PCDE Practice Test 8 — 10 Questions

Question 1

A team is designing a relational schema for a new application on Cloud SQL. The schema includes a table 'Orders' and a table 'Customers'. Each order belongs to one customer. The team anticipates high write throughput and needs to enforce referential integrity. Which schema design is most appropriate?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

Use a foreign key constraint from Orders.customer_id to Customers.customer_id. Using a foreign key constraint from Orders.customer_id to Customers.customer_id enforces referential integrity at the database level, which is essential for maintaining data consistency in a relational schema. Cloud SQL (e.g., MySQL or PostgreSQL) natively supports foreign key constraints, ensuring that every order references an existing customer without relying on application logic. This approach is efficient for high write throughput as the database handles the check atomically, avoiding race conditions.

Answer

Use Cloud Spanner interleaved tables with Orders as a child of Customers

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Implement referential integrity checks in the application code and omit database constraints

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Store order data as a JSON array in a column of the Customers table

Question 2

An organization wants to implement a blameless postmortem culture after incidents. Which of the following is a key practice in blameless postmortems?

Accepted Answer

Identifying contributing factors using techniques like the 5 Whys. Blameless postmortems focus on identifying contributing factors and systemic issues, not individual blame. The 5 Whys technique helps uncover root causes.

Answer

Firing the responsible engineer to prevent recurrence

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Assigning blame to the engineer who made the mistake

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Immediately implementing a fix without documentation

Question 3

A company wants to implement Binary Authorization for containers deployed to GKE. They need to ensure that only images signed by their internal CI system are allowed to run. Which three components are required?

Accepted Answer

An attestor in Binary Authorization. Binary Authorization requires images to be signed (e.g., using Cloud Key Management Service or Signify), an attestor that verifies signatures, and an admission controller (Binary Authorization) that enforces the policy on the cluster.

Answer

Cloud Build with privilege escalation mode

Answer

Container Registry with vulnerability scanning enabled

Question 4

An organization wants to restrict the creation of Cloud SQL instances outside of specific regions. Which organization policy constraint should they use?

Accepted Answer

`resourceLocations`. The `resourceLocations` constraint is the correct organization policy to restrict Cloud SQL instance creation to specific regions. This policy defines a list of allowed locations (e.g., `us-central1`, `europe-west1`) where all resources, including Cloud SQL instances, can be created. By setting this constraint at the organization, folder, or project level, any attempt to create a Cloud SQL instance outside the permitted regions will be denied.

Answer

`compute.requireShieldedVm`

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`iam.disableServiceAccountKeyCreation`

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`sql.restrictPublicIp`

Question 5

A team uses Skaffold for local development and wants to integrate it into their CI/CD pipeline on Cloud Build for continuous deployment to GKE. What is the recommended approach?

Accepted Answer

Use 'skaffold run' in a Cloud Build step. Skaffold can be run as a step in cloudbuild.yaml. It handles building, tagging, and deploying based on skaffold.yaml configuration. Using 'skaffold run' in a Cloud Build step is the standard integration.

Answer

Use Cloud Build's built-in kubectl deployer

Answer

Run 'skaffold dev' in the Cloud Build step

Answer

Convert skaffold.yaml to a Helm chart

Question 6

A company is designing a disaster recovery strategy for their Cloud Spanner database. They need an RPO of less than 30 seconds and an RTO of less than 1 minute. Which two configurations would meet these requirements? (Choose TWO)

Accepted Answer

Multi-region configuration with read-write replicas (e.g., nam3). The correct answers are B and D. A multi-region configuration with read-write replicas (e.g., nam3) provides automatic failover across regions with an RPO of approximately 15 seconds and an RTO of less than 1 minute, meeting the requirements for region-level failures. A regional instance in Cloud Spanner provides synchronous replication within the region, achieving an RPO of zero and an RTO of seconds, which meets the requirements for zone-level failures within a region. Option A (cross-region backup and restore) typically has an RPO of hours and RTO of hours, so it does not meet the strict RPO/RTO. Option C (point-in-time recovery) provides RPO of seconds to minutes but depends on backups and may not achieve RTO <1 minute for restore operations. Option E (multi-region with read-only replicas) does not support automatic failover because read-only replicas cannot become the new leader, so failover is not automatic and RTO would be longer.

Answer

Cross-region backup and restore

Answer

Point-in-time recovery (PITR)

Answer

Multi-region configuration with read-only replicas

Question 7

You are designing a Firestore database for a chat application. Documents will store messages with fields: senderId, messageText, timestamp, conversationId. To efficiently retrieve the most recent 50 messages in a conversation, which index should you create?

Accepted Answer

A composite index on (conversationId, timestamp, __name__) descending. To efficiently retrieve the most recent 50 messages for a specific conversation, you need a composite index on (conversationId, timestamp, __name__) with descending order. This allows Firestore to perform a range query on conversationId and then order by timestamp descending, using the index to skip scanning irrelevant documents. The __name__ field is included to ensure the index is covering and to handle document name ordering ties, which is required for consistent pagination with descending order.

Answer

A single-field index on timestamp

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An index on conversationId only

Answer

A composite index on (senderId, timestamp)

Question 8

A company is using DMS to migrate a MySQL database to Cloud SQL with continuous replication. During the CDC phase, the replication lag is increasing and not catching up. The source database is heavily used for OLTP workloads. Which action would most likely reduce the replication lag?

Accepted Answer

Reduce the number of concurrent write operations on the source database.. Increasing the source database's binary log retention period does not reduce lag; it retains more logs. Reducing concurrent writes on source directly slows the rate of change, allowing DMS to catch up.

Answer

Increase the size of the Cloud SQL destination instance.

Answer

Increase the binary log retention period on the source.

Answer

Enable parallel replication on DMS.

Question 9

Which TWO data types are supported in Cloud Spanner schemas?

Accepted Answer

ARRAY. ARRAY is a supported data type in Cloud Spanner, allowing you to store ordered lists of elements of the same primitive type (e.g., ARRAY, ARRAY). This is essential for modeling one-to-many relationships without requiring separate tables, and it integrates seamlessly with Cloud Spanner's query engine for array operations.

Answer

GEOMETRY

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TEXT

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TINYINT

Question 10

A financial services company uses BigQuery to run complex analytical queries on trading data. They notice that a particular query joining a large fact table (10 TB) with a small dimension table (100 MB) is slow. The fact table is partitioned by date and clustered by symbol. The dimension table is not partitioned. The query filters on a specific date range and a few symbols. Which optimization is MOST likely to improve query performance?

Accepted Answer

Enable automatic query rewriting to use clustering keys for pruning on the dimension table join.. BigQuery's automatic query rewriting can leverage clustering keys from the fact table to prune the join, even though the dimension table is not clustered. When the query filters on a specific date range and symbols, BigQuery can use the fact table's clustering on symbol to skip irrelevant blocks during the join, reducing data scanned and improving performance. This optimization is automatic and does not require manual denormalization or repartitioning.

Answer

Denormalize the dimension table into the fact table.

Answer

Partition the dimension table by its primary key.

Answer

Cluster the dimension table on its primary key.