PDE Practice Test 4 — 10 Questions

Question 1

Drag and drop the steps to configure a VPC network with private Google access for on-premises connectivity using Cloud VPN into the correct order.

Question 2

Match each data pipeline term to its definition.

Question 3

Match each data lifecycle stage to its description.

Question 4

A company runs a batch ETL pipeline on Cloud Dataproc. During peak hours, the job takes longer than expected. The pipeline reads from Cloud Storage, transforms data, and writes to BigQuery. What is the most cost-effective way to improve performance without redesigning the pipeline?

Accepted Answer

Add a secondary worker group using preemptible VMs and increase the number of workers.. Adding a secondary worker group with preemptible VMs is the most cost-effective way to improve performance because it allows you to scale out the cluster horizontally with compute instances that are significantly cheaper (up to 80% discount) than regular VMs. This directly addresses the bottleneck of processing capacity during peak hours without requiring any pipeline redesign, as Cloud Dataproc can automatically distribute work across additional workers.

Answer

Enable local SSDs on all worker nodes.

Answer

Increase the master node's machine type to n1-highmem-32.

Answer

Use Cloud Composer to schedule the job with a higher priority.

Question 5

Match each data storage term to its characteristic.

Question 6

Match each data encryption concept to its description.

Question 7

A financial services firm processes sensitive transactions using Cloud Dataflow. The pipeline reads from Pub/Sub, performs stateful processing (e.g., fraud detection), and writes to Cloud Spanner. Compliance requires exactly-once processing semantics. Which configuration ensures exactly-once processing?

Accepted Answer

Set Dataflow pipeline to exactly-once mode and design Spanner writes to be idempotent.. Option C is correct because exactly-once processing in a Dataflow pipeline requires the pipeline itself to be set to exactly-once mode (which uses consistent snapshots and transactional sinks) and the output writes to Spanner to be idempotent. This combination ensures that even if a record is reprocessed due to failures, the final state in Spanner remains consistent, satisfying compliance requirements.

Answer

Configure Pub/Sub to use exactly-once delivery mode.

Answer

Use Pub/Sub with at-least-once delivery and Dataflow with at-least-once processing mode.

Answer

Enable Dataflow's streaming engine and use Spanner's built-in retry logic.

Question 8

A healthcare company streams patient monitoring data to Cloud Pub/Sub. A Dataflow pipeline reads the stream, enriches with patient records from BigQuery, and writes to Bigtable for real-time queries. The BigQuery lookup is slow and causes pipeline lag. What is the best approach to improve performance?

Accepted Answer

Use a side input from a BigQuery query with a global window and periodic refresh.. Option D is correct because using a side input from BigQuery with a global window and periodic refresh allows the Dataflow pipeline to cache the patient records in memory across all workers, avoiding per-element slow lookups. This pattern leverages Beam's side input semantics to broadcast a relatively static lookup table, significantly reducing latency compared to synchronous BigQuery queries for each incoming event.

Answer

Increase the number of Dataflow workers and use vertical scaling.

Answer

Use BigQuery's streaming read API in the pipeline.

Answer

Pre-join the data in a batch pipeline and load into Bigtable.

Question 9

A media company ingests video files from partners via a REST API. Files are stored in Cloud Storage, and metadata is written to Firestore. A Cloud Function is triggered on object finalize to transcode video using Transcoder API. Sometimes, the function fails because the file is still being uploaded when triggered. How should this be fixed?

Accepted Answer

Use Cloud Pub/Sub notifications for Cloud Storage and trigger the function from the subscription.. Option D is correct because Cloud Storage object finalize notifications are sent only after the entire file has been written and committed. By using Pub/Sub notifications for Cloud Storage and triggering the Cloud Function from the subscription, you decouple the trigger from the upload process, ensuring the function only runs when the file is fully available. This eliminates the race condition where the function is triggered before the upload completes.

Answer

Implement a Cloud Composer workflow to poll for file existence.

Answer

Require partners to use resumable uploads.

Answer

Increase the Cloud Functions timeout to allow time for the upload to finish.

Question 10

A company uses Cloud Composer to orchestrate data pipelines. One DAG fails intermittently with the error: 'Task received SIGTERM signal.' The task runs a long-running Dataproc job. What is the most likely cause?

Accepted Answer

The Airflow task timed out due to the default execution timeout.. The default Airflow task execution timeout is 28 days in Cloud Composer, but individual tasks can have a shorter `execution_timeout` set in the DAG definition. When a long-running Dataproc job exceeds this timeout, Airflow sends a SIGTERM signal to the task to kill it, resulting in the observed error. This is the most likely cause because the error message directly indicates a forced termination by the Airflow scheduler, not an infrastructure or code failure.

Answer

The Dataproc cluster was preempted by Google Cloud.

Answer

The Dataproc job failed due to an error in the code.

Answer

The Cloud Composer environment ran out of disk space.