <br/><br/> Amazon Kinesis Data Streams <br/><br/> Amazon DynamoDB Streams <br/><br/>
    LambdaInit: Lambda invocation
    BatchProcessor: Batch Processor
    RecordHandler: Record Handler function
    YourLogic: Your logic to process each batch item
    LambdaResponse: Lambda response

    BatchSource --> LambdaInit

    LambdaInit --> BatchProcessor
    BatchProcessor --> RecordHandler

    state BatchProcessor {
        [*] --> RecordHandler: Your function
        RecordHandler --> YourLogic
    }

    RecordHandler --> BatchProcessor: Collect results
    BatchProcessor --> LambdaResponse: Report items that failed processing

Key features

  • Reports batch item failures to reduce number of retries for a record upon errors
  • Simple interface to process each batch record
  • Bring your own batch processor
  • Parallel processing

Background

When using SQS, Kinesis Data Streams, or DynamoDB Streams as a Lambda event source, your Lambda functions are triggered with a batch of messages.

If your function fails to process any message from the batch, the entire batch returns to your queue or stream. This same batch is then retried until either condition happens first: a) your Lambda function returns a successful response, b) record reaches maximum retry attempts, or c) when records expire.

journey
  section Conditions
    Successful response: 5: Success
    Maximum retries: 3: Failure
    Records expired: 1: Failure

This behavior changes when you enable Report Batch Item Failures feature in your Lambda function event source configuration:

  • SQS queues. Only messages reported as failure will return to the queue for a retry, while successful ones will be deleted.
  • Kinesis data streams and DynamoDB streams. Single reported failure will use its sequence number as the stream checkpoint. Multiple reported failures will use the lowest sequence number as checkpoint.
Warning: This utility lowers the chance of processing records more than once; it does not guarantee it

We recommend implementing processing logic in an idempotent manner wherever possible.

You can find more details on how Lambda works with either SQS, Kinesis, or DynamoDB in the AWS Documentation.

Installation

You should install with NuGet:

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Install-Package AWS.Lambda.Powertools.BatchProcessing

Or via the .NET Core command line interface:

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dotnet add package AWS.Lambda.Powertools.BatchProcessing

Getting started

For this feature to work, you need to (1) configure your Lambda function event source to use ReportBatchItemFailures, and (2) return a specific response to report which records failed to be processed.

You use your preferred deployment framework to set the correct configuration while this utility handles the correct response to be returned.

Batch processing can be configured with the settings bellow:

Setting Description Environment variable Default
Error Handling Policy The error handling policy to apply during batch processing. POWERTOOLS_BATCH_ERROR_HANDLING_POLICY DeriveFromEvent
Parallel Enabled Controls if parallel processing of batch items is enabled. POWERTOOLS_BATCH_PARALLEL_ENABLED false
Max Degree of Parallelism The maximum degree of parallelism to apply if parallel processing is enabled. POWERTOOLS_BATCH_MAX_DEGREE_OF_PARALLELISM 1
Throw on Full Batch Failure Controls if a BatchProcessingException is thrown on full batch failure. POWERTOOLS_BATCH_THROW_ON_FULL_BATCH_FAILURE true

Required resources

The remaining sections of the documentation will rely on these samples. For completeness, this demonstrates IAM permissions and Dead Letter Queue where batch records will be sent after 2 retries were attempted.

You do not need any additional IAM permissions to use this utility, except for what each event source requires.

template.yaml
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AWSTemplateFormatVersion: "2010-09-09"
Transform: AWS::Serverless-2016-10-31
Description: Example project demoing SQS Queue processing using the Batch Processing Utility in Powertools for AWS Lambda (.NET)

Globals:
  Function:
    Timeout: 20
    Runtime: dotnet8
    MemorySize: 1024
    Environment:
      Variables:
        POWERTOOLS_SERVICE_NAME: powertools-dotnet-sample-batch-sqs
        POWERTOOLS_LOG_LEVEL: Debug
        POWERTOOLS_LOGGER_CASE: PascalCase
        POWERTOOLS_BATCH_ERROR_HANDLING_POLICY: DeriveFromEvent
        POWERTOOLS_BATCH_MAX_DEGREE_OF_PARALLELISM: 1
        POWERTOOLS_BATCH_PARALLEL_ENABLED : false
        POWERTOOLS_BATCH_THROW_ON_FULL_BATCH_FAILURE: true

Resources:

  # --------------
  # KMS key for encrypted messages / records
  CustomerKey:
    Type: AWS::KMS::Key
    Properties:
      Description: KMS key for encrypted queues
      Enabled: true
      KeyPolicy:
        Version: "2012-10-17"
        Statement:
          - Sid: Enable IAM User Permissions
            Effect: Allow
            Principal:
              AWS: !Sub "arn:aws:iam::${AWS::AccountId}:root"
            Action: "kms:*"
            Resource: "*"
          - Sid: Allow AWS Lambda to use the key
            Effect: Allow
            Principal:
              Service: lambda.amazonaws.com
            Action:
              - kms:Decrypt
              - kms:GenerateDataKey
            Resource: "*"

  CustomerKeyAlias:
    Type: AWS::KMS::Alias
    Properties:
      AliasName: !Sub alias/${AWS::StackName}-kms-key
      TargetKeyId: !Ref CustomerKey

  # --------------
  # Batch Processing for SQS Queue
  SqsDeadLetterQueue:
    Type: AWS::SQS::Queue
    Properties:
      KmsMasterKeyId: !Ref CustomerKey

  SqsQueue:
    Type: AWS::SQS::Queue
    Properties:
      RedrivePolicy:
        deadLetterTargetArn: !GetAtt SqsDeadLetterQueue.Arn
        maxReceiveCount: 2
      KmsMasterKeyId: !Ref CustomerKey

  SqsBatchProcessorFunction:
    Type: AWS::Serverless::Function
    Properties:
      CodeUri: ./src/HelloWorld/
      Handler: HelloWorld::HelloWorld.Function::SqsHandlerUsingAttribute
      Policies:
        - Statement:
            - Sid: DlqPermissions
              Effect: Allow
              Action:
                - sqs:SendMessage
                - sqs:SendMessageBatch
              Resource: !GetAtt SqsDeadLetterQueue.Arn
            - Sid: KmsKeyPermissions
              Effect: Allow
              Action:
                - kms:Decrypt
                - kms:GenerateDataKey
              Resource: !GetAtt CustomerKey.Arn
      Events:
        SqsBatch:
          Type: SQS
          Properties:
            BatchSize: 5
            Enabled: true
            FunctionResponseTypes:
              - ReportBatchItemFailures
            Queue: !GetAtt SqsQueue.Arn

