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Google GCP-DE Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Operationalizing data and ML pipelines | 30% | - Monitoring and troubleshooting
|
| Topic 2: Building and operationalizing data processing systems | 30% | - Data pipeline implementation
|
| Topic 3: Designing data processing systems | 20% | - Data pipeline architecture design
|
| Topic 4: Maintaining and optimizing data and ML solutions | 20% | - Machine learning integration
|
Google Data Engineer Sample Questions:
Question 1
Which of the following is NOT true about Dataflow pipelines?
A. Dataflow pipelines can be programmed in Java
B. Dataflow pipelines can consume data from other Google Cloud services
C. Dataflow pipelines use a unified programming model, so can work both with streaming and batch data sources
D. Dataflow pipelines are tied to Dataflow, and cannot be run on any other runner
Question 2
Which Cloud Dataflow / Beam feature should you use to aggregate data in an unbounded data source every hour based on the time when the data entered the pipeline?
A. A processing time trigger
B. An event time trigger
C. An hourly watermark
D. The with Allowed Lateness method
Question 3
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 Bigtable
D. Cloud Datastore
Question 4
Which row keys are likely to cause a disproportionate number of reads and/or writes on a particular node in a Bigtable cluster (select 2 answers)?
A. A stock symbol followed by a timestamp
B. A timestamp followed by a stock symbol
C. A sequential numeric ID
D. A non-sequential numeric ID
Question 5
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 temporary table in Cloud Spanner that will act as a buffer for new data
B. 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
C. 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
D. Change the zone of your Cloud Dataflow pipeline to run in us-central1
E. Increase the number of max workers
F. Create a temporary table in Cloud Bigtable that will act as a buffer for new data
G. Use a larger instance type for your Cloud Dataflow workers
Solutions:
| Question 1 Answer: D | Question 2 Answer: A | Question 3 Answer: B | Question 4 Answer: B,C | Question 5 Answer: B,G |
