Batch Processing - Powertools for AWS Lambda (.NET) (original) (raw)

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:

Or via the .NET Core command line interface:

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:

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.

SQSKinesis Data StreamsDynamoDB Streams

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

Function.csSample eventSample response

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

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

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

Function.csSample eventSample response

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

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

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

Function.csSample eventSample response

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

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

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.

Function.csSample eventSample response

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

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.

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

Function.cs

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)

Function.cs

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

GetRequiredService inside the methodInjecting method parametersExample implementation of IServiceProvider

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).

Function.cs

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.

Setting ThrowOnFullBatchFailure on DecoratorSetting ThrowOnFullBatchFailure outside Decorator

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.

Function.cs

Testing your code¶

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

Test.csFunction.csCustomSqsRecordHandler.csSQS Event.cs