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Google Data Engineer Sample Questions:

1. You are designing storage for two relational tables that are part of a 10-TB database on Google Cloud. You want to support transactions that scale horizontally. You also want to optimize data for range queries on nonkey columns. What should you do?

A) Use Cloud Spanner for storag
B) Add secondary indexes to support query patterns.
C) Use Cloud Spanner for storag
D) Use Cloud SQL for storag
E) Use Cloud Dataflow to transform data to support query patterns.
F) Use Cloud Dataflow to transform data to support query patterns.
G) Use Cloud SQL for storag
H) Add secondary indexes to support query patterns.

2. When a Cloud Bigtable node fails, is lost.

A) the time dimension
B) the last transaction
C) no data
D) all data

3. You have developed three data processing jobs. One executes a Cloud Dataflow pipeline that transforms data uploaded to Cloud Storage and writes results to BigQuery. The second ingests data from on-premises servers and uploads it to Cloud Storage. The third is a Cloud Dataflow pipeline that gets information from third-party data providers and uploads the information to Cloud Storage. You need to be able to schedule and monitor the execution of these three workflows and manually execute them when needed. What should you do?

A) Develop an App Engine application to schedule and request the status of the jobs using GCP API calls.
B) Create a Direct Acyclic Graph in Cloud Composer to schedule and monitor the jobs.
C) Use Stackdriver Monitoring and set up an alert with a Webhook notification to trigger the jobs.
D) Set up cron jobs in a Compute Engine instance to schedule and monitor the pipelines using GCP API calls.

4. Which of the following is NOT one of the three main types of triggers that Dataflow supports?

A) Trigger that is a combination of other triggers
B) Trigger based on time
C) Trigger based on element size in bytes
D) Trigger based on element count

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

Solutions: