Abstract
The homogeneous data structure ‘train' and the heterogeneous data structure ‘atrain' are the fundamental, very powerful dynamic and flexible data structures, being the first data structures introduced exclusively for big data. Thus ‘Data Structures for Big Data' is to be regarded as a new subject in Big Data Science, not just as a new topic, considering the explosive momentum of the big data. Based upon the notion of the big data structures train and atrain, the author introduces the useful data structures for the programmers working with big data which are: homogeneous stacks ‘train stack' and ‘rT-coach stack', heterogeneous stacks ‘atrain stack' and ‘rA-coach stack', homogeneous queues ‘train queue' and ‘rT-coach queue', heterogeneous queues ‘atrain queue' and ‘rA-coach queue', homogeneous binary trees ‘train binary tree' and ‘rT-coach binary tree', heterogeneous binary trees ‘atrain binary tree' and ‘rA-coach binary tree', homogeneous trees ‘train tree' and ‘rT-coach tree', heterogeneous trees ‘atrain tree' and ‘rA-coach tree', to enrich the subject ‘Data Structures for Big Data' for big data science.
TopPreliminaries Of The Data Structure R-Atrain For Big Data
The data structure ‘r-Train’ (‘train’, in short) where r is a natural number is a new kind of powerful robust data structure which can store homogeneous big data dynamically in a flexible way. However, the heterogeneous data structure ‘r-Atrain’ (‘atrain’, in short) where r is a natural number is a new kind of powerful robust data structure which can store heterogeneous big data of any 4V dynamically in a flexible way. In (Biswas, 2015a) a detailed study of the two fundamental big data structures train and atrain is available with the detailed description of the distributed system ADS for big data, an infinitely scalable architecture to deal with big data of any 4Vs. However, for the sake of preliminaries of this chapter, the heterogeneous data structure r-atrain for big data is reproduced in brief from (Biswas, 2015a), before we start for the actual content here. For details of train and atrain, one could see (Biswas, 2015a).