GCP Professional Data Engineer Practice Question

Your data engineering team needs to stream change data capture (CDC) events from an on-premises MySQL 8.0 database into BigQuery with end-to-end latency under two minutes. The solution must

require minimal custom code and operational overhead,
automatically propagate source-table schema changes to BigQuery, and
allow the future onboarding of an additional PostgreSQL source without major re-engineering. Which approach best meets these requirements?

Schedule daily exports from MySQL using BigQuery Data Transfer Service to load CSV files from Cloud Storage into BigQuery tables.
Configure Datastream to capture MySQL binary log events into a Cloud Storage staging bucket and invoke the Google-provided Datastream-to-BigQuery Dataflow template for continuous loading into BigQuery.
Deploy a self-managed Debezium connector that streams MySQL binlogs into Pub/Sub topics and trigger Cloud Functions to write each message to BigQuery.
Set up asynchronous replication from the on-premises MySQL instance to Cloud SQL, then query the replica directly from BigQuery using federated queries refreshed every hour.

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Answer Description

Google Cloud Datastream provides a fully managed, serverless way to capture MySQL and PostgreSQL change events. By configuring Datastream to read the MySQL 8.0 binary log (using GTID-based replication) and write the events to a Cloud Storage staging bucket, you can then launch the Google-provided "Datastream to BigQuery" Dataflow template. This managed template continuously loads the change stream into BigQuery, handles schema evolution, and requires no custom Dataflow code or infrastructure management. Onboarding a future PostgreSQL source only entails creating an additional Datastream stream that targets the same BigQuery dataset. In contrast:

Running a self-managed Debezium connector on Pub/Sub introduces significant operational burden.
Daily BigQuery Data Transfer Service loads are batch-oriented and violate the two-minute latency goal.
Cloud SQL replication plus hourly federated queries provides batch latency and adds administrative overhead. Therefore, the Datastream plus managed template approach best satisfies the stated constraints.

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