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Cloud Database Engineer PCDE Practice Questions

Google Cloud Certified - Professional Cloud Database Engineer

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Question 1

You are a DBA at a retail company. The production databases are running in Cloud SQL for MySQL Enterprise Plus edition, version 8.0.34, in the us-central1 region. You need to set up and test disaster recovery (DR) with zero data loss in the us-west1 region. What should you do?

Create a cross-region read replica, version 8.0.34, in the us-west1 region. Test switchover by using the gcloud promote-replica with failover command.
Create a cross-region read replica version 8.0.34, in the us-west1 region. Designate it as the failover DR replica, and test switchover by using the gcloud switchover command.
Use advanced DR by setting up a cascading read replica in the us-west1 region, and designate it as the failover DR replica. Test switchover by using the gcloud switchover command.
Create a cross-region read replica, version 8.0.37, in the us-west1 region. Designate it as the failover DR replica, and test switchover by using the gcloud switchover command.

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Question 2

You have a single global application that uses clickstream data stored in a Bigtable instance. The application's users are spread across North America, Asia, and Europe. You want to reduce user latency, while keeping costs to a minimum. What should you do?

Create one instance of Bigtable with three clusters in one central region across three zones. Set up a single app profile with multi-cluster routing.
Create one instance of Bigtable with three clusters in a region in North America, Asia, and Europe. Set up a single app profile with multi-cluster routing.
Create three instances of Bigtable, each one in a region in North America, Asia, and Europe. Set up three app profiles, one for each region with single-cluster routing.
Create one instance of Bigtable with three clusters in a region in North America, Asia, and Europe. Set up three app profiles, one for each region with single-cluster routing.

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Question 3

You are designing a new ecommerce application on Google Cloud. You expect high and bursty write volumes during peak sales periods. You need to configure Spanner to ensure consistent database performance during this sales period. What should you do?

Enable autoscaling in the Spanner instance, and set the maximum number of nodes to match the peak write volume.
Implement sharding to distribute the write load across multiple Spanner instances.
Use interleaved tables to reduce the number of cross-node transactions.
Configure read-only transactions to improve read performance during peak periods.

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Question 4

You work at a retail company using Cloud SQL for MySQL to store transactional data. You need to combine the transactional data with customer behavior information from BigQuery to make real-time sales predictions using machine learning. You want to accomplish this without incurring the overhead costs of moving the data out of their respective data stores. What should you do?

Use BigQuery ML for predictions, and combine federated queries to Cloud SQL.
Refactor the application to simultaneously write data to both MySQL and BigQuery. Use BigQuery to generate predictions.
Extract data from BigQuery into Cloud SQL, and use Gemini Enterprise Agent Platform to generate predictions.
Use Datastream to build ETL/ELT pipelines to move data from Cloud SQL to BigQuery. Use BigQuery ML for predictions.

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Question 5

Your Cloud SQL for PostgreSQL database supporting a financial application has been experiencing "deadlock detected" errors during end-of-month processing. You notice that CPU utilization spikes to 90% during these periods, and several long-running queries are consuming significant resources. You need to identify the specific queries causing the deadlocks and implement monitoring to solve similar issues before they cause application failures. What should you do?

Optimize SQL queries by adding appropriate indexes to frequently accessed columns and rewriting complex joins to use LEFT JOIN instead of INNER JOIN , where applicable.
Use Cloud SQL System Insights to identify long-running queries and number of deadlocks that occurred in the database. Enable a log_lock_waits flag to determine if lock waits are causing poor performance. Set up Cloud Monitoring alerts for higher CPU utilization and connection count.
Increase the deadlock_timeout parameter on the Cloud SQL for PostgreSQL instance. Export logs to Cloud Logging, and create log-based metrics to track deadlock occurrences.
Implement connection pooling at the application layer to reduce the number of direct database connections and optimize shared_buffers and work_mem parameters in Cloud SQL for PostgreSQL to improve query execution efficiency.

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Question 6

You are migrating your company's critical ecommerce platform from an on-premises PostgreSQL database (utilizing PostgreSQL stored procedures) to a highly available solution on Google Cloud. The platform requires an extremely low downtime (Recovery Time Objective (RTO) - 5 minutes) and minimal data loss (Recovery Point Objective - 30 seconds). The platform serves a global customer base with peak traffic distributed across multiple continents, though the primary transactional data resides in a single geographic region for regulatory compliance. You need to design a cloud database solution that meets the RTO/RPO requirements while optimizing for global read access and local transactional integrity. What should you do?

Implement a multi-regional Cloud SQL for PostgreSQL deployment with read replicas in different regions, and configure asynchronous replication for cross-region data consistency.
Deploy a single-region AlloyDB cluster with a primary instance and a read replica in the same zone.
Deploy an AlloyDB cluster in the primary region with a high-availability instance configuration, and establish cross-region read replicas in another region for global read scaling.
Implement a single-instance Spanner deployment configured for multi-regional data replication.

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