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NEW QUESTION 27
An electric utility company wants to store power plant sensor data in an Amazon DynamoDB table. The utility company has over 100 power plants and each power plant has over 200 sensors that send data every 2 seconds. The sensor data includes time with milliseconds precision, a value, and a fault attribute if the sensor is malfunctioning. Power plants are identified by a globally unique identifier. Sensors are identified by a unique identifier within each power plant. A database specialist needs to design the table to support an efficient method of finding all faulty sensors within a given power plant.
Which schema should the database specialist use when creating the DynamoDB table to achieve the fastest query time when looking for faulty sensors?
Answer: B
Explanation:
Plant id as partition key and Sensor id as a sort key. Fault can be identified quickly using the local secondary index and associated plant and sensor can be identified easily.
NEW QUESTION 28
A Database Specialist is migrating a 2 TB Amazon RDS for Oracle DB instance to an RDS for PostgreSQL DB instance using AWS DMS. The source RDS Oracle DB instance is in a VPC in the us-east-1 Region. The target RDS for PostgreSQL DB instance is in a VPC in the use-west-2 Region.
Where should the AWS DMS replication instance be placed for the MOST optimal performance?
Answer: B
NEW QUESTION 29
A database specialist is managing an application in the us-west-1 Region and wants to set up disaster recovery in the us-east-1 Region. The Amazon Aurora MySQL DB cluster needs an RPO of 1 minute and an RTO of 2 minutes.
Which approach meets these requirements with no negative performance impact?
Answer: B
NEW QUESTION 30
Recently, a financial institution created a portfolio management service. The application's backend is powered by Amazon Aurora, which supports MySQL.
The firm demands a response time of five minutes and a response time of five minutes. A database professional must create a disaster recovery system that is both efficient and has a low replication latency.
How should the database professional tackle these requirements?
Answer: C
Explanation:
https://docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/aurora-global-database-disaster-recovery.html
https://aws.amazon.com/blogs/database/how-to-choose-the-best-disaster-recovery-option-for-your-amazon-aurora-mysql-cluster/
https://aws.amazon.com/about-aws/whats-new/2019/11/aurora-supports-in-place-conversion-to-global-database/
NEW QUESTION 31
A company has a heterogeneous six-node production Amazon Aurora DB cluster that handles online transaction processing (OLTP) for the core business and OLAP reports for the human resources department.
To match compute resources to the use case, the company has decided to have the reporting workload for the human resources department be directed to two small nodes in the Aurora DB cluster, while every other workload goes to four large nodes in the same DB cluster.
Which option would ensure that the correct nodes are always available for the appropriate workload while meeting these requirements?
Answer: A
Explanation:
Explanation
https://aws.amazon.com/about-aws/whats-new/2018/11/amazon-aurora-simplifies-workload-management-with-c You can now create custom endpoints for Amazon Aurora databases. This allows you to distribute and load balance workloads across different sets of database instances in your Aurora cluster. For example, you may provision a set of Aurora Replicas to use an instance type with higher memory capacity in order to run an analytics workload. A custom endpoint can then help you route the analytics workload to these appropriately-configured instances, while keeping other instances in your cluster isolated from this workload.
As you add or remove instances from the custom endpoint to match your workload, the endpoint helps spread the load around.
NEW QUESTION 32
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