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NEW QUESTION 35
You are working on a linear regression model on BigQuery ML to predict a customer’s likelihood of purchasing your company’s products. Your model uses a city name variable as a key predictive component in order to train and serve the model your data must be organized in columns. You want to prepare your data using the least amount of coding while maintaining the predictable variables. What should you do?
- A. Cloud Data Fusion to assign each city to a region that is labeled as 1, 2 3, 4, or 5, and then use that number to represent the city in the model.
- B. Use SQL in BigQuery to transform the stale column using a one-hot encoding method, and make each city a column with binary values.
- C. Create a new view with BigQuery that does not include a column which city information.
- D. Use TensorFlow to create a categorical variable with a vocabulary list. Create the vocabulary file and upload that as part of your model to BigQuery ML.
Answer: A
NEW QUESTION 36
You are designing storage for two relational tables that are part of a 10-TB database on Google Cloud. You want to support transactions that scale horizontally. You also want to optimize data for range queries on non-key columns. What should you do?
- A. Use Cloud SQL for storage. Add secondary indexes to support query patterns.
- B. Use Cloud Spanner for storage. Use Cloud Dataflow to transform data to support query patterns.
- C. Use Cloud SQL for storage. Use Cloud Dataflow to transform data to support query patterns.
- D. Use Cloud Spanner for storage. Add secondary indexes to support query patterns.
Answer: D
Explanation:
Spanner allows transaction tables to scale horizontally and secondary indexes for range queries.
NEW QUESTION 37
You have developed three data processing jobs. One executes a Cloud Dataflow pipeline that transforms data uploaded to Cloud Storage and writes results to BigQuery. The second ingests data from on- premises servers and uploads it to Cloud Storage. The third is a Cloud Dataflow pipeline that gets information from third-party data providers and uploads the information to Cloud Storage. You need to be able to schedule and monitor the execution of these three workflows and manually execute them when needed. What should you do?
- A. Develop an App Engine application to schedule and request the status of the jobs using GCP API calls.
- B. Use Stackdriver Monitoring and set up an alert with a Webhook notification to trigger the jobs.
- C. Set up cron jobs in a Compute Engine instance to schedule and monitor the pipelines using GCP API calls.
- D. Create a Direct Acyclic Graph in Cloud Composer to schedule and monitor the jobs.
Answer: D
Explanation:
Cloud composer is used to schedule the interdependent jobs.
NEW QUESTION 38
Cloud Dataproc charges you only for what you really use with _____ billing.
- A. month-by-month
- B. week-by-week
- C. minute-by-minute
- D. hour-by-hour
Answer: C
Explanation:
Explanation
One of the advantages of Cloud Dataproc is its low cost. Dataproc charges for what you really use with minute-by-minute billing and a low, ten-minute-minimum billing period.
Reference: https://cloud.google.com/dataproc/docs/concepts/overview
NEW QUESTION 39
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