PDE Practice Test 21 — 15 Questions

Question 1

A company wants to build an event-driven application that processes images uploaded to a Cloud Storage bucket. The processing takes up to 10 minutes per image and should be automatically triggered. Which compute option should they use?

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

Accepted Answer

Cloud Run on Eventarc trigger. Cloud Functions have a 9-minute timeout; Cloud Run can handle up to 60 minutes and is triggered by Eventarc for GCS events.

Answer

Cloud Functions (2nd gen) with Eventarc trigger

Answer

App Engine

Answer

Cloud Functions (1st gen)

Question 2

A company is migrating on-premises Apache Kafka workloads to Google Cloud. They want to minimize changes to existing producer and consumer applications while leveraging managed services. Which TWO services should they consider? (Choose 2)

Accepted Answer

Dataproc with Apache Kafka. Kafka on Dataproc provides a managed Kafka cluster that is fully compatible, minimizing application changes. Confluent Cloud on Google Cloud can be used but is not a Google-managed service; however, it is a viable partner solution. Pub/Sub is not Kafka API-compatible. Dataflow is not a replacement for Kafka. BigQuery is a data warehouse, not a streaming broker.

Answer

BigQuery

Answer

Cloud Pub/Sub

Answer

Cloud Dataflow

Question 3

A company wants to move data from an on-premises MySQL database to BigQuery for analytics. They need to capture all changes (inserts, updates, deletes) in near real-time and also perform an initial historical load. Which approach meets these requirements with minimal operational overhead?

Accepted Answer

Use Datastream to backfill historical data and then stream CDC changes to BigQuery. Datastream can perform a backfill of historical data and then stream CDC changes from MySQL to BigQuery in near real-time, providing a single service for both tasks.

Answer

Use a Dataflow pipeline with a JDBC source to read the entire table periodically

Answer

Use a one-time export to CSV and load into BigQuery, then set up a cron job to export incremental changes

Answer

Use Cloud SQL as an intermediary and enable binary logging, then stream to Pub/Sub via a custom connector

Question 4

A company uses Dataflow to process data with Apache Beam in Python. The pipeline reads from Pub/Sub, applies a ParDo that calls an external API for enrichment, and writes to BigQuery. The external API has rate limits and occasionally fails. To improve reliability, which THREE strategies should be implemented? (Choose 3)

Accepted Answer

Batch multiple requests to the external API using a side input. Retry logic with exponential backoff, a dead letter queue for failed records, and batching requests reduce API pressure and handle failures gracefully.

Answer

Switch from Python to Java SDK for better performance

Answer

Increase the number of Dataflow workers to reduce load per worker

Question 5

A company wants to ingest data from an on-premises Oracle database into BigQuery in near real-time with minimal latency. The database has a high volume of inserts and updates. Which service should they use?

Accepted Answer

Datastream. Datastream is designed for CDC from Oracle and other sources to BigQuery or GCS in near real-time.

Answer

BigQuery Data Transfer Service

Answer

Pub/Sub

Answer

Storage Transfer Service

Question 6

A data team needs to transfer 200 TB of data from Amazon S3 to GCS. The transfer must be incremental, and they need to monitor the transfer progress. Which THREE components should they use?

Accepted Answer

Cloud Monitoring. Storage Transfer Service (STS) can transfer from S3 to GCS with incremental sync. Cloud Monitoring tracks progress. Service account for permissions.

Answer

Dataflow

Answer

Transfer Appliance

Question 7

A company wants to migrate their on-premises Teradata data warehouse to BigQuery. They need an automated, one-time transfer of historical data (10 TB) and ongoing incremental daily syncs. Which Google Cloud service should they use?

Accepted Answer

BigQuery Data Transfer Service for Teradata. BigQuery Data Transfer Service supports Teradata as a source for both one-time and scheduled transfers. Storage Transfer Service is for file-based transfers. Datastream is for CDC, not Teradata. Dataflow could be custom-built but Data Transfer Service is purpose-built for this scenario.

Answer

Dataflow custom pipeline

Answer

Storage Transfer Service

Answer

Datastream

Question 8

You are using Dataproc to run a Spark job that reads data from Cloud Storage, performs aggregations, and writes results back to Cloud Storage. The job is failing with out-of-memory errors on the shuffle. Which optimization should you apply?