  SqsBatchProcessorFunctionLogGroup:
    Type: AWS::Logs::LogGroup
    Properties:
      LogGroupName: !Sub "/aws/lambda/${SqsBatchProcessorFunction}"
      RetentionInDays: 7

Outputs:
  SqsQueueUrl:
    Description: "SQS Queue URL"
    Value: !Ref SqsQueue
template.yaml
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AWSTemplateFormatVersion: "2010-09-09"
Transform: AWS::Serverless-2016-10-31
Description: Example project demoing Kinesis Data Streams processing using the Batch Processing Utility in Powertools for AWS Lambda (.NET)

Globals:
  Function:
    Timeout: 20
    Runtime: dotnet8
    MemorySize: 1024
    Environment:
      Variables:
        POWERTOOLS_SERVICE_NAME: powertools-dotnet-sample-batch-kinesis
        POWERTOOLS_LOG_LEVEL: Debug
        POWERTOOLS_LOGGER_CASE: PascalCase
        POWERTOOLS_BATCH_ERROR_HANDLING_POLICY: DeriveFromEvent
        POWERTOOLS_BATCH_MAX_DEGREE_OF_PARALLELISM: 1
        POWERTOOLS_BATCH_PARALLEL_ENABLED : false
        POWERTOOLS_BATCH_THROW_ON_FULL_BATCH_FAILURE: true

Resources:

  # --------------
  # KMS key for encrypted messages / records
  CustomerKey:
    Type: AWS::KMS::Key
    Properties:
      Description: KMS key for encrypted queues
      Enabled: true
      KeyPolicy:
        Version: "2012-10-17"
        Statement:
          - Sid: Enable IAM User Permissions
            Effect: Allow
            Principal:
              AWS: !Sub "arn:aws:iam::${AWS::AccountId}:root"
            Action: "kms:*"
            Resource: "*"
          - Sid: Allow AWS Lambda to use the key
            Effect: Allow
            Principal:
              Service: lambda.amazonaws.com
            Action:
              - kms:Decrypt
              - kms:GenerateDataKey
            Resource: "*"

  CustomerKeyAlias:
    Type: AWS::KMS::Alias
    Properties:
      AliasName: !Sub alias/${AWS::StackName}-kms-key
      TargetKeyId: !Ref CustomerKey

  # --------------
  # Batch Processing for Kinesis Data Stream
  KinesisStreamDeadLetterQueue:
    Type: AWS::SQS::Queue
    Properties:
      KmsMasterKeyId: !Ref CustomerKey

  KinesisStream:
    Type: AWS::Kinesis::Stream
    Properties:
      ShardCount: 1
      StreamEncryption:
        EncryptionType: KMS
        KeyId: !Ref CustomerKey

  KinesisStreamConsumer:
    Type: AWS::Kinesis::StreamConsumer
    Properties:
      ConsumerName: powertools-dotnet-sample-batch-kds-consumer
      StreamARN: !GetAtt KinesisStream.Arn

  KinesisBatchProcessorFunction:
    Type: AWS::Serverless::Function
    Properties:
      Policies:
        - Statement:
            - Sid: KinesisStreamConsumerPermissions
              Effect: Allow
              Action:
                - kinesis:DescribeStreamConsumer
              Resource:
                - !GetAtt KinesisStreamConsumer.ConsumerARN
            - Sid: DlqPermissions
              Effect: Allow
              Action:
                - sqs:SendMessage
                - sqs:SendMessageBatch
              Resource: !GetAtt KinesisStreamDeadLetterQueue.Arn
            - Sid: KmsKeyPermissions
              Effect: Allow
              Action:
                - kms:Decrypt
                - kms:GenerateDataKey
              Resource: !GetAtt CustomerKey.Arn
      CodeUri: ./src/HelloWorld/
      Handler: HelloWorld::HelloWorld.Function::KinesisEventHandlerUsingAttribute
      Events:
        Kinesis:
          Type: Kinesis
          Properties:
            BatchSize: 5
            BisectBatchOnFunctionError: true
            DestinationConfig:
              OnFailure:
                Destination: !GetAtt KinesisStreamDeadLetterQueue.Arn
            Enabled: true
            FunctionResponseTypes:
              - ReportBatchItemFailures
            MaximumRetryAttempts: 2
            ParallelizationFactor: 1
            StartingPosition: LATEST
            Stream: !GetAtt KinesisStreamConsumer.ConsumerARN

  KinesisBatchProcessorFunctionLogGroup:
    Type: AWS::Logs::LogGroup
    Properties:
      LogGroupName: !Sub "/aws/lambda/${KinesisBatchProcessorFunction}"
      RetentionInDays: 7

Outputs:
  KinesisStreamArn:
    Description: "Kinesis Stream ARN"
    Value: !GetAtt KinesisStream.Arn
template.yaml
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AWSTemplateFormatVersion: "2010-09-09"
Transform: AWS::Serverless-2016-10-31
Description: Example project demoing DynamoDB Streams processing using the Batch Processing Utility in Powertools for AWS Lambda (.NET)

Globals:
  Function:
    Timeout: 20
    Runtime: dotnet8
    MemorySize: 1024
    Environment:
      Variables:
        POWERTOOLS_SERVICE_NAME: powertools-dotnet-sample-batch-ddb
        POWERTOOLS_LOG_LEVEL: Debug
        POWERTOOLS_LOGGER_CASE: PascalCase
        POWERTOOLS_BATCH_ERROR_HANDLING_POLICY: DeriveFromEvent
        POWERTOOLS_BATCH_MAX_DEGREE_OF_PARALLELISM: 1
        POWERTOOLS_BATCH_PARALLEL_ENABLED : false
        POWERTOOLS_BATCH_THROW_ON_FULL_BATCH_FAILURE: true

Resources:

