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Google GCP-DE Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Building and operationalizing data processing systems | 30% | - Data pipeline implementation
|
| Topic 2: Designing data processing systems | 20% | - Data pipeline architecture design
|
| Topic 3: Maintaining and optimizing data and ML solutions | 20% | - Security and governance
|
| Topic 4: Operationalizing data and ML pipelines | 30% | - Pipeline automation and orchestration
|
Google Data Engineer Sample Questions:
Which of the following job types are supported by Cloud Dataproc (select 3 answers)?
- A. Spark
- B. Pig
- C. YARN
- D. Hive
Correct Answer: A,B,D 🗳️
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You work for a mid-sized enterprise that needs to move its operational system transaction data from an on-premises database to GCP. The database is about 20 TB in size. Which database should you choose?
- A. Cloud Spanner
- B. Cloud SQL
- C. Cloud Datastore
- D. Cloud Bigtable
Correct Answer: B 🗳️
You want to migrate an on-premises Hadoop system to Cloud Dataproc. Hive is the primary tool in use, and the data format is Optimized Row Columnar (ORC). All ORC files have been successfully copied to a Cloud Storage bucket. You need to replicate some data to the cluster's local Hadoop Distributed File System (HDFS) to maximize performance. What are two ways to start using Hive in Cloud Dataproc? (Choose two.)
- A. Run the gsutil utility to transfer all ORC files from the Cloud Storage bucket to the master node of the Dataproc cluste
- B. Replicate external Hive tables to the native ones.
- C. Leverage Cloud Storage connector for Hadoop to mount the ORC files as external Hive table
- D. Replicate external Hive tables to the native ones.
- E. Load the ORC files into BigQuer
- F. Mount the Hive tables from HDFS.
- G. Run the gsutil utility to transfer all ORC files from the Cloud Storage bucket to any node of the Dataproc cluste
- H. Mount the Hive tables locally.
- I. Run the gsutil utility to transfer all ORC files from the Cloud Storage bucket to HDF
- J. Then run the Hadoop utility to copy them do HDF
- K. Leverage BigQuery connector for Hadoop to mount the BigQuery tables as external Hive table
- L. Mount the Hive tables locally.
Correct Answer: G,L 🗳️
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. cron
- B. Cloud Scheduler
- C. Workflow Templates on Cloud Dataproc
- D. Cloud Composer
Correct Answer: C 🗳️
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. Cloud SQL for PostgreSQL
- B. BigQuery
- C. Cloud Datastore
- D. Cloud Bigtable
Correct Answer: B 🗳️
