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Google GCP-DE Exam Syllabus Topics:

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

2. 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) Java using MapReduce
C) PigLatin using Pig
D) Python using MapReduce

3. You need to choose a database for a new project that has the following requirements:
Fully managed
Able to automatically scale up
Transactionally consistent
Able to scale up to 6 TB
Able to be queried using SQL Which database do you choose?

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

4. You operate an IoT pipeline built around Apache Kafka that normally receives around 5000 messages per second. You want to use Google Cloud Platform to create an alert as soon as the moving average over 1 hour drops below 4000 messages per second. What should you do?

A) Use Cloud Scheduler to run a script every five minutes that counts the number of rows created in BigQuery in the last hour
B) If that number falls below 4000, send an alert.
C) Use a Cloud Dataflow template to write your messages from Cloud Pub/Sub to BigQuer
D) Use Kafka Connect to link your Kafka message queue to Cloud Pub/Su
E) Set a fixed time window of 1 hour.Compute the average when the window closes, and send an alert if the average is less than 4000 messages.
F) Consume the stream of data in Cloud Dataflow using Kafka I
G) Use a Cloud Dataflow template to write your messages from Cloud Pub/Sub to Cloud Bigtabl
H) Use Cloud Scheduler to run a script every hour that counts the number of rows created in Cloud Bigtable in the last hour
I) Compute the average when the window closes, and send an alert if the average is less than 4000 messages.
J) Set a sliding time window of 1 hour every 5 minute
K) Consume the stream of data in Cloud Dataflow using Kafka I
L) If that number falls below 4000, send an alert.
M) Use Kafka Connect to link your Kafka message queue to Cloud Pub/Su

5. What are the minimum permissions needed for a service account used with Google Dataproc?

A) Execute to Google Cloud Storage; write to Google Cloud Logging
B) Read and write to Google Cloud Storage; write to Google Cloud Logging
C) Execute to Google Cloud Storage; execute to Google Cloud Logging
D) Write to Google Cloud Storage; read to Google Cloud Logging

Solutions: