PCDE Mock Exam 83 — 25 Questions

Question 1

A BI team uses BigQuery BI Engine to accelerate dashboards. They have a 100 GB table and enable BI Engine with a reservation of 10 GB. Some queries on this table are still slow. What is the most likely reason?

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

Accepted Answer

The query selects columns that are not fully cached due to the small reservation size.. BI Engine accelerates queries by caching columns in memory. With a 100 GB table and only a 10 GB reservation, the cache can hold only a fraction of the table's columns. Queries that reference columns not fully cached will fall back to BigQuery's standard execution, causing slow performance.

Answer

BI Engine only works with SQL views, not direct tables.

Answer

The table uses clustering, which BI Engine ignores.

Answer

The table is partitioned, which BI Engine does not support.

Question 2

Arrange the steps to import data from Cloud Storage into Cloud Firestore using a managed import.

Accepted Answer

First, run the gcloud firestore import command specifying the Cloud Storage URI. Second, monitor the import operation using gcloud firestore operations describe. Third, verify the imported data in Cloud Firestore.. Import needs properly formatted files; use gcloud command, then monitor and verify.

Answer

First, monitor the import operation using gcloud firestore operations describe. Second, run the gcloud firestore import command. Third, verify the imported data in Cloud Firestore.

Answer

First, verify the imported data in Cloud Firestore. Second, run the gcloud firestore import command. Third, monitor the import operation.

Answer

First, run the gcloud firestore import command. Second, verify the imported data in Cloud Firestore. Third, monitor the import operation.

Question 3

Match each Google Cloud tool to its purpose in database management.

Accepted Answer

Cloud SQL: Managed relational database service for MySQL, PostgreSQL, SQL Server. Cloud SQL, Cloud Spanner, and BigQuery are core Google Cloud database tools. Cloud SQL is for managed relational databases, Cloud Spanner for globally distributed relational databases, and BigQuery for analytics. Distractors confuse Cloud SQL with NoSQL services and Cloud Spanner with caching services.

Answer

Cloud SQL: Fully managed NoSQL database for real-time data

Answer

Cloud Spanner: In-memory data store for caching

Question 4

Arrange the steps to create and connect to a Cloud SQL for PostgreSQL instance using the gcloud command-line tool.

Accepted Answer

Create Cloud SQL instance, then set the password, then configure network access, then connect via psql.. After creating the instance, you set the password, configure network access, then connect via psql.

Answer

Set the password, then create Cloud SQL instance, then configure network access, then connect via psql.

Answer

Create Cloud SQL instance, then configure network access, then set the password, then connect via psql.

Answer

Create Cloud SQL instance, then connect via psql, then set the password, then configure network access.

Question 5

A company uses BigQuery for real-time BI. They have a table with streaming inserts. Analysts run queries that need to see data within seconds. However, they notice that streaming data appears with a delay of up to 2 minutes. What is the most likely reason?

Accepted Answer

The streaming buffer's flush interval is set to 2 minutes.. BigQuery's streaming buffer has a default flush interval of up to 90 seconds, but it can be configured. When the flush interval is set to 2 minutes, data written via streaming inserts remains in the buffer for that duration before being committed to the table, causing a delay of up to 2 minutes before it becomes visible to queries. This matches the symptom described in the question.

Answer

The query uses cached results.

Answer

The table is partitioned by hour.

Answer

The table has a clustering key.

Question 6

A company needs to store petabytes of time-series IoT sensor data and query it with single-digit millisecond latency at millions of reads per second. The data has a simple key-value structure with timestamps. Which Google Cloud database is MOST appropriate?

Accepted Answer

Cloud Bigtable. Cloud Bigtable is designed for exactly this use case — petabyte-scale, low-latency (single-digit ms), high-throughput NoSQL storage for time-series, IoT, and financial data. It scales horizontally by adding nodes. BigQuery is optimised for analytics (seconds-to-minutes latency), Cloud SQL is for OLTP (limited to tens of thousands of QPS), and Firestore is for document data with hierarchical structure.

Answer

BigQuery

Answer

Cloud Spanner

Answer

Firestore

Question 7

A company wants to enforce that only approved images from Artifact Registry can be deployed to their GKE clusters. They also want to ensure that images are scanned for vulnerabilities. Which TWO services should they use together?

