Professional-Data-Engineer Google Exam Questions and Free Practice Test

Question 37

- (Exam Topic 5)
If you're running a performance test that depends upon Cloud Bigtable, all the choices except one below are recommended steps. Which is NOT a recommended step to follow?

A. Do not use a production instance.

B. Run your test for at least 10 minutes.

C. Before you test, run a heavy pre-test for several minutes.

D. Use at least 300 GB of data.

Correct Answer:A
If you're running a performance test that depends upon Cloud Bigtable, be sure to follow these steps as you plan and execute your test:
Use a production instance. A development instance will not give you an accurate sense of how a production instance performs under load.
Use at least 300 GB of data. Cloud Bigtable performs best with 1 TB or more of data. However, 300 GB of data is enough to provide reasonable results in a performance test on a 3-node cluster. On larger clusters, use 100 GB of data per node.
Before you test, run a heavy pre-test for several minutes. This step gives Cloud Bigtable a chance to balance data across your nodes based on the access patterns it observes.
Run your test for at least 10 minutes. This step lets Cloud Bigtable further optimize your data, and it helps ensure that you will test reads from disk as well as cached reads from memory.
Reference: https://cloud.google.com/bigtable/docs/performance

Question 38

- (Exam Topic 6)
You have a petabyte of analytics data and need to design a storage and processing platform for it. You must be able to perform data warehouse-style analytics on the data in Google Cloud and expose the dataset as files for batch analysis tools in other cloud providers. What should you do?

A. Store and process the entire dataset in BigQuery.

B. Store and process the entire dataset in Cloud Bigtable.

C. Store the full dataset in BigQuery, and store a compressed copy of the data in a Cloud Storage bucket.

D. Store the warm data as files in Cloud Storage, and store the active data in BigQuer

E. Keep this ratio as 80% warm and 20

Correct Answer:C

Question 39

- (Exam Topic 6)
You need to move 2 PB of historical data from an on-premises storage appliance to Cloud Storage within six months, and your outbound network capacity is constrained to 20 Mb/sec. How should you migrate this data to Cloud Storage?

A. Use Transfer Appliance to copy the data to Cloud Storage

B. Use gsutil cp –J to compress the content being uploaded to Cloud Storage

C. Create a private URL for the historical data, and then use Storage Transfer Service to copy the data to Cloud Storage

D. Use trickle or ionice along with gsutil cp to limit the amount of bandwidth gsutil utilizes to less than 20 Mb/sec so it does not interfere with the production traffic

Correct Answer:A

Question 40

- (Exam Topic 6)
You are working on a niche product in the image recognition domain. Your team has developed a model that is dominated by custom C++ TensorFlow ops your team has implemented. These ops are used inside your main training loop and are performing bulky matrix multiplications. It currently takes up to several days to train a model. You want to decrease this time significantly and keep the cost low by using an accelerator on Google Cloud. What should you do?

A. Use Cloud TPUs without any additional adjustment to your code.

B. Use Cloud TPUs after implementing GPU kernel support for your customs ops.

C. Use Cloud GPUs after implementing GPU kernel support for your customs ops.

D. Stay on CPUs, and increase the size of the cluster you’re training your model on.

Correct Answer:B

Question 41

- (Exam Topic 6)
You work on a regression problem in a natural language processing domain, and you have 100M labeled exmaples in your dataset. You have randomly shuffled your data and split your dataset into train and test samples (in a 90/10 ratio). After you trained the neural network and evaluated your model on a test set, you discover that the root-mean-squared error (RMSE) of your model is twice as high on the train set as on the test set. How should you improve the performance of your model?

A. Increase the share of the test sample in the train-test split.

B. Try to collect more data and increase the size of your dataset.

C. Try out regularization techniques (e.g., dropout of batch normalization) to avoid overfitting.

D. Increase the complexity of your model by, e.g., introducing an additional layer or increase sizing the size of vocabularies or n-grams used.

Correct Answer:D

Question 42

- (Exam Topic 6)
Your team is responsible for developing and maintaining ETLs in your company. One of your Dataflow jobs is failing because of some errors in the input data, and you need to improve reliability of the pipeline (incl. being able to reprocess all failing data).
What should you do?

A. Add a filtering step to skip these types of errors in the future, extract erroneous rows from logs.

B. Add a try… catch block to your DoFn that transforms the data, extract erroneous rows from logs.

C. Add a try… catch block to your DoFn that transforms the data, write erroneous rows to PubSub directly from the DoFn.

D. Add a try… catch block to your DoFn that transforms the data, use a sideOutput to create a PCollectionthat can be stored to PubSub later.

Correct Answer:C

START Professional-Data-Engineer EXAM