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Google PROFESSIONAL-CLOUD-DATABASE-ENGINEER Exam Questions
Professional Cloud Database Engineer (Page 4 )

Updated On: 21-Feb-2026
Page 4 of 28
PDF with 182 Questions

Your organization operates in a highly regulated industry. Separation of concerns (SoC) and security principle of least privilege (PoLP) are critical. The operations team consists of:
Person A is a database administrator.
Person B is an analyst who generates metric reports.
Application C is responsible for automatic backups.

You need to assign roles to team members for Cloud Spanner.
Which roles should you assign?

  1. roles/spanner.databaseAdmin for Person A
    roles/spanner.databaseReader for Person B
    roles/spanner.backupWriter for Application C
  2. roles/spanner.databaseAdmin for Person A
    roles/spanner.databaseReader for Person B
    roles/spanner.backupAdmin for Application C
  3. roles/spanner.databaseAdmin for Person A
    roles/spanner.databaseUser for Person B

    roles/spanner databaseReader for Application C
  4. roles/spanner.databaseAdmin for Person A
    roles/spanner.databaseUser for Person B
    roles/spanner.backupWriter for Application C

Answer(s): A

Explanation:

https://cloud.google.com/spanner/docs/iam#spanner.backupWriter



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 SL

  1. 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?
  2. Manually scale down the number of nodes after the peak period has passed.
  3. Use interleaving to co-locate parent and child rows.
  4. Use the Cloud Spanner query optimizer to determine the most efficient way to execute the SQL query.
  5. Use granular instance sizing in Cloud Spanner and Autoscaler.

Answer(s): D

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



You recently launched a new product to the US market. You currently have two Bigtable clusters in one US region to serve all the traffic. Your marketing team is planning an immediate expansion to

APAC. You need to roll out the regional expansion while implementing high availability according to Google-recommended practices.
What should you do?

  1. Maintain a target of 23% CPU utilization by locating:
    cluster-a in zone us-central1-a cluster-b in zone europe-west1-d cluster-c in zone asia-east1-b
  2. Maintain a target of 23% CPU utilization by locating:
    cluster-a in zone us-central1-a cluster-b in zone us-central1-b cluster-c in zone us-east1-a
  3. Maintain a target of 35% CPU utilization by locating:
    cluster-a in zone us-central1-a cluster-b in zone australia-southeast1-a cluster-c in zone europe-west1-d cluster-d in zone asia-east1-b
  4. Maintain a target of 35% CPU utilization by locating:
    cluster-a in zone us-central1-a cluster-b in zone us-central2-a cluster-c in zone asia-northeast1-b cluster-d in zone asia-east1-b

Answer(s): D

Explanation:

https://cloud.google.com/bigtable/docs/replication-settings#regional-failover



Your ecommerce website captures user clickstream data to analyze customer traffic patterns in real time and support personalization features on your website. You plan to analyze this data using big data tools. You need a low-latency solution that can store 8 TB of data and can scale to millions of read and write requests per second.
What should you do?

  1. Write your data into Bigtable and use Dataproc and the Apache Hbase libraries for analysis.
  2. Deploy a Cloud SQL environment with read replicas for improved performance. Use Datastream to export data to Cloud Storage and analyze with Dataproc and the Cloud Storage connector.
  3. Use Memorystore to handle your low-latency requirements and for real-time analytics.
  4. Stream your data into BigQuery and use Dataproc and the BigQuery Storage API to analyze large volumes of data.

Answer(s): A

Explanation:

Start with the lowest tier and smallest size and then grow your instance as needed. Memorystore provides automated scaling using APIs, and optimized node placement across zones for redundancy. Memorystore for Memcached can support clusters as large as 5 TB, enabling millions of QPS at very low latency



Your company uses Cloud Spanner for a mission-critical inventory management system that is globally available. You recently loaded stock keeping unit (SKU) and product catalog data from a company acquisition and observed hot-spots in the Cloud Spanner database. You want to follow Google-recommended schema design practices to avoid performance degradation.
What should you do? (Choose two.)

  1. Use an auto-incrementing value as the primary key.
  2. Normalize the data model.
  3. Promote low-cardinality attributes in multi-attribute primary keys.
  4. Promote high-cardinality attributes in multi-attribute primary keys.
  5. Use bit-reverse sequential value as the primary key.

Answer(s): D,E

Explanation:

https://cloud.google.com/spanner/docs/schema-design D because high cardinality means you have more unique values in the collumn. That's a good thing for a hot-spotting issue. E because Spanner specifically has this feature to reduce hot spotting. Basically, it generates unique values https://cloud.google.com/spanner/docs/schema-design#bit_reverse_primary_key

D) Promote high-cardinality attributes in multi-attribute primary keys. This is a correct answer because promoting high-cardinality attributes in multi-attribute primary keys can help avoid hotspots in Cloud Spanner. High-cardinality attributes are those that have many distinct values, such as UUIDs, email addresses, or timestamps1. By placing high-cardinality attributes first in the primary key, you can ensure that the rows are distributed more evenly across the key space, and avoid having too many requests sent to the same server2. E) Use bit-reverse sequential value as the primary key. This is a correct answer because using bit-reverse sequential value as the primary key can help avoid hotspots in Cloud Spanner. Bit-reverse sequential value is a technique that reverses the bits of a monotonically increasing value, such as a timestamp or an auto-incrementing ID1. By reversing the bits, you can create a pseudo-random value that spreads the writes across the key space, and avoid having all the inserts occurring at the end of the table2.






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