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Author: Prem Jain
Publisher: IBM Redbooks
ISBN: 0738451045
Category : Computers
Languages : en
Pages : 56
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Book Description
This IBM® RedpaperTM provides a reference architecture, based on Apache Hadoop, to help businesses gain control over their data, meet tight service level agreements (SLAs) around their data applications, and turn data-driven insight into effective action. Big Data Networked Storage Solution for Hadoop delivers the capabilities for ingesting, storing, and managing large data sets with high reliability. IBM InfoSphere® Big InsightsTM provides an innovative analytics platform that processes and analyzes all types of data to turn large complex data into insight. IBM InfoSphere BigInsights brings the power of Hadoop to the enterprise. With built-in analytics, extensive integration capabilities, and the reliability, security and support that you require, IBM can help put your big data to work for you. This IBM Redpaper publication provides basic guidelines and best practices for how to size and configure Big Data Networked Storage Solution for Hadoop.
Author: Prem Jain
Publisher: IBM Redbooks
ISBN: 0738451045
Category : Computers
Languages : en
Pages : 56
Get Book Here
Book Description
This IBM® RedpaperTM provides a reference architecture, based on Apache Hadoop, to help businesses gain control over their data, meet tight service level agreements (SLAs) around their data applications, and turn data-driven insight into effective action. Big Data Networked Storage Solution for Hadoop delivers the capabilities for ingesting, storing, and managing large data sets with high reliability. IBM InfoSphere® Big InsightsTM provides an innovative analytics platform that processes and analyzes all types of data to turn large complex data into insight. IBM InfoSphere BigInsights brings the power of Hadoop to the enterprise. With built-in analytics, extensive integration capabilities, and the reliability, security and support that you require, IBM can help put your big data to work for you. This IBM Redpaper publication provides basic guidelines and best practices for how to size and configure Big Data Networked Storage Solution for Hadoop.
Author: Prem Jain
Publisher:
ISBN:
Category : Apache Hadoop
Languages : en
Pages :
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Book Description
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Author: Shoban Babu Sriramoju
Publisher: Horizon Books ( A Division of Ignited Minds Edutech P Ltd)
ISBN: 9386369575
Category :
Languages : en
Pages : 197
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Book Description
Big data is certainly one of the biggest buzz phrases in IT today. Combined with virtualization and cloud computing, big data is a technological capability that will force data centers to significantly transform and evolve within the next five years. Similar to virtualization, big data infrastructure is unique and can create an architectural upheaval in the way systems, storage, and software infrastructure are connected and managed. Unlike previous business analytics solutions, the real-time capability of new big data solutions can provide mission critical business intelligence that can change the shape and speed of enterprise decision making forever. Hence, the way in which IT infrastructure is connected and distributed warrants a fresh and critical analysis.
Author: Piyush Saxena
Publisher: GRIN Verlag
ISBN: 3656721610
Category : Computers
Languages : en
Pages : 110
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Book Description
Master's Thesis from the year 2014 in the subject Computer Science - Applied, grade: 82.00, , course: M.Tech CS&E, language: English, abstract: Hadoop and Map reduce today are facing huge amounts of data and are moving towards ubiquitous for big data storage and processing. This has made it an essential feature to evaluate and characterize the Hadoop file system and its deployment through extensive benchmarking. We have other benchmarking tools widely available with us today that are capable of analyzing the performance of the Hadoop system but they are made to either run in a single node system or are created for assessing the storage device that is attached and its basic characteristics as top speed and other hardware related details or manufacturer’s details. For this, the tool used is HiBench that is an essential part of Hadoop and is comprehensive benchmark suit that consist of a complete deposit of Hadoop applications having micro bench marks & real time applications for the purpose of benchmarking the performance of Hadoop on the available type of storage device (i.e. HDD and SSD) and machine configuration. This is helpful to optimize the performance and improve the support towards the limitations of Hadoop system. In this research work we will analyze and characterize the performance of external sorting algorithm in Hadoop (MapReduce) with SSD and HDD that are connected with various Interconnect technologies like 10GigE, IPoIB and RDBAIB. In addition, we will also demonstrate that the traditional servers and old Cloud systems can be upgraded by software and hardware up gradations to perform at par with the modern technologies to handle these loads, without spending ruthlessly on up gradations or complete changes in the system with the use of Modern storage devices and interconnect networking systems. This in turn reduces the power consumption drastically and allows smoother running of large scale servers with low latency and high throughput allowing use of the utmost power of the processors for the big data flowing in the network.
Author: Bill Havanki
Publisher: "O'Reilly Media, Inc."
