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[General] Professional-Data-Engineer Test Engine, Exam Professional-Data-Engineer Simulato

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【General】 Professional-Data-Engineer Test Engine, Exam Professional-Data-Engineer Simulato

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Google Certified Professional Data Engineer Exam Sample Questions (Q273-Q278):NEW QUESTION # 273
You are building a new data pipeline to share data between two different types of applications: jobs generators and job runners. Your solution must scale to accommodate increases in usage and must accommodate the addition of new applications without negatively affecting the performance of existing ones. What should you do?
  • A. Create an API using App Engine to receive and send messages to the applications
  • B. Use a Cloud Pub/Sub topic to publish jobs, and use subscriptions to execute them
  • C. Create a table on Cloud SQL, and insert and delete rows with the job information
  • D. Create a table on Cloud Spanner, and insert and delete rows with the job information
Answer: A
Explanation:
References:

NEW QUESTION # 274
You have uploaded 5 years of log data to Cloud Storage A user reported that some data points in the log data are outside of their expected ranges, which indicates errors You need to address this issue and be able to run the process again in the future while keeping the original data for compliance reasons. What should you do?
  • A. Create a Compute Engine instance and create a new copy of the data in Cloud Storage Skip the rows with errors
  • B. Create a Cloud Dataflow workflow that reads the data from Cloud Storage, checks for values outside the expected range, sets the value to an appropriate default, and writes the updated records to a new dataset in
    Cloud Storage
  • C. Import the data from Cloud Storage into BigQuery Create a new BigQuery table, and skip the rows with errors.
  • D. Create a Cloud Dataflow workflow that reads the data from Cloud Storage, checks for values outside the expected range, sets the value to an appropriate default, and writes the updated records to the same dataset in Cloud Storage
Answer: D

NEW QUESTION # 275
Assuming that all expiring logs will be archived correctly, where should you store data that is subject to that mandate?
  • A. Encrypted on Cloud Storage with user-supplied encryption keys. A separate decryption key will be given to each authorized user.
  • B. In a bucket on Cloud Storage that is accessible only by an AppEngine service that collects user information and logs the access before providing a link to the bucket.
  • C. In a BigQuery dataset that is viewable only by authorized personnel, with the Data Access log used to provide the auditability.
  • D. In Cloud SQL, with separate database user names to each user. The Cloud SQL Admin activity logs will be used to provide the auditability.
Answer: A

NEW QUESTION # 276
What are all of the BigQuery operations that Google charges for?
  • A. Storage, queries, and streaming inserts
  • B. Storage, queries, and loading data from a file
  • C. Storage, queries, and exporting data
  • D. Queries and streaming inserts
Answer: A
Explanation:
Google charges for storage, queries, and streaming inserts. Loading data from a file and exporting data are free operations.
Reference: https://cloud.google.com/bigquery/pricing

NEW QUESTION # 277
You have spent a few days loading data from comma-separated values (CSV) files into the Google BigQuery table CLICK_STREAM. The column DTstores the epoch time of click events. For convenience, you chose a simple schema where every field is treated as the STRINGtype. Now, you want to compute web session durations of users who visit your site, and you want to change its data type to the TIMESTAMP. You want to minimize the migration effort without making future queries computationally expensive. What should you do?
  • A. Construct a query to return every row of the table CLICK_STREAM, while using the built-in function to cast strings from the column DTinto TIMESTAMPvalues. Run the query into a destination table NEW_CLICK_STREAM, in which the column TSis the TIMESTAMPtype. Reference the table NEW_CLICK_STREAMinstead of the table CLICK_STREAMfrom now on. In the future, new data is loaded into the table NEW_CLICK_STREAM.
  • B. Create a view CLICK_STREAM_V, where strings from the column DTare cast into TIMESTAMPvalues.
    Reference the view CLICK_STREAM_Vinstead of the table CLICK_STREAMfrom now on.
  • C. Add two columns to the table CLICK STREAM: TSof the TIMESTAMPtype and IS_NEWof the BOOLEANtype. Reload all data in append mode. For each appended row, set the value of IS_NEWto true. For future queries, reference the column TSinstead of the column DT, with the WHEREclause ensuring that the value of IS_NEWmust be true.
  • D. Delete the table CLICK_STREAM, and then re-create it such that the column DTis of the TIMESTAMP type. Reload the data.
  • E. Add a column TSof the TIMESTAMPtype to the table CLICK_STREAM, and populate the numeric values from the column TSfor each row. Reference the column TSinstead of the column DTfrom now on.
Answer: C

NEW QUESTION # 278
......
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