GCP-DE Exams Collection & Sample GCP-DE Test Online
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Sample Google GCP-DE Test Online - GCP-DE Test Collection
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Google Data Engineer Sample Questions (Q60-Q65):
NEW QUESTION # 60
What Dataflow concept determines when a Window's contents should be output based on certain criteria being met?
- A. OutputCriteria
- B. Triggers
- C. Sessions
- D. Windows
Answer: B
Explanation:
Triggers control when the elements for a specific key and window are output. As elements arrive, they are put into one or more windows by a Window transform and its associated WindowFn, and then passed to the associated Trigger to determine if the Windows contents should be output.
Reference:
https://cloud.google.com/dataflow/java-sdk/JavaDoc/com/google/cloud/dataflow/sdk/transforms/windowing/Tri
NEW QUESTION # 61
Which of the following job types are supported by Cloud Dataproc (select 3 answers)?
- A. YARN
- B. Pig
- C. Hive
- D. Spark
Answer: B,C,D
Explanation:
Cloud Dataproc provides out-of-the box and end-to-end support for many of the most popular job types, including Spark, Spark SQL, PySpark, MapReduce, Hive, and Pig jobs.
Reference: https://cloud.google.com/dataproc/docs/resources/faq#what_type_of_jobs_can_i_run
NEW QUESTION # 62
You architect a system to analyze seismic dat
a. Your extract, transform, and load (ETL) process runs as a series of MapReduce jobs on an Apache Hadoop cluster. The ETL process takes days to process a data set because some steps are computationally expensive. Then you discover that a sensor calibration step has been omitted. How should you change your ETL process to carry out sensor calibration systematically in the future?
- A. Develop an algorithm through simulation to predict variance of data output from the last MapReduce job based on calibration factors, and apply the correction to all data.
- B. Modify the transformMapReduce jobs to apply sensor calibration before they do anything else.
- C. Introduce a new MapReduce job to apply sensor calibration to raw data, and ensure all other MapReduce jobs are chained after this.
- D. Add sensor calibration data to the output of the ETL process, and document that all users need to apply sensor calibration themselves.
Answer: B
NEW QUESTION # 63
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. Monitor the total execution time for a sampling of job
- B. Monitor CPU utilization for the cluste
- C. Locate the bottleneck and adjust cluster resources.
- D. Use the diagnose command to generate an operational output archiv
- E. Use the default autoscaling setting for worker instances.
- F. Configure the job to use non-default Compute Engine machine types when needed.
- G. Use Cloud Dataflow to run your transformation
- H. Use Cloud Dataflow to run your transformation
- I. Monitor the job system lag with Stackdrive
- J. Resize the number of worker nodes in your cluster via the command line.
- K. Use Cloud Dataproc to run your transformation
- L. Use Cloud Dataproc to run your transformation
Answer: B
NEW QUESTION # 64
Your company maintains a hybrid deployment with GCP, where analytics are performed on your anonymized customer dat a. The data are imported to Cloud Storage from your data center through parallel uploads to a data transfer server running on GCP. Management informs you that the daily transfers take too long and have asked you to fix the problem. You want to maximize transfer speeds. Which action should you take?
- A. Increase the CPU size on your server.
- B. Increase the size of the Google Persistent Disk on your server.
- C. Increase your network bandwidth from Compute Engine to Cloud Storage.
- D. Increase your network bandwidth from your datacenter to GCP.
Answer: D
NEW QUESTION # 65
......
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