Accepted Answer

Binary Authorization. Binary Authorization enforces deployment policies based on attestations; Container Analysis scans images for vulnerabilities. Artifact Registry stores images; Cloud Build builds them; IAM controls access.

Answer

Cloud IAM

Answer

Cloud Build

Answer

Artifact Registry

Question 8

A healthcare company uses Cloud SQL for PostgreSQL and needs to meet a disaster recovery requirement of RPO = 1 hour and RTO = 2 hours for a cross-region failover. They currently have a cross-region read replica in another region. Which additional action should they take to meet the RPO consistently?

Accepted Answer

Set up monitoring and alerting on the replication lag metric. Cross-region read replicas have asynchronous replication lag, which can vary. To ensure that the RPO is bounded to 1 hour, the company must monitor the replication lag and alert if it exceeds 1 hour. They can also increase the replica's resources to reduce lag, but monitoring is essential to guarantee the RPO.

Answer

Configure the read replica to use synchronous replication

Answer

Increase the replica's storage capacity

Answer

Enable point-in-time recovery on the primary instance

Question 9

A company wants to implement a disaster recovery plan for their AlloyDB database. They need automatic failover with minimal data loss and RTO under 30 seconds. Which configuration should they use?

Accepted Answer

Enable high availability (HA) on the AlloyDB cluster, which provisions a standby in a different zone.. AlloyDB provides automatic failover within 30 seconds when you enable high availability (primary + standby). This is zone-redundant within the same region.

Answer

Configure a cross-region read replica and promote it manually during a disaster.

Answer

Deploy AlloyDB in a single zone without HA.

Answer

Use AlloyDB with multiple read pools and a custom failover script.

Question 10

A company runs an e-commerce platform on Cloud Spanner multi-region (nam6). They experience a regional failure affecting the leader region. After failover, they observe increased write latency. What is the most likely cause?

Accepted Answer

The new leader region is geographically farther from the application instances.. In a multi-region Spanner configuration, the leader region handles write coordination. After failover, a new leader is elected in a different region, which may be farther from the majority of clients, increasing write latency if clients are not geographically distributed.

Answer

The new leader region has fewer replicas.

Answer

The instance is now running in read-only mode.

Answer

The failover caused data loss, requiring recovery.

Question 11

A company uses Cloud SQL for MySQL with a 1-hour RPO and 2-hour RTO. They currently rely on automated daily backups. To improve DR capabilities, they want to reduce RPO to 5 minutes while keeping costs low. Which action should they take?

Accepted Answer

Enable point-in-time recovery (PITR) with a binary log retention of 5 minutes.. Enabling point-in-time recovery (PITR) on Cloud SQL allows restoring to any point in time within the backup retention period, reducing RPO from 24 hours to seconds (limited to binary log retention).

Answer

Increase backup frequency to every hour.

Answer

Create a cross-region read replica.

Answer

Deploy Cloud SQL HA with a standby in another zone.

Question 12

A company runs a global application on Cloud Spanner with a multi-region configuration. They need to test their DR procedures without impacting production. Which THREE actions should they perform? (Choose 3)

Accepted Answer

Simulate a zone failure by modifying IAM permissions to restrict access to replicas in a zone.. Non-destructive tests include creating a backup and restoring it to a separate instance for validation, simulating a zone failure by restricting replica access, and performing regular failover drills via backup/restore to test RTO.

Answer

Delete the production instance and recreate it from a backup.

Answer

Promote a read replica to a writable instance in a different region.

Question 13

A company uses Cloud Bigtable with replication across two regions. They want to implement a DR plan that minimizes RPO and RTO. Which TWO steps should they take? (Choose 2)

Accepted Answer

Configure multi-cluster routing with read-failover.. Using multi-cluster routing with read-failover ensures reads automatically switch to the secondary cluster when primary is unhealthy, minimizing RPO by directing writes to primary. Regularly testing failover validates the process and updates runbooks.

Answer

Enable automatic failover for writes in the Bigtable cluster configuration.

Answer

Set the replication routing policy to any-replica.

Answer

Set the replication routing policy to single-cluster with failover priority.

Question 14

A company is using BigQuery for BI and needs to reduce costs for a large historical dataset that is infrequently queried. Which approach should they take?

Accepted Answer

Partition by ingestion time and set expiration on partitions older than 90 days.. Partitioning by ingestion time allows BigQuery to automatically manage data lifecycle by setting partition expiration. This reduces storage costs for historical data that is infrequently queried, as partitions older than 90 days are deleted without manual intervention. This approach directly addresses the need to reduce costs for a large historical dataset while maintaining query performance on recent data.

Answer

Use materialized views for common aggregations.

Answer

Use clustered tables.

Answer

Use a view with a WHERE clause filtering recent data.

Question 15

An engineer needs to create a build trigger in Cloud Build that runs tests on every pull request to the 'develop' branch. They also want to prevent the build from running if the PR is from a forked repository. What should they do?

Accepted Answer

Use a Cloud Build filter to ignore fork PRs. Cloud Build triggers can be configured to ignore pull requests from forked repositories by setting the 'ignore pull request from forks' option in the trigger configuration.

Answer

Create a trigger with pull request event and branch pattern 'develop'

Answer

Use a separate repository for external contributions

Answer

Add a condition in cloudbuild.yaml to skip if fork

Question 16

An organization uses Cloud Build and wants to inject a secret API key into a build step without exposing it in the cloudbuild.yaml. Which approach should they use?

Accepted Answer

Use `secretEnv` to reference a Secret Manager secret. Cloud Build's `secretEnv` field allows you to reference a secret stored in Secret Manager and inject it as an environment variable into a build step. This approach ensures the secret value is never exposed in the `cloudbuild.yaml` file or build logs, as Cloud Build retrieves it securely at runtime using the Secret Manager API.

Answer

Store the key in a Cloud Build substitution variable

Answer

Pass the key via `args` with a substitution

Answer

Store the key in a Cloud Storage bucket and download it in the build

Question 17

A deployment pipeline uses Cloud Deploy with canary strategy targeting Cloud Run. The engineer wants to run a data migration job before the new revision receives traffic. How should they implement this?

Accepted Answer

Add a preDeploy hook in the delivery pipeline that runs a Cloud Run job. Cloud Deploy supports preDeploy hooks that run Cloud Run jobs before the deployment proceeds.

Answer

Add a postDeploy hook that runs the migration

Answer

Include a Cloud Build step before the deploy step

Answer

Use a startup command in the Cloud Run service

Question 18

A BI team is designing a BigQuery table for a sales dashboard that queries daily sales by product category and region. The dashboard often filters on a specific date range and a specific region. Which combination of partitioning and clustering should be used?

Accepted Answer

Partition by date, cluster by region. Partitioning by date (e.g., on a DATE or TIMESTAMP column) allows BigQuery to prune entire partitions when the dashboard filters on a specific date range, reducing the amount of data scanned. Clustering by region then sorts the data within each partition by region, enabling efficient block-level pruning when the dashboard filters on a specific region. This combination optimizes both the date range and region filters, which are the most common query patterns for this sales dashboard.

Answer

Partition by region, cluster by date

Answer

Use only clustering on date and region without partitioning

Answer

Partition by month, cluster by date

Question 19

A company has a Cloud SQL instance with a 500 GB database. They need to perform a major version upgrade from MySQL 5.7 to 8.0 with minimal downtime. Which strategy should they use?

Accepted Answer

Create a read replica with new version, then promote. Creating a read replica with the new MySQL version and then promoting it minimizes downtime because replication keeps the replica synchronized with the primary until promotion. This approach avoids the lengthy export/import process and reduces the risk of data loss or extended unavailability.

Answer

Export and import the database

Answer

Use in-place upgrade via gcloud command

Answer

Upgrade during maintenance window

Question 20

A company has a Spanner instance with 5 nodes serving a global application. They receive alerts that write latency has increased significantly during business hours in the Asia-Pacific region. The team confirms that no application changes have been made. What is the most likely cause and recommended action?

Accepted Answer

Writes are hitting a hot spot due to monotonically increasing keys; consider using a hash prefix or bit-reversed key. Monotonically increasing keys (e.g., timestamps or auto-increment IDs) cause all new writes to target the same tablet leader in Spanner, creating a hot spot. This increases write latency because the single node becomes a bottleneck, especially during peak business hours in the Asia-Pacific region. Using a hash prefix or bit-reversed key distributes writes evenly across nodes, resolving the contention.

Answer

CPU utilization is above 70%; enable Spanner fine-grained access control

Answer

Set up interleaved indexes to speed up writes

Answer

The instance is under-provisioned; increase the number of nodes