- (Exam Topic 6)
As your organization expands its usage of GCP, many teams have started to create their own projects. Projects are further multiplied to accommodate different stages of deployments and target audiences. Each project requires unique access control configurations. The central IT team needs to have access to all projects. Furthermore, data from Cloud Storage buckets and BigQuery datasets must be shared for use in other projects in an ad hoc way. You want to simplify access control management by minimizing the number of policies. Which two steps should you take? Choose 2 answers.

1. A. Use Cloud Deployment Manager to automate access provision.
2. B. Introduce resource hierarchy to leverage access control policy inheritance.
3. C. Create distinct groups for various teams, and specify groups in Cloud IAM policies.
4. D. Only use service accounts when sharing data for Cloud Storage buckets and BigQuery datasets.
5. E. For each Cloud Storage bucket or BigQuery dataset, decide which projects need acces
6. F. Find all the active members who have access to these projects, and create a Cloud IAM policy to grant access to all these users.

Correct Answer: AC

- (Exam Topic 6)
You are migrating an application that tracks library books and information about each book, such as author or year published, from an on-premises data warehouse to BigQuery In your current relational database, the author information is kept in a separate table and joined to the book information on a common key Based on Google's recommended practice for schema design, how would you structure the data to ensure optimal speed of queries about the author of each book that has been borrowed?

1. A. Keep the schema the same, maintain the different tables for the book and each of the attributes, and query as you are doing today
2. B. Create a table that is wide and includes a column for each attribute, including the author's first name, last name, date of birth, etc
3. C. Create a table that includes information about the books and authors, but nest the author fields inside the author column
4. D. Keep the schema the same, create a view that joins all of the tables, and always query the view

Correct Answer: C

- (Exam Topic 5)
Which of these is NOT a way to customize the software on Dataproc cluster instances?

1. A. Set initialization actions
2. B. Modify configuration files using cluster properties
3. C. Configure the cluster using Cloud Deployment Manager
4. D. Log into the master node and make changes from there

Correct Answer: C
You can access the master node of the cluster by clicking the SSH button next to it in the Cloud Console.
You can easily use the --properties option of the dataproc command in the Google Cloud SDK to modify many common configuration files when creating a cluster.
When creating a Cloud Dataproc cluster, you can specify initialization actions in executables and/or scripts that Cloud Dataproc will run on all nodes in your Cloud Dataproc cluster immediately after the cluster is set up. [https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/init-actions]
Reference: https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/cluster-properties

- (Exam Topic 5)
When creating a new Cloud Dataproc cluster with the projects.regions.clusters.create operation, these four values are required: project, region, name, and .

1. A. zone
2. B. node
3. C. label
4. D. type

Correct Answer: A
At a minimum, you must specify four values when creating a new cluster with the projects.regions.clusters.create operation:
The project in which the cluster will be created The region to use
The name of the cluster
The zone in which the cluster will be created
You can specify many more details beyond these minimum requirements. For example, you can
also specify the number of workers, whether preemptible compute should be used, and the network settings. Reference:
https://cloud.google.com/dataproc/docs/tutorials/python-library-example#create_a_new_cloud_dataproc_cluste

- (Exam Topic 5)
Which of these is not a supported method of putting data into a partitioned table?

1. A. If you have existing data in a separate file for each day, then create a partitioned table and upload each file into the appropriate partition.
2. B. Run a query to get the records for a specific day from an existing table and for the destination table,specify a partitioned table ending with the day in the format "$YYYYMMDD".
3. C. Create a partitioned table and stream new records to it every day.
4. D. Use ORDER BY to put a table's rows into chronological order and then change the table's type to "Partitioned".

Correct Answer: D
You cannot change an existing table into a partitioned table. You must create a partitioned table from scratch. Then you can either stream data into it every day and the data will automatically be put in the right partition, or you can load data into a specific partition by using "$YYYYMMDD" at the end of the table name.
Reference: https://cloud.google.com/bigquery/docs/partitioned-tables