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Google Data Engineer Sample Questions:

1. 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) Use at least 300 GB of data.
B) Run your test for at least 10 minutes.
C) Do not use a production instance.
D) Before you test, run a heavy pre-test for several minutes.

2. 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 Datastore
B) Cloud SQL for PostgreSQL
C) BigQuery
D) Cloud Bigtable

3. You receive data files in CSV format monthly from a third party. You need to cleanse this data, but every third month the schema of the files changes. Your requirements for implementing these transformations include:
Executing the transformations on a schedule
Enabling non-developer analysts to modify transformations
Providing a graphical tool for designing transformations
What should you do?

A) Use Apache Spark on Cloud Dataproc to infer the schema of the CSV file before creating a Dataframe.Then implement the transformations in Spark SQL before writing the data out to Cloud Storage and loading into BigQuery
B) The Python code should be stored in a revision control system and modified as the incoming data's schema changes
C) Load each month's CSV data into BigQuery, and write a SQL query to transform the data to a standard scheme
D) Merge the transformed tables together with a SQL query
E) Use Cloud Dataprep to build and maintain the transformation recipes, and execute them on a scheduled basis
F) Help the analysts write a Cloud Dataflow pipeline in Python to perform the transformatio

4. What Dataflow concept determines when a Window's contents should be output based on certain criteria being met?

A) Triggers
B) OutputCriteria
C) Sessions
D) Windows

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) If a preemptible worker is reclaimed, then a replacement worker must be added manually.
D) A Dataproc cluster cannot have only preemptible workers.

Solutions: