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Google GCP-DE Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Preparing data for analysis and machine learning | 13% | - Preparing data for ML
|
| Topic 2: Designing data processing systems | 24% | - Designing data pipelines
|
| Topic 3: Storing and managing data | 20% | - Implementing storage solutions
|
| Topic 4: Ingesting and processing data | 25% | - Building data pipelines
|
| Topic 5: Maintaining and automating data workloads | 18% | - Operationalizing workloads
|
Google Data Engineer Sample Questions:
If you're running a performance test that depends upon Cloud Bigtable, all the choices except one below are recommended steps. Which is NOT a recommended step to follow?
- A. Do not use a production instance.
- B. Run your test for at least 10 minutes.
- C. Before you test, run a heavy pre-test for several minutes.
- D. Use at least 300 GB of data.
Correct Answer: A 🗳️
Explanation: Only visible for TrainingDumps members. You can sign-up / login (it's free).
You are implementing several batch jobs that must be executed on a schedule. These jobs have many interdependent steps that must be executed in a specific order. Portions of the jobs involve executing shell scripts, running Hadoop jobs, and running queries in BigQuery. The jobs are expected to run for many minutes up to several hours. If the steps fail, they must be retried a fixed number of times. Which service should you use to manage the execution of these jobs?
- A. Cloud Functions
- B. Cloud Composer
- C. Cloud Dataflow
- D. Cloud Scheduler
Correct Answer: D 🗳️
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 Dataproc to run your transformation
- B. Monitor CPU utilization for the cluste
- C. Use Cloud Dataflow to run your transformation
- D. Use the diagnose command to generate an operational output archiv
- E. Use the default autoscaling setting for worker instances.
- F. Monitor the total execution time for a sampling of job
- G. Monitor the job system lag with Stackdrive
- H. Resize the number of worker nodes in your cluster via the command line.
- I. Use Cloud Dataproc to run your transformation
- J. Use Cloud Dataflow to run your transformation
- K. Locate the bottleneck and adjust cluster resources.
- L. Configure the job to use non-default Compute Engine machine types when needed.
Correct Answer: B 🗳️
When using Cloud Dataproc clusters, you can access the YARN web interface by configuring a browser to connect through a proxy.
- A. HTTP
- B. VPN
- C. SOCKS
- D. HTTPS
Correct Answer: C 🗳️
Explanation: Only visible for TrainingDumps members. You can sign-up / login (it's free).
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 nonkey columns. What should you do?
- A. Use Cloud Dataflow to transform data to support query patterns.
- B. Use Cloud SQL for storag
- C. Use Cloud Spanner for storag
- D. Add secondary indexes to support query patterns.
- E. Use Cloud Spanner for storag
- F. Use Cloud SQL for storag
- G. Use Cloud Dataflow to transform data to support query patterns.
- H. Add secondary indexes to support query patterns.
Correct Answer: A 🗳️
Explanation: Only visible for TrainingDumps members. You can sign-up / login (it's free).
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