Free Access Google.Professional-Data-Engineer.v2025-03-18.q108 Practice Test (Page 18)

Question 81

You are a head of BI at a large enterprise company with multiple business units that each have different priorities and budgets. You use on-demand pricing for BigQuery with a quota of 2K concurrent on-demand slots per project. Users at your organization sometimes don't get slots to execute their query and you need to correct this. You'd like to avoid introducing new projects to your account.
What should you do?

A.Convert your batch BQ queries into interactive BQ queries.

B.Create an additional project to overcome the 2K on-demand per-project quota.

C.Switch to flat-rate pricing and establish a hierarchical priority model for your projects.

D.Increase the amount of concurrent slots per project at the Quotas page at the Cloud Console.

Question 82

You are running a pipeline in Cloud Dataflow that receives messages from a Cloud Pub/Sub topic and writes the results to a BigQuery dataset in the EU. Currently, your pipeline is located in europe-west4 and has a maximum of 3 workers, instance type n1-standard-1. You notice that during peak periods, your pipeline is struggling to process records in a timely fashion, when all 3 workers are at maximum CPU utilization. Which two actions can you take to increase performance of your pipeline? (Choose two.)

A.Increase the number of max workers

B.Create a temporary table in Cloud Spanner that will act as a buffer for new data. Create a new step in your pipeline to write to this table first, and then create a new pipeline to write from Cloud Spanner to BigQuery

C.Use a larger instance type for your Cloud Dataflow workers

D.Change the zone of your Cloud Dataflow pipeline to run in us-central1

E.Create a temporary table in Cloud Bigtable that will act as a buffer for new data. Create a new step in your pipeline to write to this table first, and then create a new pipeline to write from Cloud Bigtable to BigQuery

Question 83

You have a requirement to insert minute-resolution data from 50,000 sensors into a BigQuery table. You expect significant growth in data volume and need the data to be available within 1 minute of ingestion for real-time analysis of aggregated trends. What should you do?

A.Use a Cloud Dataflow pipeline to stream data into the BigQuery table.

B.Use the INSERT statement to insert a batch of data every 60 seconds.

C.Use the MERGE statement to apply updates in batch every 60 seconds.

D.Use bq load to load a batch of sensor data every 60 seconds.

Question 84

You are building an ELT solution in BigQuery by using Dataform. You need to perform uniqueness and null value checks on your final tables. What should you do to efficiently integrate these checks into your pipeline?

A.Build Dataform assertions into your code

B.Write a Spark-based stored procedure.

C.Build BigQuery user-defined functions (UDFs).

D.Create Dataplex data quality tasks.

Question 85

When you store data in Cloud Bigtable, what is the recommended minimum amount of stored data?

A.500 TB

B.1 GB

C.1 TB

D.500 GB

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