High Performance Persistent Storage System For Bigdata Analysis
DOWNLOAD eBooks
Download High Performance Persistent Storage System For Bigdata Analysis PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get High Performance Persistent Storage System For Bigdata Analysis book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
High Performance Persistent Storage System For Bigdata Analysis
DOWNLOAD eBooks
Author : Piyush Saxena
language : en
Publisher: GRIN Verlag
Release Date : 2014-08-19
High Performance Persistent Storage System For Bigdata Analysis written by Piyush Saxena and has been published by GRIN Verlag this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-08-19 with Computers categories.
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.
High Performance Big Data Analytics
DOWNLOAD eBooks
Author : Pethuru Raj
language : en
Publisher: Springer
Release Date : 2015-10-16
High Performance Big Data Analytics written by Pethuru Raj and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-10-16 with Computers categories.
This book presents a detailed review of high-performance computing infrastructures for next-generation big data and fast data analytics. Features: includes case studies and learning activities throughout the book and self-study exercises in every chapter; presents detailed case studies on social media analytics for intelligent businesses and on big data analytics (BDA) in the healthcare sector; describes the network infrastructure requirements for effective transfer of big data, and the storage infrastructure requirements of applications which generate big data; examines real-time analytics solutions; introduces in-database processing and in-memory analytics techniques for data mining; discusses the use of mainframes for handling real-time big data and the latest types of data management systems for BDA; provides information on the use of cluster, grid and cloud computing systems for BDA; reviews the peer-to-peer techniques and tools and the common information visualization techniques, used in BDA.
Block Trace Analysis And Storage System Optimization
DOWNLOAD eBooks
Author : Jun Xu
language : en
Publisher: Apress
Release Date : 2018-11-16
Block Trace Analysis And Storage System Optimization written by Jun Xu and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-16 with Computers categories.
Understand the fundamental factors of data storage system performance and master an essential analytical skill using block trace via applications such as MATLAB and Python tools. You will increase your productivity and learn the best techniques for doing specific tasks (such as analyzing the IO pattern in a quantitative way, identifying the storage system bottleneck, and designing the cache policy). In the new era of IoT, big data, and cloud systems, better performance and higher density of storage systems has become crucial. To increase data storage density, new techniques have evolved and hybrid and parallel access techniques—together with specially designed IO scheduling and data migration algorithms—are being deployed to develop high-performance data storage solutions. Among the various storage system performance analysis techniques, IO event trace analysis (block-level trace analysis particularly) is one of the most common approaches for system optimization and design. However, the task of completing a systematic survey is challenging and very few works on this topic exist. Block Trace Analysis and Storage System Optimization brings together theoretical analysis (such as IO qualitative properties and quantitative metrics) and practical tools (such as trace parsing, analysis, and results reporting perspectives). The book provides content on block-level trace analysis techniques, and includes case studies to illustrate how these techniques and tools can be applied in real applications (such as SSHD, RAID, Hadoop, and Ceph systems). What You’ll Learn Understand the fundamental factors of data storage system performance Master an essential analytical skill using block trace via various applications Distinguish how the IO pattern differs in the block level from the file level Know how the sequential HDFS request becomes “fragmented” in final storage devices Perform trace analysis tasks with a tool based on the MATLAB and Python platforms Who This Book Is For IT professionals interested in storage system performance optimization: network administrators, data storage managers, data storage engineers, storage network engineers, systems engineers
Storage Systems
DOWNLOAD eBooks
Author : Alexander Thomasian
language : en
Publisher: Academic Press
Release Date : 2021-10-13
Storage Systems written by Alexander Thomasian and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-13 with Science categories.
