Hadoop Data Processing And Modelling

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Hadoop: Data Processing and Modelling

Garry Turkington,Tanmay Deshpande,Sandeep Karanth
Hadoop Data Processing and Modelling Book PDF

Author : Garry Turkington,Tanmay Deshpande,Sandeep Karanth
Publisher : Packt Publishing Ltd
Page : 979 pages
File Size : 50,7 Mb
Release : 2016-08-31
Category : Computers
ISBN : 9781787120457

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Hadoop: Data Processing and Modelling by Garry Turkington,Tanmay Deshpande,Sandeep Karanth Pdf

Unlock the power of your data with Hadoop 2.X ecosystem and its data warehousing techniques across large data sets About This Book Conquer the mountain of data using Hadoop 2.X tools The authors succeed in creating a context for Hadoop and its ecosystem Hands-on examples and recipes giving the bigger picture and helping you to master Hadoop 2.X data processing platforms Overcome the challenging data processing problems using this exhaustive course with Hadoop 2.X Who This Book Is For This course is for Java developers, who know scripting, wanting a career shift to Hadoop - Big Data segment of the IT industry. So if you are a novice in Hadoop or an expert, this book will make you reach the most advanced level in Hadoop 2.X. What You Will Learn Best practices for setup and configuration of Hadoop clusters, tailoring the system to the problem at hand Integration with relational databases, using Hive for SQL queries and Sqoop for data transfer Installing and maintaining Hadoop 2.X cluster and its ecosystem Advanced Data Analysis using the Hive, Pig, and Map Reduce programs Machine learning principles with libraries such as Mahout and Batch and Stream data processing using Apache Spark Understand the changes involved in the process in the move from Hadoop 1.0 to Hadoop 2.0 Dive into YARN and Storm and use YARN to integrate Storm with Hadoop Deploy Hadoop on Amazon Elastic MapReduce and Discover HDFS replacements and learn about HDFS Federation In Detail As Marc Andreessen has said “Data is eating the world,” which can be witnessed today being the age of Big Data, businesses are producing data in huge volumes every day and this rise in tide of data need to be organized and analyzed in a more secured way. With proper and effective use of Hadoop, you can build new-improved models, and based on that you will be able to make the right decisions. The first module, Hadoop beginners Guide will walk you through on understanding Hadoop with very detailed instructions and how to go about using it. Commands are explained using sections called “What just happened” for more clarity and understanding. The second module, Hadoop Real World Solutions Cookbook, 2nd edition, is an essential tutorial to effectively implement a big data warehouse in your business, where you get detailed practices on the latest technologies such as YARN and Spark. Big data has become a key basis of competition and the new waves of productivity growth. Hence, once you get familiar with the basics and implement the end-to-end big data use cases, you will start exploring the third module, Mastering Hadoop. So, now the question is if you need to broaden your Hadoop skill set to the next level after you nail the basics and the advance concepts, then this course is indispensable. When you finish this course, you will be able to tackle the real-world scenarios and become a big data expert using the tools and the knowledge based on the various step-by-step tutorials and recipes. Style and approach This course has covered everything right from the basic concepts of Hadoop till you master the advance mechanisms to become a big data expert. The goal here is to help you learn the basic essentials using the step-by-step tutorials and from there moving toward the recipes with various real-world solutions for you. It covers all the important aspects of Hadoop from system designing and configuring Hadoop, machine learning principles with various libraries with chapters illustrated with code fragments and schematic diagrams. This is a compendious course to explore Hadoop from the basics to the most advanced techniques available in Hadoop 2.X.

Data Processing and Modeling with Hadoop

Vinicius Aquino do Vale
Data Processing and Modeling with Hadoop Book PDF

Author : Vinicius Aquino do Vale
Publisher : BPB Publications
Page : 196 pages
File Size : 51,8 Mb
Release : 2021-10-12
Category : Computers
ISBN : 9789391392284

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Data Processing and Modeling with Hadoop by Vinicius Aquino do Vale Pdf

Understand data in a simple way using a data lake. KEY FEATURES ● In-depth practical demonstration of Hadoop/Yarn concepts with numerous examples. ● Includes graphical illustrations and visual explanations for Hadoop commands and parameters. ● Includes details of dimensional modeling and Data Vault modeling. ● Includes details of how to create and define a structure to a data lake. DESCRIPTION The book 'Data Processing and Modeling with Hadoop' explains how a distributed system works and its benefits in the big data era in a straightforward and clear manner. After reading the book, you will be able to plan and organize projects involving a massive amount of data. The book describes the standards and technologies that aid in data management and compares them to other technology business standards. The reader receives practical guidance on how to segregate and separate data into zones, as well as how to develop a model that can aid in data evolution. It discusses security and the measures that are utilized to reduce the impact of security. Self-service analytics, Data Lake, Data Vault 2.0, and Data Mesh are discussed in the book. After reading this book, the reader will have a thorough understanding of how to structure a data lake, as well as the ability to plan, organize, and carry out the implementation of a data-driven business with full governance and security. WHAT YOU WILL LEARN ● Learn the basics of components to the Hadoop Ecosystem. ● Understand the structure, files, and zones of a Data Lake. ● Learn to implement the security part of the Hadoop Ecosystem. ● Learn to work with the Data Vault 2.0 modeling. ● Learn to develop a strategy to define good governance. ● Learn new tools to work with Data and Big Data WHO THIS BOOK IS FOR This book caters to big data developers, technical specialists, consultants, and students who want to build good proficiency in big data. Knowing basic SQL concepts, modeling, and development would be good, although not mandatory. TABLE OF CONTENTS 1. Understanding the Current Moment 2. Defining the Zones 3. The Importance of Modeling 4. Massive Parallel Processing 5. Doing ETL/ELT 6. A Little Governance 7. Talking About Security 8. What Are the Next Steps?

Hadoop Application Architectures

Mark Grover,Ted Malaska,Jonathan Seidman,Gwen Shapira
Hadoop Application Architectures Book PDF

Author : Mark Grover,Ted Malaska,Jonathan Seidman,Gwen Shapira
Publisher : "O'Reilly Media, Inc."
Page : 399 pages
File Size : 41,9 Mb
Release : 2015-06-30
Category : Computers
ISBN : 9781491900079

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Hadoop Application Architectures by Mark Grover,Ted Malaska,Jonathan Seidman,Gwen Shapira Pdf

Get expert guidance on architecting end-to-end data management solutions with Apache Hadoop. While many sources explain how to use various components in the Hadoop ecosystem, this practical book takes you through architectural considerations necessary to tie those components together into a complete tailored application, based on your particular use case. To reinforce those lessons, the book’s second section provides detailed examples of architectures used in some of the most commonly found Hadoop applications. Whether you’re designing a new Hadoop application, or planning to integrate Hadoop into your existing data infrastructure, Hadoop Application Architectures will skillfully guide you through the process. This book covers: Factors to consider when using Hadoop to store and model data Best practices for moving data in and out of the system Data processing frameworks, including MapReduce, Spark, and Hive Common Hadoop processing patterns, such as removing duplicate records and using windowing analytics Giraph, GraphX, and other tools for large graph processing on Hadoop Using workflow orchestration and scheduling tools such as Apache Oozie Near-real-time stream processing with Apache Storm, Apache Spark Streaming, and Apache Flume Architecture examples for clickstream analysis, fraud detection, and data warehousing

Data Processing and Modeling with Hadoop

Vinicius Aquino Do Vale
Data Processing and Modeling with Hadoop Book PDF

Author : Vinicius Aquino Do Vale
Publisher : Unknown
Page : 198 pages
File Size : 43,6 Mb
Release : 2021
Category : Apache Hadoop
ISBN : OCLC:1314098665

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Data Processing and Modeling with Hadoop by Vinicius Aquino Do Vale Pdf

The book describes the standards and technologies that aid in data management and compares them to other technology business standards. The reader receives practical guidance on how to segregate and separate data into zones, as well as how to develop a model that can aid in data evolution. --

Modeling and Processing for Next-Generation Big-Data Technologies

Fatos Xhafa,Leonard Barolli,Admir Barolli,Petraq Papajorgji
Modeling and Processing for Next Generation Big Data Technologies Book PDF

Author : Fatos Xhafa,Leonard Barolli,Admir Barolli,Petraq Papajorgji
Publisher : Springer
Page : 524 pages
File Size : 42,5 Mb
Release : 2014-11-04
Category : Technology & Engineering
ISBN : 9783319091778

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Modeling and Processing for Next-Generation Big-Data Technologies by Fatos Xhafa,Leonard Barolli,Admir Barolli,Petraq Papajorgji Pdf

This book covers the latest advances in Big Data technologies and provides the readers with a comprehensive review of the state-of-the-art in Big Data processing, analysis, analytics, and other related topics. It presents new models, algorithms, software solutions and methodologies, covering the full data cycle, from data gathering to their visualization and interaction, and includes a set of case studies and best practices. New research issues, challenges and opportunities shaping the future agenda in the field of Big Data are also identified and presented throughout the book, which is intended for researchers, scholars, advanced students, software developers and practitioners working at the forefront in their field.

Modern Big Data Processing with Hadoop

V Naresh Kumar,Prashant Shindgikar
Modern Big Data Processing with Hadoop Book PDF

Author : V Naresh Kumar,Prashant Shindgikar
Publisher : Packt Publishing Ltd
Page : 390 pages
File Size : 40,8 Mb
Release : 2018-03-30
Category : Computers
ISBN : 9781787128811

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Modern Big Data Processing with Hadoop by V Naresh Kumar,Prashant Shindgikar Pdf

A comprehensive guide to design, build and execute effective Big Data strategies using Hadoop Key Features -Get an in-depth view of the Apache Hadoop ecosystem and an overview of the architectural patterns pertaining to the popular Big Data platform -Conquer different data processing and analytics challenges using a multitude of tools such as Apache Spark, Elasticsearch, Tableau and more -A comprehensive, step-by-step guide that will teach you everything you need to know, to be an expert Hadoop Architect Book Description The complex structure of data these days requires sophisticated solutions for data transformation, to make the information more accessible to the users.This book empowers you to build such solutions with relative ease with the help of Apache Hadoop, along with a host of other Big Data tools. This book will give you a complete understanding of the data lifecycle management with Hadoop, followed by modeling of structured and unstructured data in Hadoop. It will also show you how to design real-time streaming pipelines by leveraging tools such as Apache Spark, and build efficient enterprise search solutions using Elasticsearch. You will learn to build enterprise-grade analytics solutions on Hadoop, and how to visualize your data using tools such as Apache Superset. This book also covers techniques for deploying your Big Data solutions on the cloud Apache Ambari, as well as expert techniques for managing and administering your Hadoop cluster. By the end of this book, you will have all the knowledge you need to build expert Big Data systems. What you will learn Build an efficient enterprise Big Data strategy centered around Apache Hadoop Gain a thorough understanding of using Hadoop with various Big Data frameworks such as Apache Spark, Elasticsearch and more Set up and deploy your Big Data environment on premises or on the cloud with Apache Ambari Design effective streaming data pipelines and build your own enterprise search solutions Utilize the historical data to build your analytics solutions and visualize them using popular tools such as Apache Superset Plan, set up and administer your Hadoop cluster efficiently Who this book is for This book is for Big Data professionals who want to fast-track their career in the Hadoop industry and become an expert Big Data architect. Project managers and mainframe professionals looking forward to build a career in Big Data Hadoop will also find this book to be useful. Some understanding of Hadoop is required to get the best out of this book.

Hands-On Big Data Modeling

James Lee,Tao Wei,Suresh Kumar Mukhiya
Hands On Big Data Modeling Book PDF

Author : James Lee,Tao Wei,Suresh Kumar Mukhiya
Publisher : Packt Publishing Ltd
Page : 293 pages
File Size : 47,9 Mb
Release : 2018-11-30
Category : Computers
ISBN : 9781788626088

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Hands-On Big Data Modeling by James Lee,Tao Wei,Suresh Kumar Mukhiya Pdf