ISBN: 1491959584
Category : Computers
Languages : en
Pages : 320
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Book Description
Until recently, Hadoop deployments existed on hardware owned and run by organizations. Now, of course, you can acquire the computing resources and network connectivity to run Hadoop clusters in the cloud. But there’s a lot more to deploying Hadoop to the public cloud than simply renting machines. This hands-on guide shows developers and systems administrators familiar with Hadoop how to install, use, and manage cloud-born clusters efficiently. You’ll learn how to architect clusters that work with cloud-provider features—not just to avoid pitfalls, but also to take full advantage of these services. You’ll also compare the Amazon, Google, and Microsoft clouds, and learn how to set up clusters in each of them. Learn how Hadoop clusters run in the cloud, the problems they can help you solve, and their potential drawbacks Examine the common concepts of cloud providers, including compute capabilities, networking and security, and storage Build a functional Hadoop cluster on cloud infrastructure, and learn what the major providers require Explore use cases for high availability, relational data with Hive, and complex analytics with Spark Get patterns and practices for running cloud clusters, from designing for price and security to dealing with maintenance
Author: Syed Thouheed Ahmed
Publisher: MileStone Research Publications
ISBN: 9354738281
Category : Computers
Languages : en
Pages : 101
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Book Description
Big data analytics and cloud computing is the fastest growing technologies in current era. This text book serves as a purpose in providing an understanding of big data principles and framework at the beginner?s level. The text book covers various essential concepts of big-data analytics and processing tools such as HADOOP and YARN. The Textbook covers an analogical understanding on bridging cloud computing with big-data technologies with essential cloud infrastructure protocol and ecosystem concepts. PART I: Hadoop Distributed File System Basics, Running Example Programs and Benchmarks, Hadoop MapReduce Framework Essential Hadoop Tools, Hadoop YARN Applications, Managing Hadoop with Apache Ambari, Basic Hadoop Administration Procedures PART II: Introduction to Cloud Computing: Origins and Influences, Basic Concepts and Terminology, Goals and Benefits, Risks and Challenges. Fundamental Concepts and Models: Roles and Boundaries, Cloud Characteristics, Cloud Delivery Models, Cloud Deployment Models. Cloud Computing Technologies:Broadband networks and internet architecture, data center technology, virtualization technology, web technology, multi-tenant technology, service Technology Cloud Infrastructure Mechanisms:Logical Network Perimeter, Virtual Server, Cloud Storage Device, Cloud Usage Monitor, Resource Replication, Ready-made environment
Author: James O'Reilly
Publisher: Morgan Kaufmann
ISBN: 0128038659
Category : Computers
Languages : en
Pages : 282
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Book Description
Network Storage: Tools and Technologies for Storing Your Company's Data explains the changes occurring in storage, what they mean, and how to negotiate the minefields of conflicting technologies that litter the storage arena, all in an effort to help IT managers create a solid foundation for coming decades. The book begins with an overview of the current state of storage and its evolution from the network perspective, looking closely at the different protocols and connection schemes and how they differentiate in use case and operational behavior. The book explores the software changes that are motivating this evolution, ranging from data management, to in-stream processing and storage in virtual systems, and changes in the decades-old OS stack. It explores Software-Defined Storage as a way to construct storage networks, the impact of Big Data, high-performance computing, and the cloud on storage networking. As networks and data integrity are intertwined, the book looks at how data is split up and moved to the various appliances holding that dataset and its impact. Because data security is often neglected, users will find a comprehensive discussion on security issues that offers remedies that can be applied. The book concludes with a look at technologies on the horizon that will impact storage and its networks, such as NVDIMMs, The Hybrid Memory Cube, VSANs, and NAND Killers. - Puts all the new developments in storage networking in a clear perspective for near-term and long-term planning - Offers a complete overview of storage networking, serving as a go-to resource for creating a coherent implementation plan - Provides the details needed to understand the area, and clears a path through the confusion and hype that surrounds such a radical revolution of the industry
Author: Mark Grover
Publisher: "O'Reilly Media, Inc."
ISBN: 1491900075
Category : Computers
Languages : en
Pages : 399
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Book Description
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
Author: Min Chen
Publisher: Springer
ISBN: 331906245X
Category : Computers
Languages : en
Pages : 100
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Book Description
This Springer Brief provides a comprehensive overview of the background and recent developments of big data. The value chain of big data is divided into four phases: data generation, data acquisition, data storage and data analysis. For each phase, the book introduces the general background, discusses technical challenges and reviews the latest advances. Technologies under discussion include cloud computing, Internet of Things, data centers, Hadoop and more. The authors also explore several representative applications of big data such as enterprise management, online social networks, healthcare and medical applications, collective intelligence and smart grids. This book concludes with a thoughtful discussion of possible research directions and development trends in the field. Big Data: Related Technologies, Challenges and Future Prospects is a concise yet thorough examination of this exciting area. It is designed for researchers and professionals interested in big data or related research. Advanced-level students in computer science and electrical engineering will also find this book useful.
