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NEW QUESTION: 1
You are designing a Mapping. How are target and source tables defined? (Choose the best answer.)
A. Forevery load the definition of the tables used, their columns and constraints must be manually built.
B. Their definition is imported with a reverse-engineering process directly from databases and other sources.
C. Their definition is imported with areverse-engineering process directly from databases and other sources, but you must manually define all keys and constraints existing on the database.
D. An external engine must be run to describe what metadata is needed for a Mapping.
Answer: C
Explanation:
(https://docs.oracle.com/middleware/1212/odi/ODIDG/create_rev_model.htm#ODIDG234)

NEW QUESTION: 2

A. Option A
B. Option C
C. Option D
D. Option B
Answer: D
Explanation:
Explanation
To communicate with the worker role, a web role instance places messages on to a queue. A worker role instance polls the queue for new messages, retrieves them, and processes them. There are a couple of important things to know about the way the queue service works in Azure. First, you reference a queue by name, and multiple role instances can share a single queue. Second, there is no concept of a typed message; you construct a message from either a string or a byte array. An individual message can be no more than 64 kilobytes (KB) in size.
References:
https://msdn.microsoft.com/en-gb/library/ff803365.aspx
http://azure.microsoft.com/en-gb/documentation/articles/cloud-services-dotnet-multi-tier-app-using-service-bus-

NEW QUESTION: 3
A Machine Learning Specialist is packaging a custom ResNet model into a Docker container so the company can leverage Amazon SageMaker for training. The Specialist is using Amazon EC2 P3 instances to train the model and needs to properly configure the Docker container to leverage the NVIDIA GPUs.
What does the Specialist need to do?
A. Bundle the NVIDIA drivers with the Docker image.
B. Organize the Docker container's file structure to execute on GPU instances.
C. Set the GPU flag in the Amazon SageMaker CreateTrainingJob request body.
D. Build the Docker container to be NVIDIA-Docker compatible.
Answer: D
Explanation:
https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-dg.pdf
If you plan to use GPU devices, make sure that your containers are nvidia-docker compatible.
Only the CUDA toolkit should be included on containers. Don't bundle NVIDIA drivers with the image.
For more information about nvidia-docker, see NVIDIA/nvidia-docker.

NEW QUESTION: 4
Which gives a user access to a system?
A. Service requirement
B. Service consumption
C. Service agreement
D. Service provision
Answer: D