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Google GCP-DE Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Maintaining and automating data workloads | 18% | - Operationalizing workloads
|
| Preparing data for analysis and machine learning | 13% | - Preparing data for ML
|
| Designing data processing systems | 24% | - Designing data pipelines
|
| Ingesting and processing data | 25% | - Building data pipelines
|
| Storing and managing data | 20% | - Implementing storage solutions
|
Google Data Engineer Sample Questions:
1. Which Google Cloud Platform service is an alternative to Hadoop with Hive?
A) BigQuery
B) Cloud Bigtable
C) Cloud Datastore
D) Cloud Dataflow
2. Which of these rules apply when you add preemptible workers to a Dataproc cluster (select 2 answers)?
A) Preemptible workers cannot store data.
B) A Dataproc cluster cannot have only preemptible workers.
C) If a preemptible worker is reclaimed, then a replacement worker must be added manually.
D) Preemptible workers cannot use persistent disk.
3. Flowlogistic's management has determined that the current Apache Kafka servers cannot handle the data volume for their real-time inventory tracking system. You need to build a new system on Google Cloud Platform (GCP) that will feed the proprietary tracking software. The system must be able to ingest data from a variety of global sources, process and query in real-time, and store the data reliably. Which combination of GCP products should you choose?
A) Cloud Pub/Sub, Cloud SQL, and Cloud Storage
B) Cloud Load Balancing, Cloud Dataflow, and Cloud Storage
C) Cloud Pub/Sub, Cloud Dataflow, and Local SSD
D) Cloud Pub/Sub, Cloud Dataflow, and Cloud Storage
4. 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) Increase the number of max workers
B) Create a temporary table in Cloud Spanner that will act as a buffer for new data
C) Create a temporary table in Cloud Bigtable that will act as a buffer for new data
D) Use a larger instance type for your Cloud Dataflow workers
E) 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
F) Change the zone of your Cloud Dataflow pipeline to run in us-central1
G) 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
5. 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) Add sensor calibration data to the output of the ETL process, and document that all users need to apply sensor calibration themselves.
C) Modify the transformMapReduce jobs to apply sensor calibration before they do anything else.
D) Introduce a new MapReduce job to apply sensor calibration to raw data, and ensure all other MapReduce jobs are chained after this.
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: A,B | Question # 3 Answer: A | Question # 4 Answer: D,E | Question # 5 Answer: C |





