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NEW QUESTION 30 You are developing an application on Google Cloud that will automatically generate subject labels for users' blog posts. You are under competitive pressure to add this feature quickly, and you have no additional developer resources. No one on your team has experience with machine learning. What should you do?

  • A. Call the Cloud Natural Language API from your application. Process the generated Sentiment Analysis as labels.
  • B. Build and train a text classification model using TensorFlow. Deploy the model using Cloud Machine Learning Engine. Call the model from your application and process the results as labels.
  • C. Call the Cloud Natural Language API from your application. Process the generated Entity Analysis as labels.
  • D. Build and train a text classification model using TensorFlow. Deploy the model using a Kubernetes Engine cluster. Call the model from your application and process the results as labels.

Answer: A   NEW QUESTION 31 Which of these is not a supported method of putting data into a partitioned table?

  • A. Use ORDER BY to put a table's rows into chronological order and then change the table's type to "Partitioned".
  • B. If you have existing data in a separate file for each day, then create a partitioned table and upload each file into the appropriate partition.
  • C. Create a partitioned table and stream new records to it every day.
  • D. Run a query to get the records for a specific day from an existing table and for the destination table, specify a partitioned table ending with the day in the format "$YYYYMMDD".

Answer: A Explanation: You cannot change an existing table into a partitioned table. You must create a partitioned table from scratch. Then you can either stream data into it every day and the data will automatically be put in the right partition, or you can load data into a specific partition by using "$YYYYMMDD" at the end of the table name. Reference: https://cloud.google.com/bigquery/docs/partitioned-tables   NEW QUESTION 32 Which is not a valid reason for poor Cloud Bigtable performance?

  • A. The workload isn't appropriate for Cloud Bigtable.
  • B. There are issues with the network connection.
  • C. The Cloud Bigtable cluster has too many nodes.
  • D. The table's schema is not designed correctly.

Answer: C Explanation: Explanation The Cloud Bigtable cluster doesn't have enough nodes. If your Cloud Bigtable cluster is overloaded, adding more nodes can improve performance. Use the monitoring tools to check whether the cluster is overloaded. Reference: https://cloud.google.com/bigtable/docs/performance   NEW QUESTION 33 You are selecting services to write and transform JSON messages from Cloud Pub/Sub to BigQuery for a data pipeline on Google Cloud. You want to minimize service costs. You also want to monitor and accommodate input data volume that will vary in size with minimal manual intervention. What should you do?

  • A. Use Cloud Dataflow to run your transformations. Monitor the total execution time for a sampling of jobs. Configure the job to use non-default Compute Engine machine types when needed.
  • B. Use Cloud Dataproc to run your transformations. Monitor CPU utilization for the cluster. Resize the number of worker nodes in your cluster via the command line.
  • C. Use Cloud Dataflow to run your transformations. Monitor the job system lag with Stackdriver. Use the default autoscaling setting for worker instances.
  • D. Use Cloud Dataproc to run your transformations. Use the diagnose command to generate an operational output archive. Locate the bottleneck and adjust cluster resources.

Answer: C Explanation: Dataflow is good with autoscaling and stackdriver to monitor CPU and Storage.   NEW QUESTION 34 You are designing a basket abandonment system for an ecommerce company. The system will send a message to a user based on these rules: No interaction by the user on the site for 1 hour Has added more than $30 worth of products to the basket Has not completed a transaction You use Google Cloud Dataflow to process the data and decide if a message should be sent. How should you design the pipeline?

  • A. Use a fixed-time window with a duration of 60 minutes.
  • B. Use a global window with a time based trigger with a delay of 60 minutes.
  • C. Use a sliding time window with a duration of 60 minutes.
  • D. Use a session window with a gap time duration of 60 minutes.

Answer: B   NEW QUESTION 35 ...... BTW, DOWNLOAD part of PassTestking Professional-Data-Engineer dumps from Cloud Storage: https://drive.google.com/open?id=1KxcYJVgFF1OVX2f5BT7qivpCMJvS2VtH