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Google Data Engineer Sample Questions:

1. 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) Use a larger instance type for your Cloud Dataflow workers
B) Create a temporary table in Cloud Bigtable that will act as a buffer for new data
C) Increase the number of max workers
D) 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
E) 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
F) Change the zone of your Cloud Dataflow pipeline to run in us-central1
G) Create a temporary table in Cloud Spanner that will act as a buffer for new data

2. 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 Composer
B) Cloud Functions
C) Cloud Scheduler
D) Cloud Dataflow

3. The YARN ResourceManager and the HDFS NameNode interfaces are available on a Cloud Dataproc cluster .

A) master node
B) conditional node
C) worker node
D) application node

4. Which of the following job types are supported by Cloud Dataproc (select 3 answers)?

A) Pig
B) Hive
C) YARN
D) Spark

5. Which of these rules apply when you add preemptible workers to a Dataproc cluster (select 2 answers)?

A) Preemptible workers cannot store data.
B) Preemptible workers cannot use persistent disk.
C) A Dataproc cluster cannot have only preemptible workers.
D) If a preemptible worker is reclaimed, then a replacement worker must be added manually.

Solutions: