Amazon Web Services Updated DBS-C01 Exam Questions and Answers by persephone

https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/vpc-endpoints-dynamodb.html

https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/USER_ShareSnapshot.html

Correct Answer: B, E, F

Explanation from Amazon documents:

To upload data faster to a Neptune DB instance from a .csv file stored in Amazon S3, the database specialist should use the Neptune Bulk Loader, which is a feature that allows you to load data from external files directly into a Neptune DB instance1. The Neptune Bulk Loader is faster and has less overhead than the API calls, such as SPARQL INSERT statements or Gremlin addV and addE steps2. The Neptune Bulk Loader supports both RDF and Gremlin data formats1.

To use the Neptune Bulk Loader, the database specialist needs to do the following13:

• Ensure the vertices and edges are specified in different .csv files with proper header column formatting. This is required for the Gremlin data format, which uses two .csv files: one for vertices and one for edges. The first row of each file must contain the column names, which must match the property names of the graph elements. The files must also have a column named ~id for vertices and ~from and ~to for edges, which specify the unique identifiers of the graph elements1.
• Ensure an IAM role for the Neptune DB instance is configured with the appropriate permissions to allow access to the file in the S3 bucket. This is required for the Neptune DB instance to read the data from the S3 bucket. The IAM role must have a trust policy that allows Neptune to assume the role, and a permissions policy that allows access to the S3 bucket and objects3.
• Create an S3 VPC endpoint and issue an HTTP POST to the database’s loader endpoint. This is required for the Neptune DB instance to communicate with the S3 bucket without going through the public internet. The S3 VPC endpoint must be in the same VPC as the Neptune DB instance. The HTTP POST request must specify the source parameter as the S3 URI of the .csv file, and optionally other parameters such as format, failOnError, parallelism, etc1.

Therefore, option B, E, and F are the correct steps to upload the data faster. Option A is not necessary because Amazon Cognito is not used for authenticating the Neptune DB instance to the S3 bucket. Option C is not suitable because AWS DMS is not designed for loading graph data into Neptune. Option D is not efficient because curling the S3 URI and running the addVertex or addEdge commands will be slower and more costly than using the Neptune Bulk Loader.

https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/USER_RebootInstance.html

https://exain.wordpress.com/2017/07/12/amazon-rds-multi-az-setup-failover-simulation/

"Rebooting with failover is beneficial when you want to simulate a failure of a DB instance for testing, or restore operations to the original AZ after a failover occurs."