Solve all big data problems by learning how to create efficient data models Key FeaturesCreate effective models that get the most out of big dataApply your knowledge to datasets from Twitter and weather data to learn big dataTackle different data modeling challenges with expert techniques presented in this bookBook Description Modeling and managing data is a central focus of all big data projects. In fact, a database is considered to be effective only if you have a logical and sophisticated data model. This book will help you develop practical skills in modeling your own big data projects and improve the performance of analytical queries for your specific business requirements. To start with, you’ll get a quick introduction to big data and understand the different data modeling and data management platforms for big data. Then you’ll work with structured and semi-structured data with the help of real-life examples. Once you’ve got to grips with the basics, you’ll use the SQL Developer Data Modeler to create your own data models containing different file types such as CSV, XML, and JSON. You’ll also learn to create graph data models and explore data modeling with streaming data using real-world datasets. By the end of this book, you’ll be able to design and develop efficient data models for varying data sizes easily and efficiently. What you will learnGet insights into big data and discover various data modelsExplore conceptual, logical, and big data modelsUnderstand how to model data containing different file typesRun through data modeling with examples of Twitter, Bitcoin, IMDB and weather data modelingCreate data models such as Graph Data and Vector SpaceModel structured and unstructured data using Python and RWho this book is for This book is great for programmers, geologists, biologists, and every professional who deals with spatial data. If you want to learn how to handle GIS, GPS, and remote sensing data, then this book is for you. Basic knowledge of R and QGIS would be helpful.

High-Performance Modelling and Simulation for Big Data Applications

Joanna Kołodziej,Horacio González-Vélez
High Performance Modelling and Simulation for Big Data Applications Book PDF

Author : Joanna Kołodziej,Horacio González-Vélez
Publisher : Springer
Page : 364 pages
File Size : 47,9 Mb
Release : 2019-03-25
Category : Computers
ISBN : 9783030162726

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High-Performance Modelling and Simulation for Big Data Applications by Joanna Kołodziej,Horacio González-Vélez Pdf

This open access book was prepared as a Final Publication of the COST Action IC1406 “High-Performance Modelling and Simulation for Big Data Applications (cHiPSet)“ project. Long considered important pillars of the scientific method, Modelling and Simulation have evolved from traditional discrete numerical methods to complex data-intensive continuous analytical optimisations. Resolution, scale, and accuracy have become essential to predict and analyse natural and complex systems in science and engineering. When their level of abstraction raises to have a better discernment of the domain at hand, their representation gets increasingly demanding for computational and data resources. On the other hand, High Performance Computing typically entails the effective use of parallel and distributed processing units coupled with efficient storage, communication and visualisation systems to underpin complex data-intensive applications in distinct scientific and technical domains. It is then arguably required to have a seamless interaction of High Performance Computing with Modelling and Simulation in order to store, compute, analyse, and visualise large data sets in science and engineering. Funded by the European Commission, cHiPSet has provided a dynamic trans-European forum for their members and distinguished guests to openly discuss novel perspectives and topics of interests for these two communities. This cHiPSet compendium presents a set of selected case studies related to healthcare, biological data, computational advertising, multimedia, finance, bioinformatics, and telecommunications.

Big Data Processing with Hadoop

T. Revathi,K. Muneeswaran,M. Blessa Binolin Pepsi
Big Data Processing with Hadoop Book PDF

Author : T. Revathi,K. Muneeswaran,M. Blessa Binolin Pepsi
Publisher : Engineering Science Reference
Page : 0 pages
File Size : 48,5 Mb
Release : 2018-11-16
Category : Computers
ISBN : 1522537929

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Big Data Processing with Hadoop by T. Revathi,K. Muneeswaran,M. Blessa Binolin Pepsi Pdf

Due to the increasing availability of affordable internet services, the number of users, and the need for a wider range of multimedia-based applications, internet usage is on the rise. With so many users and such a large amount of data, the requirements of analyzing large data sets leads to the need for further advancements to information processing. Big Data Processing With Hadoop is an essential reference source that discusses possible solutions for millions of users working with a variety of data applications, who expect fast turnaround responses, but encounter issues with processing data at the rate it comes in. Featuring research on topics such as market basket analytics, scheduler load simulator, and writing YARN applications, this book is ideally designed for IoT professionals, students, and engineers seeking coverage on many of the real-world challenges regarding big data.

Large Scale and Big Data

Sherif Sakr,Mohamed Gaber
Large Scale and Big Data Book PDF

Author : Sherif Sakr,Mohamed Gaber
Publisher : CRC Press
Page : 640 pages
File Size : 45,7 Mb
Release : 2014-06-25
Category : Computers
ISBN : 9781466581500

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Large Scale and Big Data by Sherif Sakr,Mohamed Gaber Pdf

Large Scale and Big Data: Processing and Management provides readers with a central source of reference on the data management techniques currently available for large-scale data processing. Presenting chapters written by leading researchers, academics, and practitioners, it addresses the fundamental challenges associated with Big Data processing tools and techniques across a range of computing environments. The book begins by discussing the basic concepts and tools of large-scale Big Data processing and cloud computing. It also provides an overview of different programming models and cloud-based deployment models. The book’s second section examines the usage of advanced Big Data processing techniques in different domains, including semantic web, graph processing, and stream processing. The third section discusses advanced topics of Big Data processing such as consistency management, privacy, and security. Supplying a comprehensive summary from both the research and applied perspectives, the book covers recent research discoveries and applications, making it an ideal reference for a wide range of audiences, including researchers and academics working on databases, data mining, and web scale data processing. After reading this book, you will gain a fundamental understanding of how to use Big Data-processing tools and techniques effectively across application domains. Coverage includes cloud data management architectures, big data analytics visualization, data management, analytics for vast amounts of unstructured data, clustering, classification, link analysis of big data, scalable data mining, and machine learning techniques.

Artificial Intelligence in Data and Big Data Processing

Ngoc Hoang Thanh Dang,Yu-Dong Zhang,João Manuel R. S. Tavares,Bo-Hao Chen
Artificial Intelligence in Data and Big Data Processing Book PDF

Author : Ngoc Hoang Thanh Dang,Yu-Dong Zhang,João Manuel R. S. Tavares,Bo-Hao Chen
Publisher : Springer Nature
Page : 738 pages
File Size : 52,5 Mb
Release : 2022-05-18
Category : Computers
ISBN : 9783030976101

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Artificial Intelligence in Data and Big Data Processing by Ngoc Hoang Thanh Dang,Yu-Dong Zhang,João Manuel R. S. Tavares,Bo-Hao Chen Pdf

The book presents studies related to artificial intelligence (AI) and its applications to process and analyze data and big data to create machines or software that can better understand business behavior, industry activities, and human health. The studies were presented at “The 2021 International Conference on Artificial Intelligence and Big Data in Digital Era” (ICABDE 2021), which was held in Ho Chi Minh City, Vietnam, during December 18-19, 2021. The studies are pointing toward the famous slogan in technology “Make everything smarter,” i.e., creating machines that can understand and can communicate with humans, and they must act like humans in different aspects such as vision, communication, thinking, feeling, and acting. “A computer would deserve to be called intelligent if it could deceive a human into believing that it was human” —Alan Turing

Big Data Processing Using Spark in Cloud

Mamta Mittal,Valentina E. Balas,Lalit Mohan Goyal,Raghvendra Kumar
Big Data Processing Using Spark in Cloud Book PDF

Author : Mamta Mittal,Valentina E. Balas,Lalit Mohan Goyal,Raghvendra Kumar
Publisher : Springer
Page : 275 pages
File Size : 42,7 Mb
Release : 2018-06-16
Category : Computers
ISBN : 9789811305504

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Big Data Processing Using Spark in Cloud by Mamta Mittal,Valentina E. Balas,Lalit Mohan Goyal,Raghvendra Kumar Pdf

The book describes the emergence of big data technologies and the role of Spark in the entire big data stack. It compares Spark and Hadoop and identifies the shortcomings of Hadoop that have been overcome by Spark. The book mainly focuses on the in-depth architecture of Spark and our understanding of Spark RDDs and how RDD complements big data’s immutable nature, and solves it with lazy evaluation, cacheable and type inference. It also addresses advanced topics in Spark, starting with the basics of Scala and the core Spark framework, and exploring Spark data frames, machine learning using Mllib, graph analytics using Graph X and real-time processing with Apache Kafka, AWS Kenisis, and Azure Event Hub. It then goes on to investigate Spark using PySpark and R. Focusing on the current big data stack, the book examines the interaction with current big data tools, with Spark being the core processing layer for all types of data. The book is intended for data engineers and scientists working on massive datasets and big data technologies in the cloud. In addition to industry professionals, it is helpful for aspiring data processing professionals and students working in big data processing and cloud computing environments.

Machine Learning Models and Algorithms for Big Data Classification

Shan Suthaharan
Machine Learning Models and Algorithms for Big Data Classification Book PDF

Author : Shan Suthaharan
Publisher : Springer
Page : 359 pages
File Size : 48,6 Mb
Release : 2015-10-20
Category : Business & Economics
ISBN : 9781489976413

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Machine Learning Models and Algorithms for Big Data Classification by Shan Suthaharan Pdf

This book presents machine learning models and algorithms to address big data classification problems. Existing machine learning techniques like the decision tree (a hierarchical approach), random forest (an ensemble hierarchical approach), and deep learning (a layered approach) are highly suitable for the system that can handle such problems. This book helps readers, especially students and newcomers to the field of big data and machine learning, to gain a quick understanding of the techniques and technologies; therefore, the theory, examples, and programs (Matlab and R) presented in this book have been simplified, hardcoded, repeated, or spaced for improvements. They provide vehicles to test and understand the complicated concepts of various topics in the field. It is expected that the readers adopt these programs to experiment with the examples, and then modify or write their own programs toward advancing their knowledge for solving more complex and challenging problems. The presentation format of this book focuses on simplicity, readability, and dependability so that both undergraduate and graduate students as well as new researchers, developers, and practitioners in this field can easily trust and grasp the concepts, and learn them effectively. It has been written to reduce the mathematical complexity and help the vast majority of readers to understand the topics and get interested in the field. This book consists of four parts, with the total of 14 chapters. The first part mainly focuses on the topics that are needed to help analyze and understand data and big data. The second part covers the topics that can explain the systems required for processing big data. The third part presents the topics required to understand and select machine learning techniques to classify big data. Finally, the fourth part concentrates on the topics that explain the scaling-up machine learning, an important solution for modern big data problems.

Security and Privacy Trends in Cloud Computing and Big Data

Muhammad Imran Tariq,Valentina Emilia Balas,Shahzadi Tayyaba
Security and Privacy Trends in Cloud Computing and Big Data Book PDF

Author : Muhammad Imran Tariq,Valentina Emilia Balas,Shahzadi Tayyaba
Publisher : CRC Press
Page : 222 pages
File Size : 55,9 Mb
Release : 2022-06-07
Category : Computers
ISBN : 9781000583700

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Security and Privacy Trends in Cloud Computing and Big Data by Muhammad Imran Tariq,Valentina Emilia Balas,Shahzadi Tayyaba Pdf

It is essential for an organization to know before involving themselves in cloud computing and big data, what are the key security requirements for applications and data processing. Big data and cloud computing are integrated together in practice. Cloud computing offers massive storage, high computation power, and distributed capability to support processing of big data. In such an integrated environment the security and privacy concerns involved in both technologies become combined. This book discusses these security and privacy issues in detail and provides necessary insights into cloud computing and big data integration. It will be useful in enhancing the body of knowledge concerning innovative technologies offered by the research community in the area of cloud computing and big data. Readers can get a better understanding of the basics of cloud computing, big data, and security mitigation techniques to deal with current challenges as well as future research opportunities.

Big Data Processing With Hadoop

Revathi, T.,Muneeswaran, K.,Blessa Binolin Pepsi, M.
Big Data Processing With Hadoop Book PDF

Author : Revathi, T.,Muneeswaran, K.,Blessa Binolin Pepsi, M.
Publisher : IGI Global
Page : 244 pages
File Size : 48,7 Mb
Release : 2018-11-16
Category : Computers
ISBN : 9781522537915

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Big Data Processing With Hadoop by Revathi, T.,Muneeswaran, K.,Blessa Binolin Pepsi, M. Pdf

Due to the increasing availability of affordable internet services, the number of users, and the need for a wider range of multimedia-based applications, internet usage is on the rise. With so many users and such a large amount of data, the requirements of analyzing large data sets leads to the need for further advancements to information processing. Big Data Processing With Hadoop is an essential reference source that discusses possible solutions for millions of users working with a variety of data applications, who expect fast turnaround responses, but encounter issues with processing data at the rate it comes in. Featuring research on topics such as market basket analytics, scheduler load simulator, and writing YARN applications, this book is ideally designed for IoT professionals, students, and engineers seeking coverage on many of the real-world challenges regarding big data.