Accepted Answer

Increase spark.sql.shuffle.partitions. For shuffle-heavy operations, increasing the number of partitions reduces the size of each partition, reducing memory pressure. Alternatively, using DataFrames with optimized serialization (e.g., Kryo) helps.

Answer

Use RDDs instead of DataFrames

Answer

Increase spark.executor.memory

Answer

Decrease the number of executors

Question 9

A company wants to use Eventarc to trigger a Cloud Run service when new objects are created in a GCS bucket. They also need to filter events for a specific bucket and object prefix. Which THREE resources must exist or be created?

Accepted Answer

Cloud Storage bucket. Eventarc trigger, Cloud Run service, and the GCS bucket. The trigger references the bucket and prefix.

Answer

Pub/Sub topic

Answer

Cloud Scheduler job

Question 10

A data engineer needs to load 10 GB of CSV files from Amazon S3 into BigQuery on a daily basis. The files arrive in a specific S3 bucket at 3 AM UTC each day. Which service should be used to automate this transfer?

Accepted Answer

BigQuery Data Transfer Service. BigQuery Data Transfer Service supports scheduled transfers from Amazon S3 directly to BigQuery, making it the appropriate choice for this recurring batch load.

Answer

Cloud Storage Transfer Service

Answer

Dataflow with Pub/Sub

Answer

Transfer Appliance

Question 11

A company wants to use dbt to transform data in BigQuery. Their source data is loaded daily into staging tables. They need to run dbt transformations on a schedule and only process tables that have changed. Which dbt feature should they use?

Accepted Answer

dbt incremental models. dbt incremental models allow processing only new or changed records based on a configured timestamp or unique key. dbt snapshots capture historical changes. dbt seeds load CSV files. dbt sources are for configuration, not incremental processing.

Answer

dbt snapshots

Answer

dbt seeds

Answer

dbt sources

Question 12

A company needs to continuously synchronize customer data changes from an on-premises Oracle database to BigQuery for near-real-time analytics. The Oracle database has Change Data Capture (CDC) enabled. Which Google Cloud service should be used to stream these changes with minimal latency and schema evolution support?

Accepted Answer

Use Datastream to stream CDC changes from Oracle to BigQuery. Datastream is designed to stream CDC from Oracle (and MySQL/PostgreSQL) directly to BigQuery or GCS, supporting schema evolution and low-latency replication.

Answer

Deploy a Dataflow pipeline with a JDBC source and Pub/Sub

Answer

Use Cloud SQL with a read replica and enable binary logging

Answer

Use Transfer Appliance to copy Oracle data periodically

Question 13

An organization needs to trigger a Cloud Run service whenever a new file is uploaded to a specific Cloud Storage bucket. Which service should they use to set up this event-driven architecture?

Accepted Answer

Eventarc with a trigger for Cloud Storage events. Eventarc can capture Cloud Storage events (e.g., OBJECT_FINALIZE) and route them to Cloud Run, Cloud Functions, or Workflows. It supports CloudEvents standard.

Answer

Pub/Sub notifications on the bucket with a push subscription to Cloud Run

Answer

Cloud Scheduler calling Cloud Run on a schedule

Answer

Cloud Functions with a GCS trigger

Question 14

A company uses Google Ads and wants to automatically load their advertising data into BigQuery daily. They also need to transform the data with SQL and schedule a recurring query. Which combination of services meets these requirements with minimal operational overhead?

Accepted Answer

BigQuery Data Transfer Service for Google Ads and scheduled queries. BigQuery Data Transfer Service can automatically load Google Ads data; scheduled queries handle transformation.

Answer

Cloud Functions triggered by Cloud Scheduler to call Google Ads API and load into BigQuery

Answer

Cloud Composer to extract Google Ads API and Dataflow to transform

Answer

Storage Transfer Service to move CSV files to GCS, then load into BigQuery

Question 15

A large enterprise is migrating its data warehouse from Teradata to BigQuery. They need to transfer historical data (100 TB) and set up ongoing daily incremental loads. They also need to transform the data using dbt. Which THREE Google Cloud services should they use?

Accepted Answer

BigQuery Data Transfer Service for Teradata. BigQuery Data Transfer Service for Teradata handles both historical and incremental loads, dbt runs on BigQuery for transformations, and Cloud Composer can orchestrate the dbt runs on a schedule.

Answer

Datastream

Answer

Transfer Appliance