Streaming data to tables with Amazon Data Firehose - Amazon Simple Storage Service

Streaming data to tables with Amazon Data Firehose

Note

The integration with AWS analytics services for table buckets is in preview release and is subject to change.

Amazon Data Firehose is a fully managed service for delivering real-time streaming data to destinations such as Amazon S3, Amazon Redshift, Amazon OpenSearch Service, Splunk, Apache Iceberg Tables, and custom HTTP endpoint or HTTP endpoints owned by supported third-party service providers. With Amazon Data Firehose, you don't need to write applications or manage resources. You configure your data producers to send data to Firehose, and it automatically delivers the data to the destination that you specified. You can also configure Firehose to transform your data before delivering it. To learn more about Amazon Data Firehose, see What is Amazon Data Firehose.

After you Integrate your table buckets with AWS analytics services, you can configure Firehose to deliver data into your S3 tables. To do so, you create an IAM service role that allows Firehose to access your tables. Next, you create a resource link to your table or table's namespace and grant the Firehose service role explicit permissions to those resources. Then, you can create a Firehose stream that routes data to your table.

Creating a role for Firehose to use S3 tables as a destination

Firehose needs an IAM service role with specific permissions to access AWS Glue tables and write data to S3 tables. You need this provide this IAM role when you create an Firehose stream.

  1. Open the IAM console at https://console.aws.amazon.com/iam/.

  2. In the left navigation pane, choose Policies

  3. Choose Create a policy, and choose JSON in policy editor.

  4. Add the following inline policy that grants permissions to all databases and tables in your data catalog. If you want, you can give permissions only to specific tables and databases. To use this policy, replace the input placeholders with your own information.

    { "Version": "2012-10-17", "Statement": [ { "Sid": "S3TableAccessViaGlueFederation", "Effect": "Allow", "Action": [ "glue:GetTable", "glue:GetDatabase", "glue:UpdateTable" ], "Resource": [ "arn:aws:glue:<region>:<account-id>:catalog/s3tablescatalog/*", "arn:aws:glue:<region>:<account-id>:catalog/s3tablescatalog", "arn:aws:glue:<region>:<account-id>:catalog", "arn:aws:glue:<region>:<account-id>:database/*", "arn:aws:glue:<region>:<account-id>:table/*/*" ] }, { "Sid": "S3DeliveryErrorBucketPermission", "Effect": "Allow", "Action": [ "s3:AbortMultipartUpload", "s3:GetBucketLocation", "s3:GetObject", "s3:ListBucket", "s3:ListBucketMultipartUploads", "s3:PutObject" ], "Resource": [ "arn:aws:s3:::<error delivery bucket>", "arn:aws:s3:::<error delivery bucket>/*" ] }, { "Sid": "RequiredWhenUsingKinesisDataStreamsAsSource", "Effect": "Allow", "Action": [ "kinesis:DescribeStream", "kinesis:GetShardIterator", "kinesis:GetRecords", "kinesis:ListShards" ], "Resource": "arn:aws:kinesis:<region>:<account-id>:stream/<stream-name>" }, { "Sid": "RequiredWhenDoingMetadataReadsANDDataAndMetadataWriteViaLakeformation", "Effect": "Allow", "Action": [ "lakeformation:GetDataAccess" ], "Resource": "*" }, { "Sid": "RequiredWhenUsingKMSEncryptionForS3ErrorBucketDelivery", "Effect": "Allow", "Action": [ "kms:Decrypt", "kms:GenerateDataKey" ], "Resource": [ "arn:aws:kms:<region>:<account-id>:key/<KMS-key-id>" ], "Condition": { "StringEquals": { "kms:ViaService": "s3.<region>.amazonaws.com" }, "StringLike": { "kms:EncryptionContext:aws:s3:arn": "arn:aws:s3:::<error delivery bucket>/prefix*" } } }, { "Sid": "LoggingInCloudWatch", "Effect": "Allow", "Action": [ "logs:PutLogEvents" ], "Resource": [ "arn:aws:logs:<region>:<account-id>:log-group:<log-group-name>:log-stream:<log-stream-name>" ] }, { "Sid": "RequiredWhenAttachingLambdaToFirehose", "Effect": "Allow", "Action": [ "lambda:InvokeFunction", "lambda:GetFunctionConfiguration" ], "Resource": [ "arn:aws:lambda:<region>:<account-id>:function:<function-name>:<function-version>" ] } ] }

    This policy has a statements that allow access to Kinesis Data Streams, invoking Lambda functions and access to AWS KMS keys. If you don't use any of these resources, you can remove the respective statements.

    If error logging is enabled, Firehose also sends data delivery errors to your CloudWatch log group and streams. For this, you must configure log group and log stream names. For log group and log stream names, see Monitor Amazon Data Firehose Using CloudWatch Logs.

  5. After you create the policy, create an IAM role with AWS service as the Trusted entity type.

  6. For Service or use case, choose Kinesis. For Use case choose Kinesis Firehose.

  7. Choose Next, and then select the policy you created earlier.

  8. Give your role a name. Review your role details, and choose Create role. The role will have the following trust policy.

    { "Version": "2012-10-17", "Statement": [ { "Effect": "Allow", "Action": [ "sts:AssumeRole" ], "Principal": { "Service": [ "firehose.amazonaws.com" ] } } ] }

Setting up a Firehose stream to S3 tables

The following procedure shows how to setup a Firehose stream to deliver data to S3 tables using the console. The following prerequisites are required to set up a Firehose stream to S3 tables.

Prerequisites

To provide routing information to Firehose when you configure a stream, you use the name of resource link you created for your namespace as the database name and the name of a table in that namespace. You can use these values in the Unique key section of a Firehose stream configuration to route data to a single table. You can also use this values to route to a table using JSON Query expressions. For more information, see Route incoming records to a single Iceberg table.

To set up a Firehose stream to S3 tables (Console)
  1. Open the Firehose console at https://console.aws.amazon.com/firehose/.

  2. Choose Create Firehose stream.

  3. For Source, choose one of the following sources:

    • Amazon Kinesis Data Streams

    • Amazon MSK

    • Direct PUT

  4. For Destination, choose Apache Iceberg Tables.

  5. Enter a Firehose stream name.

  6. Configure your Source settings.

  7. For Destination settings, select Current Account and the AWS Region of the tables you want to stream to.

  8. Configure database and table names using Unique Key configuration, JSONQuery expressions, or in a Lambda function. For more information, refer to Route incoming records to a single Iceberg table and Route incoming records to different Iceberg tables in the Firehose Developer Guide.

  9. Under Backup settings, specify a S3 backup bucket.

  10. For Existing IAM roles under Advanced settings, select the IAM role you created for Firehose.

  11. Choose Create Firehose stream.

For more information about the other settings you can configure for a stream, see Set up the Firehose stream in the Firehose Developer Guide.