Amazon Data Firehose Data Transformation - Amazon Data Firehose

Amazon Data Firehose was previously known as Amazon Kinesis Data Firehose

Amazon Data Firehose Data Transformation

Amazon Data Firehose can invoke your Lambda function to transform incoming source data and deliver the transformed data to destinations. You can enable Amazon Data Firehose data transformation when you create your Firehose stream.

Data Transformation Flow

When you enable Firehose data transformation, Firehose buffers incoming data. The buffering size hint ranges between 0.2 MB and 3MB. The default Lambda buffering size hint is 1 MB for all destinations, except Splunk. For Splunk, the default buffering hint is 256 KB. The Lambda buffering interval hint ranges between 0 and 900 seconds. The default Lambda buffering interval hint is sixty seconds for all destinations. To adjust the buffering size, set the ProcessingConfiguration parameter of the CreateDeliveryStream or UpdateDestination API with the ProcessorParameter called BufferSizeInMBs and IntervalInSeconds. Firehose then invokes the specified Lambda function asynchronously with each buffered batch using the AWS Lambda synchronous invocation mode. The transformed data is sent from Lambda to Firehose. Firehose then sends it to the destination when the specified destination buffering size or buffering interval is reached, whichever happens first.

Important

The Lambda synchronous invocation mode has a payload size limit of 6 MB for both the request and the response. Make sure that your buffering size for sending the request to the function is less than or equal to 6 MB. Also ensure that the response that your function returns doesn't exceed 6 MB.

Data Transformation and Status Model

All transformed records from Lambda must contain the following parameters, or Amazon Data Firehose rejects them and treats that as a data transformation failure.

For Kinesis Data Streams and Direct PUT:

recordId

The record ID is passed from Amazon Data Firehose to Lambda during the invocation. The transformed record must contain the same record ID. Any mismatch between the ID of the original record and the ID of the transformed record is treated as a data transformation failure.

result

The status of the data transformation of the record. The possible values are: Ok (the record was transformed successfully), Dropped (the record was dropped intentionally by your processing logic), and ProcessingFailed (the record could not be transformed). If a record has a status of Ok or Dropped, Amazon Data Firehose considers it successfully processed. Otherwise, Amazon Data Firehose considers it unsuccessfully processed.

data

The transformed data payload, after base64-encoding.

Following is a sample Lambda result output:

{ "recordId": "<recordId from the Lambda input>", "result": "Ok", "data": "<Base64 encoded Transformed data>" }

For Amazon MSK

recordId

The record ID is passed from Firehose to Lambda during the invocation. The transformed record must contain the same record ID. Any mismatch between the ID of the original record and the ID of the transformed record is treated as a data transformation failure.

result

The status of the data transformation of the record. The possible values are: Ok (the record was transformed successfully), Dropped (the record was dropped intentionally by your processing logic), and ProcessingFailed (the record could not be transformed). If a record has a status of Ok or Dropped, Firehose considers it successfully processed. Otherwise, Firehose considers it unsuccessfully processed.

KafkaRecordValue

The transformed data payload, after base64-encoding.

Following is a sample Lambda result output:

{ "recordId": "<recordId from the Lambda input>", "result": "Ok", "kafkaRecordValue": "<Base64 encoded Transformed data>" }

Lambda Blueprints

These blueprints demonstrate how you can create and use AWS Lambda functions to transform data in your Amazon Data Firehose data streams.

To see the blueprints that are available in the AWS Lambda console
  1. Sign in to the AWS Management Console and open the AWS Lambda console at https://console.aws.amazon.com/lambda/.

  2. Choose Create function, and then choose Use a blueprint.

  3. In the Blueprints field, search for the keyword firehose to find the Amazon Data Firehose Lambda blueprints.

List of blueprints:

  • Process records sent to Amazon Data Firehose stream (Node.js, Python)

    This blueprint shows a basic example of how to process data in your Firehose data stream using AWS Lambda.

    Latest release date: November, 2016.

    Release notes: none.

  • Process CloudWatch logs sent to Firehose

    This blueprint is deprecated. For information on processing CloudWatch Logs sent to Firehose, see Writing to Firehose Using CloudWatch Logs.

  • Convert Amazon Data Firehose stream records in syslog format to JSON (Node.js)

    This blueprint shows how you can convert input records in RFC3164 Syslog format to JSON.

    Latest release date: Nov, 2016.

    Release notes: none.

To see the blueprints that are available in the AWS Serverless Application Repository
  1. Go to AWS Serverless Application Repository.

  2. Choose Browse all applications.

  3. In the Applications field, search for the keyword firehose.

You can also create a Lambda function without using a blueprint. See Getting Started with AWS Lambda.

Data Transformation Failure Handling

If your Lambda function invocation fails because of a network timeout or because you've reached the Lambda invocation limit, Amazon Data Firehose retries the invocation three times by default. If the invocation does not succeed, Amazon Data Firehose then skips that batch of records. The skipped records are treated as unsuccessfully processed records. You can specify or override the retry options using the CreateDeliveryStream or UpdateDestination API. For this type of failure, you can log invocation errors to Amazon CloudWatch Logs. For more information, see Monitoring Amazon Data Firehose Using CloudWatch Logs.

If the status of the data transformation of a record is ProcessingFailed, Amazon Data Firehose treats the record as unsuccessfully processed. For this type of failure, you can emit error logs to Amazon CloudWatch Logs from your Lambda function. For more information, see Accessing Amazon CloudWatch Logs for AWS Lambda in the AWS Lambda Developer Guide.

If data transformation fails, the unsuccessfully processed records are delivered to your S3 bucket in the processing-failed folder. The records have the following format:

{ "attemptsMade": "count", "arrivalTimestamp": "timestamp", "errorCode": "code", "errorMessage": "message", "attemptEndingTimestamp": "timestamp", "rawData": "data", "lambdaArn": "arn" }
attemptsMade

The number of invocation requests attempted.

arrivalTimestamp

The time that the record was received by Amazon Data Firehose.

errorCode

The HTTP error code returned by Lambda.

errorMessage

The error message returned by Lambda.

attemptEndingTimestamp

The time that Amazon Data Firehose stopped attempting Lambda invocations.

rawData

The base64-encoded record data.

lambdaArn

The Amazon Resource Name (ARN) of the Lambda function.

Duration of a Lambda Invocation

Amazon Data Firehose supports a Lambda invocation time of up to 5 minutes. If your Lambda function takes more than 5 minutes to complete, you get the following error: Firehose encountered timeout errors when calling AWS Lambda. The maximum supported function timeout is 5 minutes.

For information about what Amazon Data Firehose does if such an error occurs, see Data Transformation Failure Handling.

Source Record Backup

Amazon Data Firehose can back up all untransformed records to your S3 bucket concurrently while delivering transformed records to the destination. You can enable source record backup when you create or update your Firehose stream. You cannot disable source record backup after you enable it.