Free Access Google.Professional-Data-Engineer.v2025-03-18.q108 Practice Test (Page 13)

Question 56

What are two of the benefits of using denormalized data structures in BigQuery?

A.Reduces the amount of data processed, reduces the amount of storage required

B.Increases query speed, makes queries simpler

C.Reduces the amount of storage required, increases query speed

D.Reduces the amount of data processed, increases query speed

Question 57

You are designing storage for two relational tables that are part of a 10-TB database on Google Cloud. You want to support transactions that scale horizontally. You also want to optimize data for range queries on nonkey columns. What should you do?

A.Use Cloud SQL for storage. Add secondary indexes to support query patterns.

B.Use Cloud Spanner for storage. Use Cloud Dataflow to transform data to support query patterns.

C.Use Cloud Spanner for storage. Add secondary indexes to support query patterns.

D.Use Cloud SQL for storage. Use Cloud Dataflow to transform data to support query patterns.

Question 58

Which of these sources can you not load data into BigQuery from?

A.File upload

B.Google Drive

C.Google Cloud Storage

D.Google Cloud SQL

Question 59

A.Use Cloud SQL for storage. Add secondary indexes to support query patterns.

B.Use Cloud SQL for storage. Use Cloud Dataflow to transform data to support query patterns.

C.Use Cloud Spanner for storage. Add secondary indexes to support query patterns.

D.Use Cloud Spanner for storage. Use Cloud Dataflow to transform data to support query patterns.

Question 60

You've migrated a Hadoop job from an on-prem cluster to dataproc and GCS. Your Spark job is a complicated analytical workload that consists of many shuffing operations and initial data are parquet files (on average 200-400 MB size each). You see some degradation in performance after the migration to Dataproc, so you'd like to optimize for it. You need to keep in mind that your organization is very cost- sensitive, so you'd like to continue using Dataproc on preemptibles (with 2 non-preemptible workers only) for this workload.
What should you do?

A.Increase the size of your parquet files to ensure them to be 1 GB minimum.

B.Switch to TFRecords formats (appr. 200MB per file) instead of parquet files.

C.Switch from HDDs to SSDs, copy initial data from GCS to HDFS, run the Spark job and copy results back to GCS.

D.Switch from HDDs to SSDs, override the preemptible VMs configuration to increase the boot disk size.

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Question 56

Question 57

Question 58

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Question 60

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