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Google Certified Professional Data Engineer Exam Sample Questions (Q275-Q280):
NEW QUESTION # 275
Which SQL keyword can be used to reduce the number of columns processed by BigQuery?
- A. LIMIT
- B. BETWEEN
- C. WHERE
- D. SELECT
Answer: D
Explanation:
Explanation
SELECT allows you to query specific columns rather than the whole table.
LIMIT, BETWEEN, and WHERE clauses will not reduce the number of columns processed by BigQuery.
Reference:
https://cloud.google.com/bigquery/launch-checklist#architecture_design_and_development_checklist
NEW QUESTION # 276
Which row keys are likely to cause a disproportionate number of reads and/or writes on a particular node in a Bigtable cluster (select 2 answers)?
- A. A stock symbol followed by a timestamp
- B. A sequential numeric ID
- C. A timestamp followed by a stock symbol
- D. A non-sequential numeric ID
Answer: B,C
Explanation:
Explanation
using a timestamp as the first element of a row key can cause a variety of problems.
In brief, when a row key for a time series includes a timestamp, all of your writes will target a single node; fill that node; and then move onto the next node in the cluster, resulting in hotspotting.
Suppose your system assigns a numeric ID to each of your application's users. You might be tempted to use the user's numeric ID as the row key for your table. However, since new users are more likely to be active users, this approach is likely to push most of your traffic to a small number of nodes.
[https://cloud.google.com/bigtable/docs/schema-design]
Reference:
https://cloud.google.com/bigtable/docs/schema-design-time-series#ensure_that_your_row_key_avoids_hotspotti
NEW QUESTION # 277
You're training a model to predict housing prices based on an available dataset with real estate properties.
Your plan is to train a fully connected neural net, and you've discovered that the dataset contains latitude and longitude of the property. Real estate professionals have told you that the location of the property is highly influential on price, so you'd like to engineer a feature that incorporates this physical dependency.
What should you do?
- A. Create a numeric column from a feature cross of latitude and longitude.
- B. Create a feature cross of latitude and longitude, bucketize at the minute level and use L1 regularization during optimization.
- C. Create a feature cross of latitude and longitude, bucketize it at the minute level and use L2 regularization during optimization.
- D. Provide latitude and longitude as input vectors to your neural net.
Answer: A
Explanation:
Explanation/Reference:
Reference https://cloud.google.com/bigquery/docs/gis-data
NEW QUESTION # 278
You are training a spam classifier. You notice that you are overfitting the training dat
a. Which three actions can you take to resolve this problem? (Choose three.)
- A. Reduce the number of training examples
- B. Use a larger set of features
- C. Decrease the regularization parameters
- D. Use a smaller set of features
- E. Get more training examples
- F. Increase the regularization parameters
Answer: B,C,E
NEW QUESTION # 279
You issue a new batch job to Dataflow. The job starts successfully, processes a few elements, and then suddenly fails and shuts down. You navigate to the Dataflow monitoring interface where you find errors related to a particular DoFn in your pipeline. What is the most likely cause of the errors?
- A. Job validation
- B. Exceptions in worker code
- C. Graph or pipeline construction
- D. Insufficient permissions
Answer: B
Explanation:
https://cloud.google.com/dataflow/docs/guides/troubleshooting-your-pipeline#detect_an_exception_in_worker_code While your job is running, you might encounter errors or exceptions in your worker code. These errors generally mean that the DoFns in your pipeline code have generated unhandled exceptions, which result in failed tasks in your Dataflow job. Exceptions in user code (for example, your DoFn instances) are reported in the Dataflow monitoring interface.
NEW QUESTION # 280
......
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