Skew Handling Technique for Scheduling Huge Data Mapper with High End Reducers in MapReduce Programming Model

2020 ◽  
pp. 331-339
Author(s):  
B. Arputhamary
Keyword(s):  
Programming Model ◽  
Huge Data ◽  
Handling Technique

scholarly journals A distributed big data library extending Java 8

2017 ◽  
Vol 7 (1.1) ◽  
pp. 237
Author(s):  
MD. A R Quadri ◽  
B. Sruthi ◽  
A. D. SriRam ◽  
B. Lavanya
Keyword(s):  
Big Data ◽  
Distributed Computing ◽  
Programming Model ◽  
Large Data ◽  
Large Data Sets ◽  
Data Sets ◽  
Distributed Environment ◽  
Multiple Systems ◽  
Huge Data ◽  
Distributed Streams

Java is one of the finest language for big data because of its write once and run anywhere nature. The new release of java 8 introduced few strategies like lambda expressions and streams which are helpful for parallel computing. Though these new strategies helps in extracting, sorting and filtering data from collections and arrays, still there are problems with it. Streams cannot properly process with the large data sets like big data. Also, there are few problems associated while executing in distributed environment. The new streams introduced in java are restricted to computations inside the single system there is no method for distributed computing over multiple systems. And streams store data in their memory and therefore cannot support huge data sets. Now, this paper cope with java 8 behalf of massive data and deed in distributed environment by providing extensions to the Programming model with distributed streams. The distributed computing of large data programming models may be consummated by introducing distributed stream frameworks.

scholarly journals Importance of MapReduce for Big Data Applications: A Survey

2018 ◽  
Vol 7 (1) ◽  
pp. 112-118
Author(s):  
M. Durairaj ◽  
T. S. Poornappriya
Keyword(s):  
Programming Model ◽  
Wide Scope ◽  
Mapreduce Framework ◽  
Huge Data ◽  
Big Data Applications ◽  
Wide Range ◽  
High Elasticity ◽  
Parallel Programming Model ◽  
Computing Environments ◽  
Practical Model

Significant regard for MapReduce framework has been trapped by a wide range of areas. It is presently a practical model for data-focused applications because of its basic interface of programming, high elasticity, and capacity to withstand the subjection to defects. Additionally, it is fit for preparing a high extent of data in Distributed Computing environments (DCE). MapReduce, on various events, has turned out to be material to a wide scope of areas. MapReduce is a parallel programming model and a related usage presented by Google. In the programming model, a client determines the calculation by two capacities, Map and Reduce. The basic MapReduce library consequently parallelizes the calculation and handles muddled issues like data dispersion, load adjusting, and adaptation to non-critical failure. Huge data spread crosswise over numerous machines, need to parallelize. Moves the data, and gives booking, adaptation to non-critical failure. A writing survey on the MapReduce programming in different areas has completed in this paper. An examination course has been distinguished by utilizing a writing audit.

A Linear Programming Model for Product Mix Profit Maximization in A Small Medium Enterprise Company

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
S Mohd Baki ◽  
Jack Kie Cheng
Keyword(s):  
Linear Programming ◽  
Production Planning ◽  
Business Performance ◽  
Programming Model ◽  
Profit Maximization ◽  
Optimal Level ◽  
Linear Programming Model ◽  
Product Mix ◽  
Small Medium Enterprises ◽  
Medium Enterprises

Production planning is often challenging for small medium enterprises (SMEs) company. Most of the SMEs are having difficulty in determining the optimal level of the production output which can affect their business performance. Product mix optimization is one of the main key for production planning. Many company have used linear programming model in determining the optimal combination of various products that need to be produced in order to maximize profit. Thus, this study aims for profit maximization of a SME company in Malaysia by using linear programming model. The purposes of this study are to identify the current process in the production line and to formulate a linear programming model that would suggest a viable product mix to ensure optimum profitability for the company. ABC Sdn Bhd is selected as a case study company for product mix profit maximization study. Some conclusive observations have been drawn and recommendations have been suggested. This study will provide the company and other companies, particularly in Malaysia, an exposure of linear programming method in making decisions to determine the maximum profit for different product mix.

Power Generation for India with Higher Efficiency

2018 ◽  
Vol 6 (7) ◽  
pp. 267
Author(s):  
Umeshkannan P ◽  
Muthurajan KG
Keyword(s):  
Power Generation ◽  
Objective Function ◽  
Fossil Fuels ◽  
Programming Model ◽  
Developed Countries ◽  
Power Requirement ◽  
Average Efficiency ◽  
Potential Demand ◽  
The Developed Countries ◽  
Developed Nations

The developed countries are consuming more amount of energy in all forms including electricity continuously with advanced technologies.  Developing  nation’s  energy usage trend rises quickly but very less in comparison with their population and  their  method of generating power is not  seems  to  be  as  advanced  as  developed  nations. The   objective   function   of   this   linear   programming model is to maximize the average efficiency of power generation inIndia for 2020 by giving preference to energy efficient technologies. This model is subjected to various constraints like potential, demand, running cost and Hydrogen / Carbon ratio, isolated load, emission and already installed capacities. Tora package is used to solve this linear program. Coal,  Gas,  Hydro  and  Nuclear  sources can are  supply around 87 %  of  power  requirement .  It’s concluded that we can produce power  at  overall  efficiency  of  37%  while  meeting  a  huge demand  of  13,00,000  GWh  of  electricity.  The objective function shows the scenario of highaverage efficiency with presence of 9% renewables. Maximum value   is   restricted   by   low   renewable   source’s efficiencies, emission constraints on fossil fuels and cost restriction on some of efficient technologies. This    model    shows    that    maximum    18%    of    total requirement   can   be   met   by   renewable itself which reduces average efficiency to 35.8%.   Improving technologies  of  renewable  sources  and  necessary  capacity addition  to  them in  regular  interval  will  enhance  their  role and existence against fossil fuels in future. The work involves conceptualizing, modeling, gathering information for data’s to be used in model for problem solving and presenting different scenarios for same objective.

PENELITIAN ASPEK PERKOTAAN DUMAI DAN BITUNG DAN KEMUNGKINANNYA SEBAGAI LOKASI KAWASAN EKONOMI KHUSUS DI INDONESIA

2012 ◽  
Vol 11 (1) ◽  
Author(s):  
CB Herman Edyanto
Keyword(s):  
Programming Model ◽  
National Income ◽  
Special Economic Zone ◽  
Good Prospect ◽  
Economic Activities ◽  
Processing Industry ◽  
North Sulawesi ◽  
Job Opportunity ◽  
Economic Zone ◽  
The Government

Special Economic Zone has been introduced as a new approach in Indonesia for regional development purposes on the basic of economic activities concentration. Some countries have run such project as part of national income and thus opening new job opportunity for the local people. A concept for its development need to be established since it also affects to the government’s expenditure. This is a chance for the government to open mind in creating new investment from other countries to Indonesia. Two cities have been chosen as cases of study namely Bitung – north Sulawesi Province and Dumai – Riau Province. The first is known as fish processing industry city whereas the second one is known as CPO processing industry city. This study has proved that Dumai has a good prospect as a special economic zone based on the application of Powersim dynamic programming model for its analysis.

Performance Comparison among Meta Classifier Algorithms in WEKA

2019 ◽  
Vol 1 (2) ◽  
pp. 106-112
Author(s):  
Nur Amiratun Nazihah Roslan ◽  
Hairulnizam Mahdin ◽  
Shahreen Kasim
Keyword(s):  
Social Networking ◽  
Performance Comparison ◽  
Data Availability ◽  
Data Mining Tool ◽  
Huge Data ◽  
Technology Advancement ◽  
The Social ◽  
The World ◽  
Media Platform ◽  
Mining Tool

With the rise of social networking approach, there has been a surge of users generated content all over the world and with that in an era where technology advancement are up to the level where it could put us in a step ahead of pathogens and germination of diseases, we couldn’t help but to take advantage of that advancement and provide an early precaution measures to overcome it. Twitter on the other hand are one of the social media platform that provides access towards a huge data availability. To manipulate those data and transform it into an important information that could be used in many different scope that could help improve people’s life for the better. In this paper, we gather all algorithm that are available inside Meta Classifier to compare between them on which algorithm suited the most with the dengue fever dataset. This research are using WEKA as the data mining tool for data analyzation.

Ochrona dziedzictwa kulturowego a działania na dużych szybkozmiennych zbiorach danych – perspektywa kryminologiczna

2019 ◽  
pp. 5-22
Author(s):  
Szymon Buczyński
Keyword(s):  
New Technology ◽  
Big Data Analytics ◽  
Technological Innovations ◽  
Cultural Organizations ◽  
Econometric Methods ◽  
The Arts ◽  
Huge Data ◽  
Wide Range ◽  
Share Data ◽  
Processing Techniques

Recent technological revolutions in data and communication systemsenable us to generate and share data much faster than ever before. Sophisticated data tools aim to improve knowledge and boost confdence. That technological tools will only get better and user-friendlier over the years, big datacan be considered an important tool for the arts and culture sector. Statistical analysis, econometric methods or data mining techniques could pave theway towards better understanding of the mechanisms occurring on the artmarket. Moreover crime reduction and prevention challenges in today’sworld are becoming increasingly complex and are in need of a new techniquethat can handle the vast amount of information that is being generated. Thisarticle provides an examination of a wide range of new technological innovations (IT) that have applications in the areas of culture preservation andheritage protection. The author provides a description of recent technological innovations, summarize the available research on the extent of adoptionon selected examples, and then review the available research on the eachform of new technology. Furthermore the aim of this paper is to explore anddiscuss how big data analytics affect innovation and value creation in cultural organizations and shape consumer behavior in cultural heritage, arts andcultural industries. This paper discusses also the likely impact of big dataanalytics on criminological research and theory. Digital criminology supports huge data base in opposition to conventional data processing techniques which are not only in suffcient but also out dated. This paper aims atclosing a gap in the academic literature showing the contribution of a bigdata approach in cultural economics, policy and management both froma theoretical and practice-based perspective. This work is also a startingpoint for further research.

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