Google Data Engineer : GCP-DE Exam Questions

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Google GCP-DE Exam Syllabus Topics:

Google Data Engineer Sample Questions:

1. What Dataflow concept determines when a Window's contents should be output based on certain criteria being met?

A) Sessions
B) OutputCriteria
C) Windows
D) Triggers

2. You want to migrate an on-premises Hadoop system to Cloud Dataproc. Hive is the primary tool in use, and the data format is Optimized Row Columnar (ORC). All ORC files have been successfully copied to a Cloud Storage bucket. You need to replicate some data to the cluster's local Hadoop Distributed File System (HDFS) to maximize performance. What are two ways to start using Hive in Cloud Dataproc? (Choose two.)

A) Then run the Hadoop utility to copy them do HDF
B) Replicate external Hive tables to the native ones.
C) Mount the Hive tables from HDFS.
D) Run the gsutil utility to transfer all ORC files from the Cloud Storage bucket to HDF
E) Run the gsutil utility to transfer all ORC files from the Cloud Storage bucket to any node of the Dataproc cluste
F) Replicate external Hive tables to the native ones.
G) Load the ORC files into BigQuer
H) Mount the Hive tables locally.
I) Leverage BigQuery connector for Hadoop to mount the BigQuery tables as external Hive table
J) Run the gsutil utility to transfer all ORC files from the Cloud Storage bucket to the master node of the Dataproc cluste
K) Leverage Cloud Storage connector for Hadoop to mount the ORC files as external Hive table
L) Mount the Hive tables locally.

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) Java using MapReduce
D) Python using MapReduce

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

5. Which of the following is NOT true about Dataflow pipelines?

A) Dataflow pipelines can consume data from other Google Cloud services
B) Dataflow pipelines are tied to Dataflow, and cannot be run on any other runner
C) Dataflow pipelines can be programmed in Java
D) Dataflow pipelines use a unified programming model, so can work both with streaming and batch data sources

Solutions: