Google Professional-Cloud-Database-Engineer PDF, Free Professional-Cloud-Database-Engineer Test Questions

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

Section	Objectives
Topic 1: Design scalable and highly available database solutions	- Select appropriate database services (relational, NoSQL, analytical) 1. Cloud SQL vs AlloyDB vs Spanner selection criteria 2. Firestore and document database patterns 3. Bigtable use cases and schema design - Design for high availability and disaster recovery 1. Regional vs multi-regional architectures 2. Replication strategies and failover design
Topic 2: Migrate data solutions to Google Cloud	- Database migration strategies 1. Online vs offline migration tools (e.g., Database Migration Service) 2. Lift-and-shift vs re-platforming
Topic 3: Manage a database solution spanning multiple systems	- Operational database management 1. Backup and restore strategies 2. Capacity planning and scaling 3. Monitoring and performance tuning
Topic 4: Ensure reliability, performance, and optimization	- Security and compliance 1. Encryption at rest and in transit 2. IAM roles and access control - Performance optimization 1. Indexing, query optimization, and caching strategies 2. Workload tuning across database services

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Google Cloud Certified - Professional Cloud Database Engineer Sample Questions (Q145-Q150):

NEW QUESTION # 145
Your application stores session documents in Firestore and queries them by steps, sessionDuration, and energyBurned. After a 30 day test period, latency is acceptable but costs are high. Which Firestore change would reduce cost while preserving performance and availability?

A. Use batched writes for lower cost
B. Denormalize documents
C. Trim Firestore indexes to only required ones
D. Add Cloud Memorystore cache

Answer: B

Explanation:
Firestore automatically creates single field indexes for most fields which means each document write updates multiple index entries and drives up write and storage costs. By trimming indexes to only the ones required by your queries on steps, sessionDuration and energyBurned you reduce index write amplification and index storage while preserving the performance of the queries you care about. This is a configuration change that does not reduce availability because Firestore remains fully managed and you keep the essential indexes for your filters and sort orders.
You can delete unused composite indexes and add single field index exemptions for attributes that are not part of your supported query patterns. Monitor index usage and keep only the minimal set that powers production queries so you sustain acceptable latency while lowering cost.

NEW QUESTION # 146
You plan to use Database Migration Service to migrate data from a PostgreSQL on-premises instance to Cloud SQL. You need to identify the prerequisites for creating and automating the task. What should you do? (Choose two.)

A. Ensure that all PostgreSQL tables have a primary key.
B. Disable all foreign key constraints on the source PostgreSQL database.
C. Ensure that pglogical is installed on the source PostgreSQL database.
D. Drop or disable all users except database administration users.
E. Shut down the database before the Data Migration Service task is started.

Answer: A,C

Explanation:
https://cloud.google.com/database-migration/docs/postgres/faq

NEW QUESTION # 147
Your team uses thousands of connected IoT devices to collect device maintenance data for your oil and gas customers in real time. You want to design inspection routines, device repair, and replacement schedules based on insights gathered from the data produced by these devices. You need a managed solution that is highly scalable, supports a multi-cloud strategy, and offers low latency for these IoT devices. What should you do?

A. Use Firestore with Looker.
B. Use MongoD8 Atlas with Charts.
C. Use Bigtable with Looker.
D. Use Cloud Spanner with Data Studio.

Answer: B

Explanation:
This scenario has BigTable written all over it - large amounts of data from many devices to be analysed in realtime. I would even argue it could qualify as a multicloud solution, given the links to HBASE. BUT it does not support SQL queries and is not therefore compatible (on its own) with Looker. Firestore + Looker has the same problem. Spanner + Data Studio is at least a compatible pairing, but I agree with others that it doesn't fit this use-case - not least because it's Google-native. By contrast, MongoDB Atlas is a managed solution (just not by Google) which is compatible with the proposed reporting tool (Mongo's own Charts), it's specifically designed for this type of solution and of course it can run on any cloud.

NEW QUESTION # 148
You want to migrate your on-premises PostgreSQL database to Compute Engine. You need to migrate this database with the minimum downtime possible. What should you do?

A. Perform a full backup of your on-premises PostgreSQL, and then, in the migration window, perform an incremental backup.
B. Create a read replica on Cloud SQL, and then promote it to a read/write standalone instance.
C. Create a hot standby on Compute Engine, and use PgBouncer to switch over the connections.
D. Use Database Migration Service to migrate your database.

Answer: C

Explanation:
https://cloud.google.com/architecture/migrating-postgresql-to-gcp

NEW QUESTION # 149
You are designing an augmented reality game for iOS and Android devices. You plan to use Cloud Spanner as the primary backend database for game state storage and player authentication. You want to track in-game rewards that players unlock at every stage of the game. During the testing phase, you discovered that costs are much higher than anticipated, but the query response times are within the SLA.
You want to follow Google-recommended practices. You need the database to be performant and highly available while you keep costs low. What should you do?

A. Use interleaving to co-locate parent and child rows.
B. Use granular instance sizing in Cloud Spanner and Autoscaler.
C. Use the Cloud Spanner query optimizer to determine the most efficient way to execute the SQL query.
D. Manually scale down the number of nodes after the peak period has passed.

Answer: B

Explanation:
Granular instance is available in Public Preview. With this feature, you can run workloads on Spanner at as low as 1/10th the cost of regular instances, https://cloud.google.com/blog/products/databases/get-more-out-of-spanner-with-granular-instance-sizing

NEW QUESTION # 150
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