Storage Systems: Organization, Performance, Coding, Reliability and Their Data Processing was motivated by the 1988 Redundant Array of Inexpensive/Independent Disks proposal to replace large form factor mainframe disks with an array of commodity disks. Disk loads are balanced by striping data into strips—with one strip per disk— and storage reliability is enhanced via replication or erasure coding, which at best dedicates k strips per stripe to tolerate k disk failures. Flash memories have resulted in a paradigm shift with Solid State Drives (SSDs) replacing Hard Disk Drives (HDDs) for high performance applications. RAID and Flash have resulted in the emergence of new storage companies, namely EMC, NetApp, SanDisk, and Purestorage, and a multibillion-dollar storage market. Key new conferences and publications are reviewed in this book.The goal of the book is to expose students, researchers, and IT professionals to the more important developments in storage systems, while covering the evolution of storage technologies, traditional and novel databases, and novel sources of data. We describe several prototypes: FAWN at CMU, RAMCloud at Stanford, and Lightstore at MIT; Oracle's Exadata, AWS' Aurora, Alibaba's PolarDB, Fungible Data Center; and author's paper designs for cloud storage, namely heterogeneous disk arrays and hierarchical RAID. Surveys storage technologies and lists sources of data: measurements, text, audio, images, and video Familiarizes with paradigms to improve performance: caching, prefetching, log-structured file systems, and merge-trees (LSMs) Describes RAID organizations and analyzes their performance and reliability Conserves storage via data compression, deduplication, compaction, and secures data via encryption Specifies implications of storage technologies on performance and power consumption Exemplifies database parallelism for big data, analytics, deep learning via multicore CPUs, GPUs, FPGAs, and ASICs, e.g., Google's Tensor Processing Units
Big Data Platforms And Applications
DOWNLOAD eBooks
Author : Florin Pop
language : en
Publisher: Springer Nature
Release Date : 2021-09-28
Big Data Platforms And Applications written by Florin Pop and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-28 with Computers categories.
This book provides a review of advanced topics relating to the theory, research, analysis and implementation in the context of big data platforms and their applications, with a focus on methods, techniques, and performance evaluation. The explosive growth in the volume, speed, and variety of data being produced every day requires a continuous increase in the processing speeds of servers and of entire network infrastructures, as well as new resource management models. This poses significant challenges (and provides striking development opportunities) for data intensive and high-performance computing, i.e., how to efficiently turn extremely large datasets into valuable information and meaningful knowledge. The task of context data management is further complicated by the variety of sources such data derives from, resulting in different data formats, with varying storage, transformation, delivery, and archiving requirements. At the same time rapid responses are needed for real-time applications. With the emergence of cloud infrastructures, achieving highly scalable data management in such contexts is a critical problem, as the overall application performance is highly dependent on the properties of the data management service.
High Performance Big Data Computing
DOWNLOAD eBooks
Author : Dhabaleswar K. Panda
language : en
Publisher: MIT Press
Release Date : 2022-08-02
High Performance Big Data Computing written by Dhabaleswar K. Panda and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-02 with Computers categories.
An in-depth overview of an emerging field that brings together high-performance computing, big data processing, and deep lLearning. Over the last decade, the exponential explosion of data known as big data has changed the way we understand and harness the power of data. The emerging field of high-performance big data computing, which brings together high-performance computing (HPC), big data processing, and deep learning, aims to meet the challenges posed by large-scale data processing. This book offers an in-depth overview of high-performance big data computing and the associated technical issues, approaches, and solutions. The book covers basic concepts and necessary background knowledge, including data processing frameworks, storage systems, and hardware capabilities; offers a detailed discussion of technical issues in accelerating big data computing in terms of computation, communication, memory and storage, codesign, workload characterization and benchmarking, and system deployment and management; and surveys benchmarks and workloads for evaluating big data middleware systems. It presents a detailed discussion of big data computing systems and applications with high-performance networking, computing, and storage technologies, including state-of-the-art designs for data processing and storage systems. Finally, the book considers some advanced research topics in high-performance big data computing, including designing high-performance deep learning over big data (DLoBD) stacks and HPC cloud technologies.
