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Google GCP-DE Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Designing data processing systems | 22%-27% | - Designing for data ingestion
|
| Topic 2: Building and operationalizing data processing systems | 28%-33% | - Building data processing systems
|
| Topic 3: Ensuring solution quality | 20%-25% | - Data quality management
|
| Topic 4: Managing and optimizing solutions | 20%-25% | - Reliability and scalability
|
Google Data Engineer Sample Questions:
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 transformation
- B. Use the diagnose command to generate an operational output archiv
- C. Locate the bottleneck and adjust cluster resources.
- D. Configure the job to use non-default Compute Engine machine types when needed.
- E. Monitor CPU utilization for the cluste
- F. Monitor the total execution time for a sampling of job
- G. Resize the number of worker nodes in your cluster via the command line.
- H. Monitor the job system lag with Stackdrive
- I. Use Cloud Dataflow to run your transformation
- J. Use the default autoscaling setting for worker instances.
- K. Use Cloud Dataproc to run your transformation
- L. Use Cloud Dataproc to run your transformation
Correct Answer: E 🗳️
You work for a global shipping company. You want to train a model on 40 TB of data to predict which ships in each geographic region are likely to cause delivery delays on any given day. The model will be based on multiple attributes collected from multiple sources. Telemetry data, including location in GeoJSON format, will be pulled from each ship and loaded every hour. You want to have a dashboard that shows how many and which ships are likely to cause delays within a region. You want to use a storage solution that has native functionality for prediction and geospatial processing. Which storage solution should you use?
- A. BigQuery
- B. Cloud Datastore
- C. Cloud Bigtable
- D. Cloud SQL for PostgreSQL
Correct Answer: A 🗳️
All Google Cloud Bigtable client requests go through a front-end server they are sent to a Cloud Bigtable node.
- A. once
- B. only if
- C. before
- D. after
Correct Answer: C 🗳️
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You are running a pipeline in Cloud Dataflow that receives messages from a Cloud Pub/Sub topic and writes the results to a BigQuery dataset in the EU. Currently, your pipeline is located in europe-west4 and has a maximum of 3 workers, instance type n1-standard-1. You notice that during peak periods, your pipeline is struggling to process records in a timely fashion, when all 3 workers are at maximum CPU utilization. Which two actions can you take to increase performance of your pipeline? (Choose two.)
- A. Create a new step in your pipeline to write to this table first, and then create a new pipeline to write from Cloud Spanner to BigQuery
- B. Use a larger instance type for your Cloud Dataflow workers
- C. Change the zone of your Cloud Dataflow pipeline to run in us-central1
- D. Create a temporary table in Cloud Bigtable that will act as a buffer for new data
- E. Increase the number of max workers
- F. Create a temporary table in Cloud Spanner that will act as a buffer for new data
- G. Create a new step in your pipeline to write to this table first, and then create a new pipeline to write from Cloud Bigtable to BigQuery
Correct Answer: B,G 🗳️
You want to automate execution of a multi-step data pipeline running on Google Cloud. The pipeline includes Cloud Dataproc and Cloud Dataflow jobs that have multiple dependencies on each other. You want to use managed services where possible, and the pipeline will run every day. Which tool should you use?
- A. Cloud Composer
- B. Workflow Templates on Cloud Dataproc
- C. cron
- D. Cloud Scheduler
Correct Answer: B 🗳️
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