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Google Certified Professional Data Engineer Exam Sample Questions (Q350-Q355):

NEW QUESTION # 350
Which action can a Cloud Dataproc Viewer perform?

A. Submit a job.
B. Create a cluster.
C. Delete a cluster.
D. List the jobs.

Answer: D

Explanation:
A Cloud Dataproc Viewer is limited in its actions based on its role. A viewer can only list clusters, get cluster details, list jobs, get job details, list operations, and get operation details.
Reference:
https://cloud.google.com/dataproc/docs/concepts/iam#iam_roles_and_cloud_dataproc_operations
_summary

NEW QUESTION # 351
Which Java SDK class can you use to run your Dataflow programs locally?

A. MachineRunner
B. DirectPipelineRunner
C. LocalRunner
D. LocalPipelineRunner

Answer: B

Explanation:
DirectPipelineRunner allows you to execute operations in the pipeline directly, without any optimization.
Useful for small local execution and tests
Reference:
https://cloud.google.com/dataflow/java-sdk/JavaDoc/com/google/cloud/dataflow/sdk/runners/DirectPipelineRun

NEW QUESTION # 352
You want to process payment transactions in a point-of-sale application that will run on Google Cloud Platform. Your user base could grow exponentially, but you do not want to manage infrastructure scaling.
Which Google database service should you use?

A. Cloud Bigtable
B. BigQuery
C. Cloud SQL
D. Cloud Datastore

Answer: D

Explanation:
https://cloud.google.com/datastore/docs/concepts/overview

NEW QUESTION # 353
You've migrated a Hadoop job from an on-premises cluster to Dataproc and Good Storage. Your Spark job is a complex analytical workload fiat consists of many shuffling operations, and initial data are parquet toes (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. Your organization is very cost-sensitive so you'd Idee to continue using Dataproc on preemptibles (with 2 non-preemptibles workers only) for this workload. What should you do?

A. Switch from HODs to SSDs override the preemptible VMs configuration to increase the boot disk size
B. Switch to TFRecords format (appr 200 MB per We) instead of parquet files
C. Increase the see of your parquet files to ensure them to be 1 GB minimum
D. Switch from HDDs to SSDs. copy initial data from Cloud Storage to Hadoop Distributed File System (HDFS) run the Spark job and copy results back to Cloud Storage

Answer: A

NEW QUESTION # 354
Your company built a TensorFlow neural-network model with a large number of neurons and layers. The model fits well for the training dat
a. However, when tested against new data, it performs poorly. What method can you employ to address this?

A. Serialization
B. Threading
C. Dropout Methods
D. Dimensionality Reduction

Answer: C

Explanation:
Reference https://medium.com/mlreview/a-simple-deep-learning-model-for-stock-price-prediction-using-tensorflow-30505541d877

NEW QUESTION # 355
......

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