Cloud Computing Technology Algorithms Capabilities in Managing and Processing Big Data in Business Organizations: MapReduce, Hadoop, Parallel Programming
نویسندگان
چکیده مقاله:
The objective of this study is to verify the importance of the capabilities of cloud computing services in managing and analyzing big data in business organizations because the rapid development in the use of information technology in general and network technology in particular, has led to the trend of many organizations to make their applications available for use via electronic platforms hosted by various Companies on their servers or so-called cloud computing that have become an excellent opportunity to provide services efficiently and at low cost, but managing big data presents a definite challenge in the cloud space beginning with the processes of extracting, processing data, storing data and analyze it. Through this study, we dealt with the concept of cloud computing and its capabilities in business organizations. We also interpreted the notion of big data and its distinct characteristics and sources. Finally, the relationship between cloud computing with big data was also explained (extraction, storage, analysis).
منابع مشابه
Big Data Processing with Hadoop-MapReduce in Cloud Systems
Received Oct 10 th , 2012 Accepted Oct 31 th , 2012 Today, we‟re surrounded by data like oxygen. The exponential growth of data first presented challenges to cutting-edge businesses such as Google, Yahoo, Amazon, Microsoft, Facebook, Twitter etc. Data volumes to be processed by cloud applications are growing much faster than computing power. This growth demands new strategies for processing and...
متن کاملEfficient Big Data Processing in Hadoop MapReduce
This tutorial is motivated by the clear need of many organizations, companies, and researchers to deal with big data volumes efficiently. Examples include web analytics applications, scientific applications, and social networks. A popular data processing engine for big data is Hadoop MapReduce. Early versions of Hadoop MapReduce suffered from severe performance problems. Today, this is becoming...
متن کاملHadoop Mapreduce Framework in Big Data Analytics
As Hadoop is a Substantial scale, open source programming system committed to adaptable, disseminated, information concentrated processing. Hadoop [1] Mapreduce is a programming structure for effectively composing requisitions which prepare boundless measures of information (multi-terabyte information sets) inparallel on extensive bunches (many hubs) of merchandise fittings in a dependable, sho...
متن کاملBig Data with Cloud Computing: an insight on the computing environment, MapReduce, and programming frameworks
The term ‘Big Data’ has spread rapidly in the framework of Data Mining and Business Intelligence. This new scenario can be defined by means of those problems that cannot be effectively or efficiently addressed using the standard computing resources that we currently have. We must emphasize that Big Data does not just imply large volumes of data but also the necessity for scalability, i.e., to e...
متن کاملXHAMI - extended HDFS and MapReduce interface for Big Data image processing applications in cloud computing environments
Hadoop Distributed File System (HDFS) and MapReduce model have become popular technologies for large scale data organization and analysis. Existing model of data organization and processing in Hadoop using HDFS and MapReduce are ideally tailored for search and data parallel applications, for which there is no need of data dependency with its neighbouring/adjacent data. However, many scientific ...
متن کاملP2P-MapReduce: Parallel data processing in dynamic Cloud environments
MapReduce is a programming model for parallel data processing widely used in Cloud computing environments. Current MapReduce implementations are based on centralized master-slave architectures that do not cope well with dynamic Cloud infrastructures, like a Cloud of clouds, in which nodes may join and leave the network at high rates. We have designed an adaptive MapReduce framework, called P2P-...
متن کاملمنابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ذخیره در منابع من قبلا به منابع من ذحیره شده{@ msg_add @}
عنوان ژورنال
دوره 12 شماره 3
صفحات 100- 113
تاریخ انتشار 2020-09-01
با دنبال کردن یک ژورنال هنگامی که شماره جدید این ژورنال منتشر می شود به شما از طریق ایمیل اطلاع داده می شود.
میزبانی شده توسط پلتفرم ابری doprax.com
copyright © 2015-2023