Google Data Engineer : GCP-DE exam

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Google GCP-DE Exam Syllabus Topics:

Google Data Engineer Sample Questions:

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

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

2. You are building a model to predict whether or not it will rain on a given day. You have thousands of input features and want to see if you can improve training speed by removing some features while having a minimum effect on model accuracy. What can you do?

A) Eliminate features that are highly correlated to the output labels.
B) Instead of feeding in each feature individually, average their values in batches of 3.
C) Combine highly co-dependent features into one representative feature.
D) Remove the features that have null values for more than 50% of the training records.

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

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

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

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

5. You need to deploy additional dependencies to all of a Cloud Dataproc cluster at startup using an existing initialization action. Company security policies require that Cloud Dataproc nodes do not have access to the Internet so public initialization actions cannot fetch resources. What should you do?

A) Copy all dependencies to a Cloud Storage bucket within your VPC security perimeter
B) Use an SSH tunnel to give the Cloud Dataproc cluster access to the Internet
C) Use Resource Manager to add the service account used by the Cloud Dataproc cluster to the Network User role
D) Deploy the Cloud SQL Proxy on the Cloud Dataproc master

Solutions: