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Google Google Cloud Certified Professional-Data-Engineer New Questions

Google Professional Data Engineer Exam Questions and Answers

Question 53

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

Options:

A.

Threading

B.

Serialization

C.

Dropout Methods

D.

Dimensionality Reduction

Question 54

You want to use Google Stackdriver Logging to monitor Google BigQuery usage. You need an instant notification to be sent to your monitoring tool when new data is appended to a certain table using an insert job, but you do not want to receive notifications for other tables. What should you do?

Options:

A.

Make a call to the Stackdriver API to list all logs, and apply an advanced filter.

B.

In the Stackdriver logging admin interface, and enable a log sink export to BigQuery.

C.

In the Stackdriver logging admin interface, enable a log sink export to Google Cloud Pub/Sub, and subscribe to the topic from your monitoring tool.

D.

Using the Stackdriver API, create a project sink with advanced log filter to export to Pub/Sub, and subscribe to the topic from your monitoring tool.

Question 55

Your company’s on-premises Apache Hadoop servers are approaching end-of-life, and IT has decided to migrate the cluster to Google Cloud Dataproc. A like-for-like migration of the cluster would require 50 TB of Google Persistent Disk per node. The CIO is concerned about the cost of using that much block storage. You want to minimize the storage cost of the migration. What should you do?

Options:

A.

Put the data into Google Cloud Storage.

B.

Use preemptible virtual machines (VMs) for the Cloud Dataproc cluster.

C.

Tune the Cloud Dataproc cluster so that there is just enough disk for all data.

D.

Migrate some of the cold data into Google Cloud Storage, and keep only the hot data in Persistent Disk.

Question 56

Your software uses a simple JSON format for all messages. These messages are published to Google Cloud Pub/Sub, then processed with Google Cloud Dataflow to create a real-time dashboard for the CFO. During testing, you notice that some messages are missing in thedashboard. You check the logs, and all messages are being published to Cloud Pub/Sub successfully. What should you do next?

Options:

A.

Check the dashboard application to see if it is not displaying correctly.

B.

Run a fixed dataset through the Cloud Dataflow pipeline and analyze the output.

C.

Use Google Stackdriver Monitoring on Cloud Pub/Sub to find the missing messages.

D.

Switch Cloud Dataflow to pull messages from Cloud Pub/Sub instead of Cloud Pub/Sub pushing messages to Cloud Dataflow.