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Google Professional-Cloud-Database-Engineer Certification is designed for individuals who possess a deep understanding of Google Cloud Platform's database services, best practices, and solutions. Google Cloud Certified - Professional Cloud Database Engineer certification is ideal for IT professionals who specialize in database administration, engineering, or architecture and are looking to validate their skills and knowledge in this field. By obtaining this certification, individuals can demonstrate their expertise in designing, deploying, and managing highly available, scalable, and secure databases on Google Cloud Platform.

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To be eligible for the exam, candidates should have at least three years of experience in database administration or development, as well as experience with Google Cloud Platform. Candidates should also have a strong understanding of SQL, database design principles, and data modeling concepts.

Google Cloud Certified - Professional Cloud Database Engineer Sample Questions (Q177-Q182):

NEW QUESTION # 177
You are starting a large CSV import into a Cloud SQL for MySQL instance that has many open connections. You checked memory and CPU usage, and sufficient resources are available. You want to follow Google-recommended practices to ensure that the import will not time out. What should you do?

A. Increase the amount of memory allocated to your instance.
B. Close idle connections or restart the instance before beginning the import operation.
C. Ensure that the service account has the Storage Admin role.
D. Increase the number of CPUs for the instance to ensure that it can handle the additional import operation.

Answer: B

Explanation:
CPU and memory are OK so that elimiates B and D. C is nonsense which leaves A. This is supported by Google's own documention (read recommended practices) which says close unused operations and re-start the instance. This is the best way to ensure maximum resources for the import operation.
https://cloud.google.com/sql/docs/mysql/import-export#troubleshooting

NEW QUESTION # 178
You are designing a physician portal app in Node.js. This application will be used in hospitals and clinics that might have intermittent internet connectivity. If a connectivity failure occurs, the app should be able to query the cached dat a. You need to ensure that the application has scalability, strong consistency, and multi-region replication. What should you do?

A. Use Table.read with the exactStaleness option to perform a read of rows in Cloud Spanner.
B. Use Pub/Sub to synchronize the changes from the application to Cloud Spanner.
C. Use Firestore and ensure that the PersistenceEnabled option is set to true.
D. Use Memorystore for Memcached.

Answer: B

NEW QUESTION # 179
Your DevOps team is using Terraform to deploy applications and Cloud SQL databases. After every new application change is rolled out, the environment is torn down and recreated, and the persistent database layer is lost. You need to prevent the database from being dropped. What should you do?

A. Use point-in-time-recovery (PITR) to recover the database.
B. Rerun terraform apply.
C. Set Terraform deletion_protection to true.
D. Create a read replica.

Answer: C

Explanation:
. From Google's documentation, "For stateful resources, such as databases, ensure that deletion protection is enabled. The syntax is: lifecycle { prevent_destroy = true } https://cloud.google.com/docs/terraform/best-practices-for-terraform#stateful-resources

NEW QUESTION # 180
Your customer has a global chat application that uses a multi-regional Cloud Spanner instance. The application has recently experienced degraded performance after a new version of the application was launched. Your customer asked you for assistance. During initial troubleshooting, you observed high read latency. What should you do?

A. Change the Cloud Spanner configuration from multi-region to single region.
B. Use SQL statements to analyze SPANNER_SYS.READ_STATS* tables.
C. Use query parameters to speed up frequently executed queries.
D. Use SQL statements to analyze SPANNER_SYS.QUERY_STATS* tables.

Answer: B

Explanation:
To troubleshoot high read latency, you can use SQL statements to analyze the SPANNER_SYS.READ_STATS* tables. These tables contain statistics about read operations in Cloud Spanner, including the number of reads, read latency, and the number of read errors. By analyzing these tables, you can identify the cause of the high read latency and take appropriate action to resolve the issue. Other options, such as using query parameters to speed up frequently executed queries or changing the Cloud Spanner configuration from multi-region to single region, may not be directly related to the issue of high read latency. Similarly, analyzing the SPANNER_SYS.QUERY_STATS* tables, which contain statistics about query operations, may not be relevant to the issue of high read latency.

NEW QUESTION # 181
Your team is running a Cloud SQL for MySQL instance with a 5 TB database that must be available 24/7. You need to save database backups on object storage with minimal operational overhead or risk to your production workloads. What should you do?

A. Use Cloud SQL serverless exports.
B. Create a read replica, and then use the mysqldump utility to export each table.
C. Clone the Cloud SQL instance, and then use the mysqldump utlity to export the data.
D. Use the mysqldump utility on the primary database instance to export the backup.

Answer: A

Explanation:
https://cloud.google.com/blog/products/databases/introducing-cloud-sql-serverless-exports

NEW QUESTION # 182
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