最新的Google Cloud Certified認證 Professional-Data-Engineer考試題庫

問題1

Your infrastructure includes a set of YouTube channels. You have been tasked with creating a process for sending the YouTube channel data to Google Cloud for analysis. You want to design a solution that allows your world-wide marketing teams to perform ANSI SQL and other types of analysis on up-to-date YouTube channels log data. How should you set up the log data transfer into Google Cloud?

A. Use Storage Transfer Service to transfer the offsite backup files to a Cloud Storage Multi- Regional storage bucket as a final destination.

B. Use BigQuery Data Transfer Service to transfer the offsite backup files to a Cloud Storage Regional storage bucket as a final destination.

C. Use BigQuery Data Transfer Service to transfer the offsite backup files to a Cloud Storage Multi- Regional storage bucket as a final destination.

D. Use Storage Transfer Service to transfer the offsite backup files to a Cloud Storage Regional bucket as a final destination.

正確答案: A

說明：（僅 VCESoft 成員可見）

問題2

You are planning to use Google's Dataflow SDK to analyze customer data such as displayed below. Your project requirement is to extract only the customer name from the data source and then write to an output PCollection.
Tom, 555 X street
Tim, 553 Y street
Sam, 111 Z street
Which operation is best suited for the above data processing requirement?

A. Data extraction

B. Sink API

C. ParDo

D. Source API

正確答案: C

說明：（僅 VCESoft 成員可見）

問題3

Your company is planning to migrate a large on-premises data warehouse to BigQuery. The data is currently stored in a proprietary, vendor-specific format. You need to perform a batch migration of this data to BigQuery. What should you do?

A. Use Datastream to replicate the data in real time.

B. Use the BigQuery Data Transfer Service.

C. Use the bqcommand-line tool to load the data directly from the on-premises data warehouse.

D. Export the data to CSV files, upload the files to Cloud Storage, then load the files into BigQuery.

正確答案: D

說明：（僅 VCESoft 成員可見）

問題4

Each analytics team in your organization is running BigQuery jobs in their own projects. You want to enable each team to monitor slot usage within their projects. What should you do?

A. Create a Stackdriver Monitoring dashboard based on the BigQuery metric slots/ allocated_for_project

B. Create a log export for each project, capture the BigQuery job execution logs, create a custom metric based on the totalSlotMs, and create a Stackdriver Monitoring dashboard based on the custom metric

C. Create a Stackdriver Monitoring dashboard based on the BigQuery metric query/scanned_bytes

D. Create an aggregated log export at the organization level, capture the BigQuery job execution logs, create a custom metric based on the totalSlotMs, and create a Stackdriver Monitoring dashboard based on the custom metric

正確答案: A

說明：（僅 VCESoft 成員可見）

問題5

Which of the following is NOT a valid use case to select HDD (hard disk drives) as the storage for Google Cloud Bigtable?

A. You will not use the data to back a user-facing or latency-sensitive application.

B. You expect to store at least 10 TB of data.

C. You will mostly run batch workloads with scans and writes, rather than frequently executing random reads of a small number of rows.

D. You need to integrate with Google BigQuery.

正確答案: D

說明：（僅 VCESoft 成員可見）

問題6

You analyze user clickstream data to personalize content recommendations. The data arrives continuously and needs to be processed with low latency, including transformations such as sessionization (grouping clicks by user within a time window) and aggregation of user activity.
You need to identify a scalable solution to handle millions of events each second and be resilient to late-arriving data. What should you do?

A. Use Cloud Storage for ingestion, Dataproc with Apache Spark for batch processing, and BigQuery for storage and analytics.

B. Use Pub/Sub for ingestion, Dataflow with Apache Beam for processing, and BigQuery for storage and analytics.

C. Use Cloud Data Fusion for ingestion and transformation, and Cloud SQL for storage and analytics.

D. Use Firebase Realtime Database for ingestion and storage, and Cloud Run functions for processing and analytics.

正確答案: B

說明：（僅 VCESoft 成員可見）

問題7

You are designing a real-time system for a ride hailing app that identifies areas with high demand for rides to effectively reroute available drivers to meet the demand. The system ingests data from multiple sources to Pub/Sub, processes the data, and stores the results for visualization and analysis in real-time dashboards. The data sources include driver location updates every 5 seconds and app-based booking events from riders. The data processing involves real-time aggregation of supply and demand data for the last 30 seconds, every 2 seconds, and storing the results in a low-latency system for visualization. What should you do?

A. Group the data by using a session window in a Dataflow pipeline, and write the aggregated data to BigQuery.

B. Group the data by using a tumbling window in a Dataflow pipeline, and write the aggregated data to Memorystore.

C. Group the data by using a hopping window in a Dataflow pipeline, and write the aggregated data to Memorystore.

D. Group the data by using a hopping window in a Dataflow pipeline, and write the aggregated data to BigQuery.

正確答案: C

問題8

Your company is migrating their 30-node Apache Hadoop cluster to the cloud. They want to re- use Hadoop jobs they have already created and minimize the management of the cluster as much as possible. They also want to be able to persist data beyond the life of the cluster. What should you do?

A. Create a Hadoop cluster on Google Compute Engine that uses Local SSD disks.

B. Create a Google Cloud Dataproc cluster that uses persistent disks for HDFS.

C. Create a Google Cloud Dataflow job to process the data.

D. Create a Hadoop cluster on Google Compute Engine that uses persistent disks.

E. Create a Cloud Dataproc cluster that uses the Google Cloud Storage connector.

正確答案: E

說明：（僅 VCESoft 成員可見）

問題9

Your financial services company is moving to cloud technology and wants to store 50 TB of financial time- series data in the cloud. This data is updated frequently and new data will be streaming in all the time. Your company also wants to move their existing Apache Hadoop jobs to the cloud to get insights into this data. Which product should they use to store the data?

A. Cloud Bigtable

B. Google Cloud Datastore

C. Google BigQuery

D. Google Cloud Storage

正確答案: A

說明：（僅 VCESoft 成員可見）

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