Big Data Benchmarks Performance Optimization And Emerging Hardware
DOWNLOAD eBooks
Author : Jianfeng Zhan
language : en
Publisher: Springer
Release Date : 2014-11-10
Big Data Benchmarks Performance Optimization And Emerging Hardware written by Jianfeng Zhan and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-10 with Computers categories.
This book constitutes the thoroughly revised selected papers of the 4th and 5th workshops on Big Data Benchmarks, Performance Optimization, and Emerging Hardware, BPOE 4 and BPOE 5, held respectively in Salt Lake City, in March 2014, and in Hangzhou, in September 2014. The 16 papers presented were carefully reviewed and selected from 30 submissions. Both workshops focus on architecture and system support for big data systems, such as benchmarking; workload characterization; performance optimization and evaluation; emerging hardware.
Driving Scientific And Engineering Discoveries Through The Convergence Of Hpc Big Data And Ai
DOWNLOAD eBooks
Author : Jeffrey Nichols
language : en
Publisher: Springer Nature
Release Date : 2020-12-22
Driving Scientific And Engineering Discoveries Through The Convergence Of Hpc Big Data And Ai written by Jeffrey Nichols and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-22 with Computers categories.
This book constitutes the revised selected papers of the 17th Smoky Mountains Computational Sciences and Engineering Conference, SMC 2020, held in Oak Ridge, TN, USA*, in August 2020. The 36 full papers and 1 short paper presented were carefully reviewed and selected from a total of 94 submissions. The papers are organized in topical sections of computational applications: converged HPC and artificial intelligence; system software: data infrastructure and life cycle; experimental/observational applications: use cases that drive requirements for AI and HPC convergence; deploying computation: on the road to a converged ecosystem; scientific data challenges. *The conference was held virtually due to the COVID-19 pandemic.
Supercomputing Frontiers
DOWNLOAD eBooks
Author : Rio Yokota
language : en
Publisher: Springer
Release Date : 2018-03-20
Supercomputing Frontiers written by Rio Yokota and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-20 with Computers categories.
It constitutes the refereed proceedings of the 4th Asian Supercomputing Conference, SCFA 2018, held in Singapore in March 2018. Supercomputing Frontiers will be rebranded as Supercomputing Frontiers Asia (SCFA), which serves as the technical programme for SCA18. The technical programme for SCA18 consists of four tracks: Application, Algorithms & Libraries Programming System Software Architecture, Network/Communications & Management Data, Storage & Visualisation The 20 papers presented in this volume were carefully reviewed nd selected from 60 submissions.
High Performance Big Data Analytics
DOWNLOAD eBooks
Author : Pethuru Raj
language : en
Publisher:
Release Date : 2015
High Performance Big Data Analytics written by Pethuru Raj and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with categories.
This important and timely text/reference presents a detailed review of high-performance computing infrastructures for next-generation big data and fast data analytics. Comprehensively covering a diverse range of computer systems and proven techniques for high-performance big-data analytics, the book also presents case studies, practical guidelines, and best practices for enabling decision-making toward implementing the appropriate computer systems and approaches. Topics and features: Includes case studies and learning activities throughout the book, and self-study exercises at the end of every chapter Presents detailed case studies on social media analytics for intelligent businesses, and on big data analytics in the healthcare sector Describes the network infrastructure requirements for effective transfer of big data, and the storage infrastructure requirements of applications which generate big data Examines real-time analytics solutions, such as machine data analytics and operational analytics Introduces in-database processing and in-memory analytics techniques for data mining Discusses the use of mainframes for handling real-time big data, and the latest types of data management systems for big and fast data analytics Provides information on the use of cluster, grid and cloud computing systems for big data analytics and data-intensive processing Reviews the peer-to-peer techniques and tools, and the common information visualization techniques, used in big data analytics Software engineers, cloud professionals and big data scientists will find this book to be an informative and inspiring read, highlighting the indispensable role data analytics will play in shaping a smart future.