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Google Professional-Cloud-Database-Engineer Exam Syllabus Topics:

Section	Objectives
Topic 1: Designing scalable and highly available cloud database solutions	- Select appropriate database services 1. Choose relational and non-relational databases 2. Plan scalability and availability strategies 3. Design globally distributed architectures
Topic 2: Optimizing database performance	- Improve database efficiency 1. Tune queries and indexes 2. Troubleshoot performance bottlenecks 3. Optimize storage and compute resources
Topic 3: Managing database solutions	- Deploy and administer databases 1. Implement monitoring and alerting 2. Configure backups and recovery 3. Manage maintenance and upgrades
Topic 4: Migrating data solutions	- Plan and execute migrations 1. Migrate on-premises databases to Google Cloud 2. Validate migrated workloads 3. Use Database Migration Service
Topic 5: Securing and ensuring compliance of database solutions	- Implement security best practices 1. Configure IAM and access controls 2. Ensure compliance and governance 3. Enable encryption and auditing

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Google Cloud Certified - Professional Cloud Database Engineer Sample Questions (Q76-Q81):

NEW QUESTION # 76
Your organization deployed a new version of a critical application that uses Cloud SQL for MySQL with high availability (HA) and binary logging enabled to store transactional information. The latest release of the application had an error that caused massive data corruption in your Cloud SQL for MySQL database. You need to minimize data loss. What should you do?

A. Perform a point-in-time recovery of your Cloud SQL for MySQL database, selecting a date and time before the data was corrupted.
B. Reload the Cloud SQL for MySQL database using the LOAD DATA command to load data from CSV files that were used to initialize the instance.
C. Open the Google Cloud Console, navigate to SQL > Backups, and select the last version of the automated backup before the corruption.
D. Fail over to the Cloud SQL for MySQL HA instance. Use that instance to recover the transactions that occurred before the corruption.

Answer: B

NEW QUESTION # 77
You are building a data warehouse on BigQuery. Sources of data include several MySQL databases located on-premises.
You need to transfer data from these databases into BigQuery for analytics. You want to use a managed solution that has low latency and is easy to set up. What should you do?

A. Create extracts from your on-premises databases periodically, and push these extracts to Cloud Storage.
Upload the changes into BigQuery, and merge them with existing tables.
B. Use Datastream to connect to your on-premises database and create a stream. Have Datastream write to Cloud Storage. Then use Dataflow to process the data into BigQuery.
C. Use Database Migration Service to replicate data to a Cloud SQL for MySQL instance. Create federated tables in BigQuery on top of the replicated instances to transform and load the data into your BigQuery database.
D. Use Cloud Data Fusion and scheduled workflows to extract data from MySQL. Transform this data into the appropriate schema, and load this data into your BigQuery database.

Answer: B

NEW QUESTION # 78
You are the primary DBA of a Cloud SQL for PostgreSQL database that supports 6 enterprise applications in production. You used Cloud SQL Insights to identify inefficient queries and now need to identify the application that is originating the inefficient queries. You want to follow Google-recommended practices. What should you do?

A. Write a utility to scan application logs.
B. Write a utility to scan database query logs.
C. Use query tags to add application-centric database monitoring.
D. Shut down and restart each application.

Answer: C

Explanation:
https://cloud.google.com/sql/docs/postgres/using-query-insights#filter_by_query_tags

NEW QUESTION # 79
You are running a mission-critical application on a Cloud SQL for PostgreSQL database with a multi-zonal setup. The primary and read replica instances are in the same region but in different zones. You need to ensure that you split the application load between both instances. What should you do?

A. Use the Cloud SQL Auth proxy for database connection pooling between the Cloud SQL primary and read replica instances.
B. Use Cloud Load Balancing for load balancing between the Cloud SQL primary and read replica instances.
C. Use HTTP(S) Load Balancing for database connection pooling between the Cloud SQL primary and read replica instances.
D. Use PgBouncer to set up database connection pooling between the Cloud SQL primary and read replica instances.

Answer: D

Explanation:
https://severalnines.com/blog/how-achieve-postgresql-high-availability-pgbouncer/
https://cloud.google.com/blog/products/databases/using-haproxy-to-scale-read-only-workloads-on-cloud-sql-for-postgresql This answer is correct because PgBouncer is a lightweight connection pooler for PostgreSQL that can help you distribute read requests between the Cloud SQL primary and read replica instances1. PgBouncer can also improve performance and scalability by reducing the overhead of creating new connections and reusing existing ones1. You can install PgBouncer on a Compute Engine instance and configure it to connect to the Cloud SQL instances using private IP addresses or the Cloud SQL Auth proxy2.

NEW QUESTION # 80
Your organization is running a MySQL workload in Cloud SQL. Suddenly you see a degradation in database performance. You need to identify the root cause of the performance degradation. What should you do?

A. Use Error Reporting to count, analyze, and aggregate the data.
B. Use Logs Explorer to analyze log data.
C. Use Cloud Monitoring to monitor CPU, memory, and storage utilization metrics.
D. Use Cloud Debugger to inspect the state of an application.

Answer: C

NEW QUESTION # 81
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