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

2. You need to deploy additional dependencies to all of a Cloud Dataproc cluster at startup using an existing initialization action. Company security policies require that Cloud Dataproc nodes do not have access to the Internet so public initialization actions cannot fetch resources. What should you do?

A) Copy all dependencies to a Cloud Storage bucket within your VPC security perimeter
B) Use an SSH tunnel to give the Cloud Dataproc cluster access to the Internet
C) Use Resource Manager to add the service account used by the Cloud Dataproc cluster to the Network User role
D) Deploy the Cloud SQL Proxy on the Cloud Dataproc master

3. You have a data stored in BigQuery. The data in the BigQuery dataset must be highly available. You need to define a storage, backup, and recovery strategy of this data that minimizes cost. How should you configure the BigQuery table?

A) Set the BigQuery dataset to be regiona
B) In the event of an emergency, use a point-in-time snapshot to recover the data.
C) In the event of an emergency, use the backup copy of the table.
D) Create a scheduled query to make copies of the data to tables suffixed with the time of the backu
E) Set the BigQuery dataset to be multi-regional
F) In the event of an emergency, use a point-in-time snapshot to recover the data.
G) Set the BigQuery dataset to be multi-regional
H) Set the BigQuery dataset to be regiona
I) Create a scheduled query to make copies of the data to tables suffixed with the time of the backup
J) In the event of an emergency, use the backup copy of the table.

4. MJTelco is building a custom interface to share dat
a. They have these requirements:
They need to do aggregations over their petabyte-scale datasets.
They need to scan specific time range rows with a very fast response time (milliseconds). Which combination of Google Cloud Platform products should you recommend?

A) BigQuery and Cloud Storage
B) Cloud Bigtable and Cloud SQL
C) Cloud Datastore and Cloud Bigtable
D) BigQuery and Cloud Bigtable

5. Suppose you have a table that includes a nested column called "city" inside a column called "person", but when you try to submit the following query in BigQuery, it gives you an error.
SELECT person FROM `project1.example.table1` WHERE city = "London"
How would you correct the error?

A) Change "person" to "city.person".
B) Change "person" to "person.city".
C) Add ", UNNEST(city)" before the WHERE clause.
D) Add ", UNNEST(person)" before the WHERE clause.

Solutions: