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Role of Big Data in e-Healthcare Application for Managing a Large Amount of Data
Published in Manuel Cardona, Vijender Kumar Solanki, Cecilia E. García Cena, Internet of Medical Things, 2021
Meenu Gupta, Rachna Jain, Rachit Singhal, Jaspreet Singh
It is open source as well. In addition to functionality provided by Hadoop, it also provides SQL query support, graphical data processing, machine learning algorithms, etc. Algorithms which require multi-pass computations are not previously supported by Hadoop and MapReduce systems. With the development of Spark this was made possible, thus gaining an edge over others. It is 100 times faster when executing on memory than previous technologies. Higher level Application Programming Interfaces (APIs) results in optimized performance and also faster performance. Least costly shuffles are provided by Spark as compared to MapReduce. Spark is written in Scala programming language and runs on Java Virtual Machine. As of now, it supports applications to be built in Scala, Java, Python, Clojure and R. Often Spark is thought of as a modified version of Hadoop, but it is wrong to think of it as such. Using Apache Spark, an application was proposed [5] where a Location-Aware Analytics System was built using spatio-textual indexes and incremental algorithms accepted widely. In [27], the authors proposed a new method for gathering and analysing Twitter data, supported by a larger set of methodological which began to address some of its limitations.
Parallel Computing Programming Basics
Published in Vivek Kale, Parallel Computing Architectures and APIs, 2019
Scala is a new programming language developed by Martin Odersky and his team at EPFL and now supported by Typesafe. The name Scala is derived from Sca(lable) La(nguage) and is a multi paradigm language, incorporating Object Oriented approaches with Functional Programming. Like any other object-oriented language (such as Java, C#, or C++), Scala can exploit inheritance, polymorphism, and abstraction and encapsulation techniques. However, you can also develop solutions using purely functional programming principles in a similar manner to languages such as Haskell or Clojure; in such an approach, programs are written purely in terms of functions that take inputs and generate outputs without any side effects. Thus, it is possible to combine the best of both worlds when creating a software system: Object-oriented principles can be exploited to structure a solution, integrating functional aspects when appropriate.
Introduction
Published in Jay Gohil, Manan Shah, Application of Big Data in Petroleum Streams, 2022
Apache Storm is another major open-source big data tool that’s a distributed real-time and fault-tolerant processing system. It supports reliable processing of unbounded streams of data (data that’s ever-growing, has a beginning but no defined end). It’s written in Clojure (a dialect of Lisp programming language on the Java platform), and some of its major advantages of Storm include support for multiple language workability, support for JSON format protocols, sheer fast execution speed (million iterations per single second) and incredible scalability capability (while being fault-tolerant).
Data Stream Management for CPS-based Healthcare: A Contemporary Review
Published in IETE Technical Review, 2022
Sadhana Tiwari, Sonali Agarwal
It is a real-time computation system which can be used with any programming language. The storm is developed in Clojure programming language, which can execute around one million tuples per second per node, so it is highly scalable, and provides fast processing of jobs. Strom treats the entire process as an “event” rather than a series of small batches [70,73–75]. The storm is can be integrated with machine learning in a distributed environment, real-time scanning and many other scenarios, including increasing data rates. It is active at YARN, can be integrated into the Hadoop ecosystem. Storms have low latency and are suitable for including data as a single entity. The storm lacks direct support for wires. Its applications could be performed as directed acyclic graphs [76].
Deep Learning Techniques for OFDM Systems
Published in IETE Journal of Research, 2021
M. Meenalakshmi, Saurabh Chaturvedi, Vivek K. Dwivedi
MXNet is an efficient open-source library used for DL applications. It has a hybrid frontend to provide both flexibility and speed. It supports eight-language interfacing, including Julia, Scala, Java, Clojure, R, Python, C++, and Perl [43]. The computation graph declarations and imperative computation declarations are used for the architecture design. MXNet supports data parallelism, model parallelism, and distributed calculation.
Programming models and systems for Big Data analysis
Published in International Journal of Parallel, Emergent and Distributed Systems, 2019
Loris Belcastro, Fabrizio Marozzo, Domenico Talia
Storm is commonly used for real-time stream processing. An applications based on Storm can be written using Java, Clojure or any other programming languages by exploiting the Storm Multi-Language Protocol.