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Google Professional-Data-Engineer Online Access

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Total 383 questions
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Google Professional Data Engineer Exam Questions and Answers

Question 25

Your company uses a proprietary system to send inventory data every 6 hours to a data ingestion service in the cloud. Transmitted data includes a payload of several fields and the timestamp of the transmission. If there are any concerns about a transmission, the system re-transmits the data. How should you deduplicate the data most efficiency?

Options:

A.

Assign global unique identifiers (GUID) to each data entry.

B.

Compute the hash value of each data entry, and compare it with all historical data.

C.

Store each data entry as the primary key in a separate database and apply an index.

D.

Maintain a database table to store the hash value and other metadata for each data entry.

Question 26

Your company is migrating their 30-node Apache Hadoop cluster to the cloud. They want to re-use Hadoop jobs they have already created and minimize the management of the cluster as much as possible. They also want to be able to persist data beyond the life of the cluster. What should you do?

Options:

A.

Create a Google Cloud Dataflow job to process the data.

B.

Create a Google Cloud Dataproc cluster that uses persistent disks for HDFS.

C.

Create a Hadoop cluster on Google Compute Engine that uses persistent disks.

D.

Create a Cloud Dataproc cluster that uses the Google Cloud Storage connector.

E.

Create a Hadoop cluster on Google Compute Engine that uses Local SSD disks.

Question 27

You designed a database for patient records as a pilot project to cover a few hundred patients in three clinics. Your design used a single database table to represent all patients and their visits, and you used self-joins to generate reports. The server resource utilization was at 50%. Since then, the scope of the project has expanded. The database must now store 100 times more patientrecords. You can no longer run the reports, because they either take too long or they encounter errors with insufficient compute resources. How should you adjust the database design?

Options:

A.

Add capacity (memory and disk space) to the database server by the order of 200.

B.

Shard the tables into smaller ones based on date ranges, and only generate reports with prespecified date ranges.

C.

Normalize the master patient-record table into the patient table and the visits table, and create other necessary tables to avoid self-join.

D.

Partition the table into smaller tables, with one for each clinic. Run queries against the smaller table pairs, and use unions for consolidated reports.

Question 28

You are deploying 10,000 new Internet of Things devices to collect temperature data in your warehouses globally. You need to process, store and analyze these very large datasets in real time. What should you do?

Options:

A.

Send the data to Google Cloud Datastore and then export to BigQuery.

B.

Send the data to Google Cloud Pub/Sub, stream Cloud Pub/Sub to Google Cloud Dataflow, and store the data in Google BigQuery.

C.

Send the data to Cloud Storage and then spin up an Apache Hadoop cluster as needed in Google Cloud Dataproc whenever analysis is required.

D.

Export logs in batch to Google Cloud Storage and then spin up a Google Cloud SQL instance, import the data from Cloud Storage, and run an analysis as needed.

Page: 7 / 20
Total 383 questions
Get Professional-Data-Engineer Full Access Download Professional-Data-Engineer PDF