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4 Layers of AWS Architecture a Quick Answer

I have collected real interview questions on AWS key architecture components. Those are S3, EC2, SQS, and SimpleDB. AWS is one of the most popular skills in the area of Cloud computing. Many companies are recruiting software developers to work on cloud computing.

AWS Key Architecture Components AWS is the top cloud platform. The knowledge of this helpful to learn other cloud platforms. Below are the questions asked in interviews recently.
What are the components involved in AWS?Amazon S3.With this, one can retrieve the key information which is occupied in creating cloud structural design, and the amount of produced information also can be stored in this component that is the consequence of the key specified.Amazon EC2. Helpful to run a large distributed system on the Hadoop cluster. Automatic parallelization and job scheduling can be achieved by this component.Amazon SQS. This component acts as a mediator between different controllers. Also worn for cushioning requirements those are obt…

Analytics on Fly - Read It

The basis for real-time analytics is to have all resources at disposal in the moment they are called for . So far, special materialized data structures, called cubes, have been created to efficiently serve analytical reports. Such cubes are based on a fixed number of dimensions along which analytical reports can define their result sets. Consequently, only a particular set of reports can be served by one cube. If other dimensions are needed, a new cube has to be created or existing ones have to be extended. In the worst case, a linear increase in the number of dimensions of a cube can result in an exponential growth of its storage requirements. Extending a cube can result in a deteriorating performance of those reports already using it. The decision to extend a cube or build a new one has to be considered carefully. 

In any case, a wide variety of cubes may be built during the lifetime of a system to serve reporting, thus increasing storage requirements and also maintenance efforts.

Instead of working with a predefined set of reports, business users should be able to formulate ad-hoc reports. Their playground should be the entire set of data the company owns, possibly including further data from external sources. Assuming a fast in-memory database, no more pre-computed materialized data structures are needed. As soon as changes to data are committed to the database, they will be visible for reporting. 

The preparation and conversion steps of data if still needed for reports are done during query execution and computations take place on the fly. Computation on the fly during reporting on the basis of cubes that do not store data, but only provide the interface for reporting, solves a problem that has existed up to now and allows for performance optimization of all analytical reports likewise


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