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Google Data Engineer Sample Questions:

1. You have enabled the free integration between Firebase Analytics and Google BigQuery. Firebase now automatically creates a new table daily in BigQuery in the format app_events_YYYYMMDD. You want to query all of the tables for the past 30 days in legacy SQL. What should you do?

A) Use WHERE date BETWEEN YYYY-MM-DD AND YYYY-MM-DD
B) Use the WHERE_PARTITIONTIME pseudo column
C) Use the TABLE_DATE_RANGE function
D) Use SELECT IF.(date >= YYYY-MM-DD AND date <= YYYY-MM-DD

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

3. When using Cloud Dataproc clusters, you can access the YARN web interface by configuring a browser to connect through a proxy.

A) HTTP
B) SOCKS
C) HTTPS
D) VPN

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

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

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

Solutions: