Google exams4sure pass Professional-data-engineer Exam Guide by Wesley q268 vce pdf

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Exam Name:	Google Professional Data Engineer Exam
Exam Code:	Professional-Data-Engineer Dumps
Vendor:	Google	Certification:	Google Cloud Certified
Questions:	376 Q&A's	Shared By:	wesley

Question 20

You need to choose a database for a new project that has the following requirements:

Fully managed

Able to automatically scale up

Transactionally consistent

Able to scale up to 6 TB

Able to be queried using SQL

Which database do you choose?

Options:

Cloud SQL

Cloud Bigtable

Cloud Spanner

Cloud Datastore

Discussion

Question 21

You have a data pipeline with a Cloud Dataflow job that aggregates and writes time series metrics to Cloud Bigtable. This data feeds a dashboard used by thousands of users across the organization. You need to support additional concurrent users and reduce the amount of time required to write the data. Which two actions should you take? (Choose two.)

Options:

Configure your Cloud Dataflow pipeline to use local execution

Increase the maximum number of Cloud Dataflow workers by setting maxNumWorkers in PipelineOptions

Increase the number of nodes in the Cloud Bigtable cluster

Modify your Cloud Dataflow pipeline to use the Flatten transform before writing to Cloud Bigtable

Modify your Cloud Dataflow pipeline to use the CoGroupByKey transform before writing to Cloud Bigtable

Discussion

Question 22

You are architecting a data transformation solution for BigQuery. Your developers are proficient with SOL and want to use the ELT development technique. In addition, your developers need an intuitive coding environment and the ability to manage SQL as code. You need to identify a solution for your developers to build these pipelines. What should you do?

Options:

Use Cloud Composer to load data and run SQL pipelines by using the BigQuery job operators.

Use Dataflow jobs to read data from Pub/Sub, transform the data, and load the data to BigQuery.

Use Dataform to build, manage, and schedule SQL pipelines.

Use Data Fusion to build and execute ETL pipelines

Discussion

Question 23

You have a data processing application that runs on Google Kubernetes Engine (GKE). Containers need to be launched with their latest available configurations from a container registry. Your GKE nodes need to have GPUs. local SSDs, and 8 Gbps bandwidth. You want to efficiently provision the data processing infrastructure and manage the deployment process. What should you do?

Options:

Use Compute Engi.no startup scriots to pull container Images, and use gloud commands to provision the infrastructure.

Use GKE to autoscale containers, and use gloud commands to provision the infrastructure.

Use Cloud Build to schedule a job using Terraform build to provision the infrastructure and launch with the most current container images.

Use Dataflow to provision the data pipeline, and use Cloud Scheduler to run the job.

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