DEA-C01 Practice Question 82: Firehose Iceberg Destination Updates
AWS Certified Data Engineer – Associate (DEA-C01) · Test 9 · question 2 of 10
An application publishes change events for several business entities into one stream. The data engineering team wants the events written directly to separate Apache Iceberg tables in Amazon S3, with inserts, updates and deletes applied to the tables, and they do not want to build or operate a Spark streaming application. Which solution meets these requirements?
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Answer:
*"You can use Firehose to deliver streaming data to Apache Iceberg Tables in Amazon S3."* AWS explains that *"this feature allows you to route records from a single stream into different Apache Iceberg Tables. You can automatically apply insert, update, and delete operations to records in those tables."* It is a managed configuration, with no streaming application to run (option B).
- A is wrong because JSON files plus a daily job give a batch pipeline with high latency. The team would still need to write the job that applies updates and deletes. - C is wrong because producing valid Iceberg data and metadata files from Lambda means writing and operating custom code, and it is easy to get wrong. - D is wrong because DynamoDB is not an Iceberg writer, and hourly exports would produce snapshot files rather than Iceberg tables with row-level changes applied.
Reference: Deliver data to Apache Iceberg Tables with Amazon Data Firehose