  # --------------
  # KMS key for encrypted messages / records
  CustomerKey:
    Type: AWS::KMS::Key
    Properties:
      Description: KMS key for encrypted queues
      Enabled: true
      KeyPolicy:
        Version: "2012-10-17"
        Statement:
          - Sid: Enable IAM User Permissions
            Effect: Allow
            Principal:
              AWS: !Sub "arn:aws:iam::${AWS::AccountId}:root"
            Action: "kms:*"
            Resource: "*"
          - Sid: Allow AWS Lambda to use the key
            Effect: Allow
            Principal:
              Service: lambda.amazonaws.com
            Action:
              - kms:Decrypt
              - kms:GenerateDataKey
            Resource: "*"

  CustomerKeyAlias:
    Type: AWS::KMS::Alias
    Properties:
      AliasName: !Sub alias/${AWS::StackName}-kms-key
      TargetKeyId: !Ref CustomerKey

  # --------------
  # Batch Processing for DynamoDb (DDB) Stream
  DdbStreamDeadLetterQueue:
    Type: AWS::SQS::Queue
    Properties:
      KmsMasterKeyId: !Ref CustomerKey

  DdbTable:
    Type: AWS::DynamoDB::Table
    Properties:
      BillingMode: PAY_PER_REQUEST
      AttributeDefinitions:
        - AttributeName: id
          AttributeType: S
      KeySchema:
        - AttributeName: id
          KeyType: HASH
      StreamSpecification:
        StreamViewType: NEW_AND_OLD_IMAGES

  DdbStreamBatchProcessorFunction:
    Type: AWS::Serverless::Function
    Properties:
      CodeUri: ./src/HelloWorld/
      Handler: HelloWorld::HelloWorld.Function::DynamoDbStreamHandlerUsingAttribute
      Policies:
        - AWSLambdaDynamoDBExecutionRole
        - Statement:
            - Sid: DlqPermissions
              Effect: Allow
              Action:
                - sqs:SendMessage
                - sqs:SendMessageBatch
              Resource: !GetAtt DdbStreamDeadLetterQueue.Arn
            - Sid: KmsKeyPermissions
              Effect: Allow
              Action:
                - kms:GenerateDataKey
              Resource: !GetAtt CustomerKey.Arn
      Events:
        Stream:
          Type: DynamoDB
          Properties:
            BatchSize: 5
            BisectBatchOnFunctionError: true
            DestinationConfig:
              OnFailure:
                Destination: !GetAtt DdbStreamDeadLetterQueue.Arn
            Enabled: true
            FunctionResponseTypes:
              - ReportBatchItemFailures
            MaximumRetryAttempts: 2
            ParallelizationFactor: 1
            StartingPosition: LATEST
            Stream: !GetAtt DdbTable.StreamArn

  DdbStreamBatchProcessorFunctionLogGroup:
    Type: AWS::Logs::LogGroup
    Properties:
      LogGroupName: !Sub "/aws/lambda/${DdbStreamBatchProcessorFunction}"
      RetentionInDays: 7

Outputs:
  DdbTableName:
    Description: "DynamoDB Table Name"
    Value: !Ref DdbTable

Processing messages from SQS

Using Handler decorator

Processing batches from SQS using Lambda handler decorator works in three stages:

  1. Decorate your handler with BatchProcessor attribute
  2. Create a class that implements ISqsRecordHandler interface and the HandleAsync method.
  3. Pass the type of that class to RecordHandler property of the BatchProcessor attribute
  4. Return BatchItemFailuresResponse from Lambda handler using SqsBatchProcessor.Result.BatchItemFailuresResponse
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public class CustomSqsRecordHandler : ISqsRecordHandler // (1)!
{
    public async Task<RecordHandlerResult> HandleAsync(SQSEvent.SQSMessage record, CancellationToken cancellationToken)
    {
         /*
         * Your business logic.
         * If an exception is thrown, the item will be marked as a partial batch item failure.
         */

         var product = JsonSerializer.Deserialize<Product>(record.Body);

         if (product.Id == 4) // (2)!
         {
             throw new ArgumentException("Error on id 4");
         }

         return await Task.FromResult(RecordHandlerResult.None); // (3)!
     }
}


[BatchProcessor(RecordHandler = typeof(CustomSqsRecordHandler))]
public BatchItemFailuresResponse HandlerUsingAttribute(SQSEvent _)
{
    return SqsBatchProcessor.Result.BatchItemFailuresResponse; // (4)!
}
  1. Step 1. Creates a class that implements ISqsRecordHandler interface and the HandleAsync method.
  2. Step 2. You can have custom logic inside the record handler and throw exceptions that will cause this message to fail
  3. Step 3. RecordHandlerResult can return empty (None) or some data.
  4. Step 4. Lambda function returns the Partial batch response
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{
    "Records": [
        {
            "messageId": "059f36b4-87a3-44ab-83d2-661975830a7d",
            "receiptHandle": "AQEBwJnKyrHigUMZj6rYigCgxlaS3SLy0a",
            "body": "{\"Id\":1,\"Name\":\"product-4\",\"Price\":14}",
            "attributes": {
                "ApproximateReceiveCount": "1",
                "SentTimestamp": "1545082649183",
                "SenderId": "AIDAIENQZJOLO23YVJ4VO",
                "ApproximateFirstReceiveTimestamp": "1545082649185"
            },
            "messageAttributes": {},
            "md5OfBody": "e4e68fb7bd0e697a0ae8f1bb342846b3",
            "eventSource": "aws:sqs",
            "eventSourceARN": "arn:aws:sqs:us-east-2: 123456789012:my-queue",
            "awsRegion": "us-east-1"
        },
        {
            "messageId": "244fc6b4-87a3-44ab-83d2-361172410c3a",
            "receiptHandle": "AQEBwJnKyrHigUMZj6rYigCgxlaS3SLy0a",
            "body": "fail",
            "attributes": {
                "ApproximateReceiveCount": "1",
                "SentTimestamp": "1545082649183",
                "SenderId": "AIDAIENQZJOLO23YVJ4VO",
                "ApproximateFirstReceiveTimestamp": "1545082649185"
            },
            "messageAttributes": {},
            "md5OfBody": "e4e68fb7bd0e697a0ae8f1bb342846b3",
            "eventSource": "aws:sqs",
            "eventSourceARN": "arn:aws:sqs:us-east-2: 123456789012:my-queue",
            "awsRegion": "us-east-1"
        },
        {
            "messageId": "213f4fd3-84a4-4667-a1b9-c277964197d9",
            "receiptHandle": "AQEBwJnKyrHigUMZj6rYigCgxlaS3SLy0a",
            "body": "{\"Id\":4,\"Name\":\"product-4\",\"Price\":14}",
            "attributes": {
                "ApproximateReceiveCount": "1",
                "SentTimestamp": "1545082649183",
                "SenderId": "AIDAIENQZJOLO23YVJ4VO",
                "ApproximateFirstReceiveTimestamp": "1545082649185"
            },
            "messageAttributes": {},
            "md5OfBody": "e4e68fb7bd0e697a0ae8f1bb342846b3",
            "eventSource": "aws:sqs",
            "eventSourceARN": "arn:aws:sqs:us-east-2: 123456789012:my-queue",
            "awsRegion": "us-east-1"
        },
    ]
}

The second record failed to be processed, therefore the processor added its message ID in the response.

