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Google Data Engineer Sample Questions:

1. You are building a new data pipeline to share data between two different types of applications: jobs generators and job runners. Your solution must scale to accommodate increases in usage and must accommodate the addition of new applications without negatively affecting the performance of existing ones. What should you do?

A) Create a table on Cloud SQL, and insert and delete rows with the job information
B) Create an API using App Engine to receive and send messages to the applications
C) Create a table on Cloud Spanner, and insert and delete rows with the job information
D) Use a Cloud Pub/Sub topic to publish jobs, and use subscriptions to execute them

2. Which Google Cloud Platform service is an alternative to Hadoop with Hive?

A) Cloud Bigtable
B) Cloud Dataflow
C) Cloud Datastore
D) BigQuery

3. You are responsible for writing your company's ETL pipelines to run on an Apache Hadoop cluster. The pipeline will require some checkpointing and splitting pipelines. Which method should you use to write the pipelines?

A) HiveQL using Hive
B) PigLatin using Pig
C) Python using MapReduce
D) Java using MapReduce

4. By default, which of the following windowing behavior does Dataflow apply to unbounded data sets?

A) Windows at every 100 MB of data
B) Windows at every 10 minutes
C) Single, Global Window
D) Windows at every 1 minute

5. Each analytics team in your organization is running BigQuery jobs in their own projects. You want to enable each team to monitor slot usage within their projects. What should you do?

A) Create a Stackdriver Monitoring dashboard based on the BigQuery metric slots/allocated_for_project
B) Create an aggregated log export at the organization level, capture the BigQuery job execution logs, create a custom metric based on the totalSlotMs, and create a Stackdriver Monitoring dashboard based on the custom metric
C) Create a log export for each project, capture the BigQuery job execution logs, create a custom metric based on the totalSlotMs, and create a Stackdriver Monitoring dashboard based on the custom metric
D) Create a Stackdriver Monitoring dashboard based on the BigQuery metric query/scanned_bytes

Solutions: