Data-intensive computing this approach is considered suitable for data-intensive computing and problems which are “embarrassingly parallel”, i.e. where it is relatively easy to separate the problem into a number of parallel tasks and there is no dependency or communication required between the tasks other than overall management of the tasks. These types of data processing problems are inherently adaptable to various forms of distributed computing including clusters, data grids, and cloud computing. Several common characteristics of data-intensive computing systems distinguish them from other forms of computing: A variety of system architectures have been implemented for data-intensive computing and large-scale data analysis applications
Stub (distributed computing) Stub (distributed computing) A stub in distributed computing is a piece of code that converts parameters passed between client and server during a remote procedure call (RPC). The main idea of an RPC is to allow a local computer (client) to remotely call procedures on a different computer (server). The client and server use different address spaces, so parameters used in a function (procedure) call have to be converted, otherwise the values of those parameters could not be used, because pointers to parameters in one computer's memory would point to different data on the other computer. The client and server