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{
    "batchItemFailures": [
        {
            "itemIdentifier": "244fc6b4-87a3-44ab-83d2-361172410c3a"
        },
        {
            "itemIdentifier": "213f4fd3-84a4-4667-a1b9-c277964197d9"
        }
    ]
}

FIFO queues

When using SQS FIFO queues, we will stop processing messages after the first failure, and return all failed and unprocessed messages in batchItemFailures. This helps preserve the ordering of messages in your queue. Powertools automatically detects a FIFO queue.

Processing messages from Kinesis

Processing batches from Kinesis using Lambda handler decorator works in three stages:

  1. Decorate your handler with BatchProcessor attribute
  2. Create a class that implements IKinesisEventRecordHandler interface and the HandleAsync method.
  3. Pass the type of that class to RecordHandler property of the BatchProcessor attribute
  4. Return BatchItemFailuresResponse from Lambda handler using KinesisEventBatchProcessor.Result.BatchItemFailuresResponse
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internal class CustomKinesisEventRecordHandler : IKinesisEventRecordHandler // (1)!
{
    public async Task<RecordHandlerResult> HandleAsync(KinesisEvent.KinesisEventRecord record, CancellationToken cancellationToken)
    {
        var product = JsonSerializer.Deserialize<Product>(record.Kinesis.Data);

        if (product.Id == 4) // (2)!
        {
            throw new ArgumentException("Error on id 4");
        }

        return await Task.FromResult(RecordHandlerResult.None); // (3)!
    }
}


[BatchProcessor(RecordHandler = typeof(CustomKinesisEventRecordHandler))]
public BatchItemFailuresResponse HandlerUsingAttribute(KinesisEvent _)
{
    return KinesisEventBatchProcessor.Result.BatchItemFailuresResponse; // (4)!
}
  1. Step 1. Creates a class that implements the IKinesisEventRecordHandler interface and the HandleAsync method.
  2. Step 2. You can have custom logic inside the record handler and throw exceptions that will cause this message to fail
  3. Step 3. RecordHandlerResult can return empty (None) or some data.
  4. Step 4. Lambda function returns the Partial batch response
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{
    "Records": [
        {
            "messageId": "059f36b4-87a3-44ab-83d2-661975830a7d",
            "receiptHandle": "AQEBwJnKyrHigUMZj6rYigCgxlaS3SLy0a",
            "body": "{\"Id\":1,\"Name\":\"product-4\",\"Price\":14}",
            "attributes": {
                "ApproximateReceiveCount": "1",
                "SentTimestamp": "1545082649183",
                "SenderId": "AIDAIENQZJOLO23YVJ4VO",
                "ApproximateFirstReceiveTimestamp": "1545082649185"
            },
            "messageAttributes": {},
            "md5OfBody": "e4e68fb7bd0e697a0ae8f1bb342846b3",
            "eventSource": "aws:sqs",
            "eventSourceARN": "arn:aws:sqs:us-east-2: 123456789012:my-queue",
            "awsRegion": "us-east-1"
        },
        {
            "messageId": "244fc6b4-87a3-44ab-83d2-361172410c3a",
            "receiptHandle": "AQEBwJnKyrHigUMZj6rYigCgxlaS3SLy0a",
            "body": "fail",
            "attributes": {
                "ApproximateReceiveCount": "1",
                "SentTimestamp": "1545082649183",
                "SenderId": "AIDAIENQZJOLO23YVJ4VO",
                "ApproximateFirstReceiveTimestamp": "1545082649185"
            },
            "messageAttributes": {},
            "md5OfBody": "e4e68fb7bd0e697a0ae8f1bb342846b3",
            "eventSource": "aws:sqs",
            "eventSourceARN": "arn:aws:sqs:us-east-2: 123456789012:my-queue",
            "awsRegion": "us-east-1"
        },
        {
            "messageId": "213f4fd3-84a4-4667-a1b9-c277964197d9",
            "receiptHandle": "AQEBwJnKyrHigUMZj6rYigCgxlaS3SLy0a",
            "body": "{\"Id\":4,\"Name\":\"product-4\",\"Price\":14}",
            "attributes": {
                "ApproximateReceiveCount": "1",
                "SentTimestamp": "1545082649183",
                "SenderId": "AIDAIENQZJOLO23YVJ4VO",
                "ApproximateFirstReceiveTimestamp": "1545082649185"
            },
            "messageAttributes": {},
            "md5OfBody": "e4e68fb7bd0e697a0ae8f1bb342846b3",
            "eventSource": "aws:sqs",
            "eventSourceARN": "arn:aws:sqs:us-east-2: 123456789012:my-queue",
            "awsRegion": "us-east-1"
        },
    ]
}

The second record failed to be processed, therefore the processor added its message ID in the response.

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{
    "batchItemFailures": [
        {
            "itemIdentifier": "244fc6b4-87a3-44ab-83d2-361172410c3a"
        },
        {
            "itemIdentifier": "213f4fd3-84a4-4667-a1b9-c277964197d9"
        }
    ]
}

Processing messages from DynamoDB

Processing batches from DynamoDB Streams using Lambda handler decorator works in three stages:

  1. Decorate your handler with BatchProcessor attribute
  2. Create a class that implements IDynamoDbStreamRecordHandler and the HandleAsync method.
  3. Pass the type of that class to RecordHandler property of the BatchProcessor attribute
  4. Return BatchItemFailuresResponse from Lambda handler using DynamoDbStreamBatchProcessor.Result.BatchItemFailuresResponse
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internal class CustomDynamoDbStreamRecordHandler : IDynamoDbStreamRecordHandler // (1)!
{
    public async Task<RecordHandlerResult> HandleAsync(DynamoDBEvent.DynamodbStreamRecord record, CancellationToken cancellationToken)
    {
        var product = JsonSerializer.Deserialize<Product>(record.Dynamodb.NewImage["Product"].S);

        if (product.Id == 4) // (2)!
        {
            throw new ArgumentException("Error on id 4");
        }

        return await Task.FromResult(RecordHandlerResult.None); // (3)!
    }
}


[BatchProcessor(RecordHandler = typeof(CustomDynamoDbStreamRecordHandler))]
public BatchItemFailuresResponse HandlerUsingAttribute(DynamoDBEvent _)
{
    return DynamoDbStreamBatchProcessor.Result.BatchItemFailuresResponse; // (4)!
}
  1. Step 1. Creates a class that implements the IDynamoDbStreamRecordHandler and the HandleAsync method.
  2. Step 2. You can have custom logic inside the record handler and throw exceptions that will cause this message to fail
  3. Step 3. RecordHandlerResult can return empty (None) or some data.
  4. Step 4. Lambda function returns the Partial batch response
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{
    "Records": [
        {
            "eventID": "1",
            "eventVersion": "1.0",
            "dynamodb": {
                "Keys": {
                    "Id": {
                        "N": "101"
                }
            },
            "NewImage": {
                "Product": {
                    "S": "{\"Id\":1,\"Name\":\"product-name\",\"Price\":14}"
                }
            },
            "StreamViewType": "NEW_AND_OLD_IMAGES",
            "SequenceNumber": "3275880929",
            "SizeBytes": 26
            },
            "awsRegion": "us-west-2",
            "eventName": "INSERT",
            "eventSourceARN": "eventsource_arn",
            "eventSource": "aws:dynamodb"
        },
        {
            "eventID": "1",
            "eventVersion": "1.0",
            "dynamodb": {
                "Keys": {
                    "Id": {
                        "N": "101"
                }
            },
            "NewImage": {
                "Product": {
                    "S": "fail"
                }
            },
            "StreamViewType": "NEW_AND_OLD_IMAGES",
            "SequenceNumber": "8640712661",
            "SizeBytes": 26
            },
            "awsRegion": "us-west-2",
            "eventName": "INSERT",
            "eventSourceARN": "eventsource_arn",
            "eventSource": "aws:dynamodb"
        }
    ]
}

The second record failed to be processed, therefore the processor added its message ID in the response.

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{
    "batchItemFailures": [
        {
            "itemIdentifier": "8640712661"
        }
    ]
}

Error handling

By default, we catch any exception raised by your custom record handler HandleAsync method (ISqsRecordHandler, IKinesisEventRecordHandler, IDynamoDbStreamRecordHandler). This allows us to (1) continue processing the batch, (2) collect each batch item that failed processing, and (3) return the appropriate response correctly without failing your Lambda function execution.

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public class CustomSqsRecordHandler : ISqsRecordHandler // (1)!
{
    public async Task<RecordHandlerResult> HandleAsync(SQSEvent.SQSMessage record, CancellationToken cancellationToken)
    {
         /*
         * Your business logic.
         * If an exception is thrown, the item will be marked as a partial batch item failure.
         */

         var product = JsonSerializer.Deserialize<Product>(record.Body);

         if (product.Id == 4) // (2)!
         {
             throw new ArgumentException("Error on id 4");
         }

         return await Task.FromResult(RecordHandlerResult.None); // (3)!
     }
}

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{
    "Records": [
        {
            "messageId": "059f36b4-87a3-44ab-83d2-661975830a7d",
            "receiptHandle": "AQEBwJnKyrHigUMZj6rYigCgxlaS3SLy0a",
            "body": "{\"Id\":1,\"Name\":\"product-4\",\"Price\":14}",
            "attributes": {
                "ApproximateReceiveCount": "1",
                "SentTimestamp": "1545082649183",
                "SenderId": "AIDAIENQZJOLO23YVJ4VO",
                "ApproximateFirstReceiveTimestamp": "1545082649185"
            },
            "messageAttributes": {},
            "md5OfBody": "e4e68fb7bd0e697a0ae8f1bb342846b3",
            "eventSource": "aws:sqs",
            "eventSourceARN": "arn:aws:sqs:us-east-2: 123456789012:my-queue",
            "awsRegion": "us-east-1"
        },
        {
            "messageId": "244fc6b4-87a3-44ab-83d2-361172410c3a",
            "receiptHandle": "AQEBwJnKyrHigUMZj6rYigCgxlaS3SLy0a",
            "body": "fail",
            "attributes": {
                "ApproximateReceiveCount": "1",
                "SentTimestamp": "1545082649183",
                "SenderId": "AIDAIENQZJOLO23YVJ4VO",
                "ApproximateFirstReceiveTimestamp": "1545082649185"
            },
            "messageAttributes": {},
            "md5OfBody": "e4e68fb7bd0e697a0ae8f1bb342846b3",
            "eventSource": "aws:sqs",
            "eventSourceARN": "arn:aws:sqs:us-east-2: 123456789012:my-queue",
            "awsRegion": "us-east-1"
        },
        {
            "messageId": "213f4fd3-84a4-4667-a1b9-c277964197d9",
            "receiptHandle": "AQEBwJnKyrHigUMZj6rYigCgxlaS3SLy0a",
            "body": "{\"Id\":4,\"Name\":\"product-4\",\"Price\":14}",
            "attributes": {
                "ApproximateReceiveCount": "1",
                "SentTimestamp": "1545082649183",
                "SenderId": "AIDAIENQZJOLO23YVJ4VO",
                "ApproximateFirstReceiveTimestamp": "1545082649185"
            },
            "messageAttributes": {},
            "md5OfBody": "e4e68fb7bd0e697a0ae8f1bb342846b3",
            "eventSource": "aws:sqs",
            "eventSourceARN": "arn:aws:sqs:us-east-2: 123456789012:my-queue",
            "awsRegion": "us-east-1"
        },
    ]
}

The second record failed to be processed, therefore the processor added its message ID in the response.

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{
    "batchItemFailures": [
        {
            "itemIdentifier": "244fc6b4-87a3-44ab-83d2-361172410c3a"
        },
        {
            "itemIdentifier": "213f4fd3-84a4-4667-a1b9-c277964197d9"
        }
    ]
}

Error Handling Policy

You can specify the error handling policy applied during batch processing.

ErrorHandlingPolicy is used to control the error handling policy of the batch item processing. With a value of DeriveFromEvent (default), the specific BatchProcessor, determines the policy based on the incoming event.

For example, the SqsBatchProcessor looks at the EventSourceArn to determine if the ErrorHandlingPolicy should be StopOnFirstBatchItemFailure (for FIFO queues) or ContinueOnBatchItemFailure (for standard queues). For StopOnFirstBatchItemFailure the batch processor stops processing and marks any remaining records as batch item failures. For ContinueOnBatchItemFailure the batch processor continues processing batch items regardless of item failures.

Policy Description
DeriveFromEvent Auto-derive the policy based on the event.
ContinueOnBatchItemFailure Continue processing regardless of whether other batch items fails during processing.
StopOnFirstBatchItemFailure Stop processing other batch items after the first batch item has failed processing. This is useful to preserve ordered processing of events.

Note

When using StopOnFirstBatchItemFailure and parallel processing is enabled, all batch items already scheduled to be processed, will be allowed to complete before the batch processing stops.

Therefore, if order is important, it is recommended to use sequential (non-parallel) processing together with this value."

To change the default error handling policy, you can set the POWERTOOLS_BATCH_ERROR_HANDLING_POLICY Environment Variable.

Another approach is to decorate the handler and use one of the policies in the ErrorHandlingPolicy Enum property of the BatchProcessor attribute

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[BatchProcessor(RecordHandler = typeof(CustomDynamoDbStreamRecordHandler), 
    ErrorHandlingPolicy = BatchProcessorErrorHandlingPolicy.StopOnFirstBatchItemFailure)]
public BatchItemFailuresResponse HandlerUsingAttribute(DynamoDBEvent _)
{
    return DynamoDbStreamBatchProcessor.Result.BatchItemFailuresResponse;
}

Partial failure mechanics

All records in the batch will be passed to this handler for processing, even if exceptions are thrown - Here's the behaviour after completing the batch:

  • All records successfully processed. We will return an empty list of item failures {'batchItemFailures': []}.
  • Partial success with some exceptions. We will return a list of all item IDs/sequence numbers that failed processing.
  • All records failed to be processed. By defaullt, we will throw a BatchProcessingException with a list of all exceptions raised during processing to reflect the failure in your operational metrics. However, in some scenarios, this might not be desired. See Working with full batch failures for more information.

The following sequence diagrams explain how each Batch processor behaves under different scenarios.

SQS Standard

Read more about Batch Failure Reporting feature in AWS Lambda.

Sequence diagram to explain how BatchProcessor works with SQS Standard queues.

sequenceDiagram
    autonumber
    participant SQS queue
    participant Lambda service
    participant Lambda function
    Lambda service->>SQS queue: Poll
    Lambda service->>Lambda function: Invoke (batch event)
    Lambda function->>Lambda service: Report some failed messages
    activate SQS queue
    Lambda service->>SQS queue: Delete successful messages
    SQS queue-->>SQS queue: Failed messages return
    Note over SQS queue,Lambda service: Process repeat
    deactivate SQS queue
SQS mechanism with Batch Item Failures

SQS FIFO

Read more about Batch Failure Reporting feature in AWS Lambda.

Sequence diagram to explain how SqsFifoPartialProcessor works with SQS FIFO queues.

sequenceDiagram
    autonumber
    participant SQS queue
    participant Lambda service
    participant Lambda function
    Lambda service->>SQS queue: Poll
    Lambda service->>Lambda function: Invoke (batch event)
    activate Lambda function
    Lambda function-->Lambda function: Process 2 out of 10 batch items
    Lambda function--xLambda function: Fail on 3rd batch item
    Lambda function->>Lambda service: Report 3rd batch item and unprocessed messages as failure
    deactivate Lambda function
    activate SQS queue
    Lambda service->>SQS queue: Delete successful messages (1-2)
    SQS queue-->>SQS queue: Failed messages return (3-10)
    deactivate SQS queue
SQS FIFO mechanism with Batch Item Failures

Kinesis and DynamoDB Streams

Read more about Batch Failure Reporting feature.

Sequence diagram to explain how BatchProcessor works with both Kinesis Data Streams and DynamoDB Streams.

For brevity, we will use Streams to refer to either services. For theory on stream checkpoints, see this blog post

sequenceDiagram
    autonumber
    participant Streams
    participant Lambda service
    participant Lambda function
    Lambda service->>Streams: Poll latest records
    Lambda service->>Lambda function: Invoke (batch event)
    activate Lambda function
    Lambda function-->Lambda function: Process 2 out of 10 batch items
    Lambda function--xLambda function: Fail on 3rd batch item
    Lambda function-->Lambda function: Continue processing batch items (4-10)
    Lambda function->>Lambda service: Report batch item as failure (3)
    deactivate Lambda function
    activate Streams
    Lambda service->>Streams: Checkpoints to sequence number from 3rd batch item
    Lambda service->>Streams: Poll records starting from updated checkpoint
    deactivate Streams
Kinesis and DynamoDB streams mechanism with single batch item failure

The behavior changes slightly when there are multiple item failures. Stream checkpoint is updated to the lowest sequence number reported.

Note that the batch item sequence number could be different from batch item number in the illustration.

sequenceDiagram
    autonumber
    participant Streams
    participant Lambda service
    participant Lambda function
    Lambda service->>Streams: Poll latest records
    Lambda service->>Lambda function: Invoke (batch event)
    activate Lambda function
    Lambda function-->Lambda function: Process 2 out of 10 batch items
    Lambda function--xLambda function: Fail on 3-5 batch items
    Lambda function-->Lambda function: Continue processing batch items (6-10)
    Lambda function->>Lambda service: Report batch items as failure (3-5)
    deactivate Lambda function
    activate Streams
    Lambda service->>Streams: Checkpoints to lowest sequence number
    Lambda service->>Streams: Poll records starting from updated checkpoint
    deactivate Streams
Kinesis and DynamoDB streams mechanism with multiple batch item failures

Advanced

Using utility outside handler and IoC

You can use Batch processing without using the decorator.

Calling the ProcessAsync method on the Instance of the static BatchProcessor (SqsBatchProcessor, DynamoDbStreamBatchProcessor, KinesisEventBatchProcessor)

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public async Task<BatchItemFailuresResponse> HandlerUsingUtility(DynamoDBEvent dynamoDbEvent)
{
    var result = await DynamoDbStreamBatchProcessor.Instance.ProcessAsync(dynamoDbEvent, RecordHandler<DynamoDBEvent.DynamodbStreamRecord>.From(record =>
    {
        var product = JsonSerializer.Deserialize<JsonElement>(record.Dynamodb.NewImage["Product"].S);

        if (product.GetProperty("Id").GetInt16() == 4)
        {
            throw new ArgumentException("Error on 4");
        }
    }));
    return result.BatchItemFailuresResponse;
}

To make the handler testable you can use Dependency Injection to resolve the BatchProcessor (SqsBatchProcessor, DynamoDbStreamBatchProcessor, KinesisEventBatchProcessor) instance and then call the ProcessAsync method.

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public async Task<BatchItemFailuresResponse> HandlerUsingUtilityFromIoc(DynamoDBEvent dynamoDbEvent)
{
    var batchProcessor = Services.Provider.GetRequiredService<IDynamoDbStreamBatchProcessor>();
    var recordHandler = Services.Provider.GetRequiredService<IDynamoDbStreamRecordHandler>();
    var result = await batchProcessor.ProcessAsync(dynamoDbEvent, recordHandler);
    return result.BatchItemFailuresResponse;
}

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public async Task<BatchItemFailuresResponse> HandlerUsingUtilityFromIoc(DynamoDBEvent dynamoDbEvent, 
    IDynamoDbStreamBatchProcessor batchProcessor, IDynamoDbStreamRecordHandler recordHandler)
{
    var result = await batchProcessor.ProcessAsync(dynamoDbEvent, recordHandler);
    return result.BatchItemFailuresResponse;
}

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internal class Services
{
    private static readonly Lazy<IServiceProvider> LazyInstance = new(Build);

    private static ServiceCollection _services;
    public static IServiceProvider Provider => LazyInstance.Value;

    public static IServiceProvider Init()
    {
        return LazyInstance.Value;
    }

    private static IServiceProvider Build()
    {
        _services = new ServiceCollection();
        _services.AddScoped<IDynamoDbStreamBatchProcessor, CustomDynamoDbStreamBatchProcessor>();
        _services.AddScoped<IDynamoDbStreamRecordHandler, CustomDynamoDbStreamRecordHandler>();
        return _services.BuildServiceProvider();
    }
}

Processing messages in parallel

You can set the POWERTOOLS_BATCH_PARALLEL_ENABLED Environment Variable to true or set the property BatchParallelProcessingEnabled on the Lambda decorator to process messages concurrently.

You can also set POWERTOOLS_BATCH_MAX_DEGREE_OF_PARALLELISM Environment Variable to the number of parallelism you which.

Note

MaxDegreeOfParallelism is used to control the parallelism of the batch item processing.

With a value of 1, the processing is done sequentially (default). Sequential processing is recommended when preserving order is important - i.e. with SQS FIFIO queues.

With a value > 1, the processing is done in parallel. Doing parallel processing can enable processing to complete faster, i.e., when processing does downstream service calls.

With a value of -1, the parallelism is automatically configured to be the vCPU count of the Lambda function. Internally, the Batch Processing Utility utilizes Parallel.ForEachAsync Method and the ParallelOptions.MaxDegreeOfParallelism Property to enable this functionality.

When is this useful?

Your use case might be able to process multiple records at the same time without conflicting with one another.

For example, imagine you need to process multiple loyalty points and incrementally save in a database. While you await the database to confirm your records are saved, you could start processing another request concurrently.

The reason this is not the default behaviour is that not all use cases can handle concurrency safely (e.g., loyalty points must be updated in order).

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[BatchProcessor(RecordHandler = typeof(CustomDynamoDbStreamRecordHandler), BatchParallelProcessingEnabled = true )]
public BatchItemFailuresResponse HandlerUsingAttribute(DynamoDBEvent _)
{
    return DynamoDbStreamBatchProcessor.Result.BatchItemFailuresResponse;
}

Working with full batch failures

By default, the BatchProcessor will throw a BatchProcessingException if all records in the batch fail to process. We do this to reflect the failure in your operational metrics.

When working with functions that handle batches with a small number of records, or when you use errors as a flow control mechanism, this behavior might not be desirable as your function might generate an unnaturally high number of errors. When this happens, the Lambda service will scale down the concurrency of your function, potentially impacting performance.

For these scenarios, you can set POWERTOOLS_BATCH_THROW_ON_FULL_BATCH_FAILURE = false, or the equivalent on either the BatchProcessor decorator or on the ProcessingOptions object. See examples below.

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[BatchProcessor(
    RecordHandler = typeof(CustomSqsRecordHandler),
    ThrowOnFullBatchFailure = false)]
public BatchItemFailuresResponse HandlerUsingAttribute(SQSEvent _)
{
    return SqsBatchProcessor.Result.BatchItemFailuresResponse;
}

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public async Task<BatchItemFailuresResponse> HandlerUsingUtility(SQSEvent sqsEvent)
{
    var result = await SqsBatchProcessor.Instance.ProcessAsync(sqsEvent, RecordHandler<SQSEvent.SQSMessage>.From(x =>
    {
        // Inline handling of SQS message...
    }), new ProcessingOptions
    {
        ThrowOnFullBatchFailure = false
    });
    return result.BatchItemFailuresResponse;
}

Extending BatchProcessor

You might want to bring custom logic to the existing BatchProcessor to slightly override how we handle successes and failures.

For these scenarios, you can create a class that inherits from BatchProcessor (SqsBatchProcessor, DynamoDbStreamBatchProcessor, KinesisEventBatchProcessor) and quickly override ProcessAsync and HandleRecordFailureAsync methods:

  • ProcessAsync() – Keeps track of successful batch records
  • HandleRecordFailureAsync() – Keeps track of failed batch records
Example

Let's suppose you'd like to add a metric named BatchRecordFailures for each batch record that failed processing. And also override the default error handling policy to stop on first item failure.

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public class CustomDynamoDbStreamBatchProcessor : DynamoDbStreamBatchProcessor
{
    public override async Task<ProcessingResult<DynamoDBEvent.DynamodbStreamRecord>> ProcessAsync(DynamoDBEvent @event,
    IRecordHandler<DynamoDBEvent.DynamodbStreamRecord> recordHandler, ProcessingOptions processingOptions)
    {
        ProcessingResult = new ProcessingResult<DynamoDBEvent.DynamodbStreamRecord>();

        // Prepare batch records (order is preserved)
        var batchRecords = GetRecordsFromEvent(@event).Select(x => new KeyValuePair<string, DynamoDBEvent.DynamodbStreamRecord>(GetRecordId(x), x))
            .ToArray();

        // We assume all records fail by default to avoid loss of data
        var failureBatchRecords = batchRecords.Select(x => new KeyValuePair<string, RecordFailure<DynamoDBEvent.DynamodbStreamRecord>>(x.Key,
            new RecordFailure<DynamoDBEvent.DynamodbStreamRecord>
            {
                Exception = new UnprocessedRecordException($"Record: '{x.Key}' has not been processed."),
                Record = x.Value
            }));

        // Override to fail on first failure
        var errorHandlingPolicy = BatchProcessorErrorHandlingPolicy.StopOnFirstBatchItemFailure;

        var successRecords = new Dictionary<string, RecordSuccess<DynamoDBEvent.DynamodbStreamRecord>>();
        var failureRecords = new Dictionary<string, RecordFailure<DynamoDBEvent.DynamodbStreamRecord>>(failureBatchRecords);

        try
        {
            foreach (var pair in batchRecords)
            {
                var (recordId, record) = pair;

                try
                {
                    var result = await HandleRecordAsync(record, recordHandler, CancellationToken.None);
                    failureRecords.Remove(recordId, out _);
                    successRecords.TryAdd(recordId, new RecordSuccess<DynamoDBEvent.DynamodbStreamRecord>
                    {
                        Record = record,
                        RecordId = recordId,
                        HandlerResult = result
                    });
                }
                catch (Exception ex)
                {
                    // Capture exception
                    failureRecords[recordId] = new RecordFailure<DynamoDBEvent.DynamodbStreamRecord>
                    {
                        Exception = new RecordProcessingException(
                            $"Failed processing record: '{recordId}'. See inner exception for details.", ex),
                        Record = record,
                        RecordId = recordId
                    };

                    Metrics.AddMetric("BatchRecordFailures", 1, MetricUnit.Count);

                    try
                    {
                        // Invoke hook
                        await HandleRecordFailureAsync(record, ex);
                    }
                    catch
                    {
                        // NOOP
                    }

                    // Check if we should stop record processing on first error
                    // ReSharper disable once ConditionIsAlwaysTrueOrFalse
                    if (errorHandlingPolicy == BatchProcessorErrorHandlingPolicy.StopOnFirstBatchItemFailure)
                    {
                        // This causes the loop's (inner) cancellation token to be cancelled for all operations already scheduled internally
                        throw new CircuitBreakerException(
                            "Error handling policy is configured to stop processing on first batch item failure. See inner exception for details.",
                            ex);
                    }
                }
            }
        }
        catch (Exception ex) when (ex is CircuitBreakerException or OperationCanceledException)
        {
            // NOOP
        }

        ProcessingResult.BatchRecords.AddRange(batchRecords.Select(x => x.Value));
        ProcessingResult.BatchItemFailuresResponse.BatchItemFailures.AddRange(failureRecords.Select(x =>
            new BatchItemFailuresResponse.BatchItemFailure
            {
                ItemIdentifier = x.Key
            }));
        ProcessingResult.FailureRecords.AddRange(failureRecords.Values);

        ProcessingResult.SuccessRecords.AddRange(successRecords.Values);

        return ProcessingResult;
    }

    // ReSharper disable once RedundantOverriddenMember
    protected override async Task HandleRecordFailureAsync(DynamoDBEvent.DynamodbStreamRecord record, Exception exception)
    {
        await base.HandleRecordFailureAsync(record, exception);
    }
}

Testing your code

As there is no external calls, you can unit test your code with BatchProcessor quite easily.

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[Fact]
public Task Sqs_Handler_Using_Attribute()
{
    var request = new SQSEvent
    {
        Records = TestHelper.SqsMessages
    };

    var function = new HandlerFunction();

    var response = function.HandlerUsingAttribute(request);

    Assert.Equal(2, response.BatchItemFailures.Count);
    Assert.Equal("2", response.BatchItemFailures[0].ItemIdentifier);
    Assert.Equal("4", response.BatchItemFailures[1].ItemIdentifier);

    return Task.CompletedTask;
}

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[BatchProcessor(RecordHandler = typeof(CustomSqsRecordHandler))]
public BatchItemFailuresResponse HandlerUsingAttribute(SQSEvent _)
{
    return SqsBatchProcessor.Result.BatchItemFailuresResponse;
}

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public class CustomSqsRecordHandler : ISqsRecordHandler
{
    public async Task<RecordHandlerResult> HandleAsync(SQSEvent.SQSMessage record, CancellationToken cancellationToken)
    {
        var product = JsonSerializer.Deserialize<JsonElement>(record.Body);

        if (product.GetProperty("Id").GetInt16() == 4)
        {
            throw new ArgumentException("Error on 4");
        }

        return await Task.FromResult(RecordHandlerResult.None);
    }
}

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internal static List<SQSEvent.SQSMessage> SqsMessages => new()
{
    new SQSEvent.SQSMessage
    {
        MessageId = "1",
        Body = "{\"Id\":1,\"Name\":\"product-4\",\"Price\":14}",
        EventSourceArn = "arn:aws:sqs:us-east-2:123456789012:my-queue"
    },
    new SQSEvent.SQSMessage
    {
        MessageId = "2",
        Body = "fail",
        EventSourceArn = "arn:aws:sqs:us-east-2:123456789012:my-queue"
    },
    new SQSEvent.SQSMessage
    {
        MessageId = "3",
        Body = "{\"Id\":3,\"Name\":\"product-4\",\"Price\":14}",
        EventSourceArn = "arn:aws:sqs:us-east-2:123456789012:my-queue"
    },
    new SQSEvent.SQSMessage
    {
        MessageId = "4",
        Body = "{\"Id\":4,\"Name\":\"product-4\",\"Price\":14}",
        EventSourceArn = "arn:aws:sqs:us-east-2:123456789012:my-queue"
    },
    new SQSEvent.SQSMessage
    {
        MessageId = "5",
        Body = "{\"Id\":5,\"Name\":\"product-4\",\"Price\":14}",
        EventSourceArn = "arn:aws:sqs:us-east-2:123456789012:my-queue"
    },
};