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Google GCP-DE Exam Syllabus Topics:

Google Data Engineer Sample Questions:

1. Cloud Dataproc is a managed Apache Hadoop and Apache service.

A) Blaze
B) Ignite
C) Spark
D) Fire

2. You are planning to use Google's Dataflow SDK to analyze customer data such as displayed below. Your project requirement is to extract only the customer name Passing Certification Exams Made Easy visit - https://www.2PassEasy.com from the data source and then write to an output PCollection.
Tom,555 X street Tim,553 Y street Sam, 111 Z street
Which operation is best suited for the above data processing requirement?

A) Data extraction
B) ParDo
C) Sink API
D) Source API

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

4. You work for a mid-sized enterprise that needs to move its operational system transaction data from an on-premises database to GCP. The database is about 20 TB in size. Which database should you choose?

A) Cloud SQL
B) Cloud Bigtable
C) Cloud Spanner
D) Cloud Datastore

5. 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) Increase the number of max workers
B) 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
C) 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
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) Create a temporary table in Cloud Spanner that will act as a buffer for new data

Solutions: