# PutAwsFirehose

Sends IDOL documents to an Amazon Kinesis Data Firehose. The Amazon Kinesis Data Firehose is a cloud service that can optionally transform the data before delivering it to one or more destinations, such as an Amazon S3 bucket.

## Properties

Name | Default Value | Description
--- | --- | ---
IDOL License Service |  | An IdolLicenseServiceImpl that provides a way to communicate with an IDOL License Server.
Aws Firehose Stream Name |  | The name of the Amazon Kinesis Data Firehose stream to send documents to. This is the name that you provided when you created the stream. You can create a Kinesis Data Firehose stream through the AWS Management Console, and the stream must exist before you configure NiFi Ingest.
Aws Firehose Access Key |  | The access key for the Amazon Kinesis Data Firehose stream.
Aws Firehose Secret Key |  | The secret key for the Amazon Kinesis Data Firehose stream.
Aws Firehose Enable Logging | false | A Boolean value that specifies whether to enable additional logging.
Aws Firehose Region | us-east-1 | The Amazon Web Services region that is hosting your Amazon Kinesis Data Firehose stream.
SSL Config Service |  | An IdolSSLConfigServiceImpl that specifies the settings to use to index documents over SSL/TLS.
Document Registry Service |  | A DocumentRegistryServiceImpl controller service that manages and updates a document registry database. This ensures that documents are indexed in the correct order.
Indexer Batch Size | 100 | The maximum number of FlowFiles to accumulate before indexing documents. Indexing documents in larger batches can be more efficient; indexing smaller batches more frequently means that an individual document might spend less time in the queue. Documents might be indexed in incomplete batches if the Indexing Interval Duration is reached first.
Indexing Interval Duration | 5 min | The maximum amount of time to wait between indexing batches of documents. Documents might be indexed more frequently than this if the Indexer Batch Size is reached first. Waiting longer and indexing documents in larger batches can be more efficient; indexing smaller batches more frequently means that an individual document might spend less time in the queue.

## Relationships

Name | Description
--- | ---
success | FlowFiles that were indexed successfully.
failure | FlowFiles that were not indexed successfully.

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