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| Section | Weight | Objectives |
|---|---|---|
| Designing data processing systems | 20% | - Storage and data modeling
|
| Operationalizing data and ML pipelines | 30% | - Monitoring and troubleshooting
|
| Maintaining and optimizing data and ML solutions | 20% | - Machine learning integration
|
| Building and operationalizing data processing systems | 30% | - Data pipeline implementation
|
1. You are integrating one of your internal IT applications and Google BigQuery, so users can query BigQuery from the application's interface. You do not want individual users to authenticate to BigQuery and you do not want to give them access to the dataset. You need to securely access BigQuery from your IT application.
What should you do?
A) Create groups for your users and give those groups access to the dataset
B) Create a service account and grant dataset access to that accoun
C) Use the service account's private key to access the dataset
D) Integrate with a single sign-on (SSO) platform, and pass each user's credentials along with the query request
E) Create a dummy user and grant dataset access to that use
F) Store the username and password for that user in a file on the files system, and use those credentials to access the BigQuery dataset
2. You have a data stored in BigQuery. The data in the BigQuery dataset must be highly available. You need to define a storage, backup, and recovery strategy of this data that minimizes cost. How should you configure the BigQuery table?
A) Set the BigQuery dataset to be regiona
B) Set the BigQuery dataset to be multi-regional
C) Set the BigQuery dataset to be regiona
D) In the event of an emergency, use a point-in-time snapshot to recover the data.
E) In the event of an emergency, use a point-in-time snapshot to recover the data.
F) Set the BigQuery dataset to be multi-regional
G) Create a scheduled query to make copies of the data to tables suffixed with the time of the backu
H) Create a scheduled query to make copies of the data to tables suffixed with the time of the backup
I) In the event of an emergency, use the backup copy of the table.
J) In the event of an emergency, use the backup copy of the table.
3. 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) Load the ORC files into BigQuer
B) Mount the Hive tables locally.
C) Leverage Cloud Storage connector for Hadoop to mount the ORC files as external Hive table
D) Run the gsutil utility to transfer all ORC files from the Cloud Storage bucket to HDF
E) Mount the Hive tables from HDFS.
F) Then run the Hadoop utility to copy them do HDF
G) Run the gsutil utility to transfer all ORC files from the Cloud Storage bucket to the master node of the Dataproc cluste
H) Replicate external Hive tables to the native ones.
I) Run the gsutil utility to transfer all ORC files from the Cloud Storage bucket to any node of the Dataproc cluste
J) Mount the Hive tables locally.
K) Leverage BigQuery connector for Hadoop to mount the BigQuery tables as external Hive table
L) Replicate external Hive tables to the native ones.
4. You are implementing several batch jobs that must be executed on a schedule. These jobs have many interdependent steps that must be executed in a specific order. Portions of the jobs involve executing shell scripts, running Hadoop jobs, and running queries in BigQuery. The jobs are expected to run for many minutes up to several hours. If the steps fail, they must be retried a fixed number of times. Which service should you use to manage the execution of these jobs?
A) Cloud Scheduler
B) Cloud Dataflow
C) Cloud Composer
D) Cloud Functions
5. You are operating a Cloud Dataflow streaming pipeline. The pipeline aggregates events from a Cloud Pub/Sub subscription source, within a window, and sinks the resulting aggregation to a Cloud Storage bucket. The source has consistent throughput. You want to monitor an alert on behavior of the pipeline with Cloud Stackdriver to ensure that it is processing dat a. Which Stackdriver alerts should you create?
A) An alert based on a decrease of instance/storage/used_bytes for the source and a rate of change increase of subscription/num_undelivered_messages for the destination
B) An alert based on an increase of instance/storage/used_bytes for the source and a rate of change decrease of subscription/num_undelivered_messages for the destination
C) An alert based on an increase of subscription/num_undelivered_messages for the source and a rate of change decrease of instance/storage/used_bytes for the destination
D) An alert based on a decrease of subscription/num_undelivered_messages for the source and a rate of change increase of instance/storage/used_bytes for the destination
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: E | Question # 3 Answer: I,J | Question # 4 Answer: A | Question # 5 Answer: C |
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