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Due to the growth of Internet-driven applications, issues such as storage capacity and access speed have become critical in the design of today's computer systems Book fills the need for a readily-accessible single reference source on the subject of high-performance, large scale storage and delivery systems Contains the latest information and future directions of disk arrays and parallel I/O A Wiley-IEEE Press Publication
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
High Performance MySQL is the definitive guide to building fast, reliable systems with MySQL. Written by noted experts with years of real-world experience building very large systems, this book covers every aspect of MySQL performance in detail, and focuses on robustness, security, and data integrity. High Performance MySQL teaches you advanced techniques in depth so you can bring out MySQL's full power. Learn how to design schemas, indexes, queries and advanced MySQL features for maximum performance, and get detailed guidance for tuning your MySQL server, operating system, and hardware to their fullest potential. You'll also learn practical, safe, high-performance ways to scale your applications with replication, load balancing, high availability, and failover. This second edition is completely revised and greatly expanded, with deeper coverage in all areas. Major additions include: Emphasis throughout on both performance and reliability Thorough coverage of storage engines, including in-depth tuning and optimizations for the InnoDB storage engine Effects of new features in MySQL 5.0 and 5.1, including stored procedures, partitioned databases, triggers, and views A detailed discussion on how to build very large, highly scalable systems with MySQL New options for backups and replication Optimization of advanced querying features, such as full-text searches Four new appendices The book also includes chapters on benchmarking, profiling, backups, security, and tools and techniques to help you measure, monitor, and manage your MySQL installations.
The book Operating System by Rohit Khurana is an insightful work that elaborates on fundamentals as well as advanced topics of the discipline. It offers an in-depth coverage of concepts, design and functions of an operating system irrespective of the hardware used. With illustrations and examples the aim is to make the subject crystal clear and the book extremely student-friendly. The book caters to undergraduate students of most Indian universities, who would find subject matter highly informative and enriching. Tailored as a guide for self-paced learning, it equips budding system programmers with the right knowledge and expertise. The book has been revised to keep pace with the latest technology and constantly revising syllabuses. Thus, this edition has become more comprehensive with the inclusion of several new topics. In addition, certain sections of the book have been thoroughly revised. Key Features • Case studies of Unix, Linux and Windows to put theory concepts into practice • A crisp summary for recapitulation with each chapter • A glossary of technical terms • Insightful questions and model test papers to prepare for the examinations New in this Edition • More types of operating system, like PC and mobile; Methods used for communication in client-server systems. • New topics like: Thread library; Thread scheduling; Principles of concurrency, Precedence graph, Concurrency conditions and Sleeping barber problem; Structure of page tables, Demand segmentation and Cache memory organization; STREAMS; Disk attachment, Stable and tertiary storage, Record blocking and File sharing; Goals and principles of protection, Access control matrix, Revocation of access rights, Cryptography, Trusted systems, and Firewalls.
Features vendor-neutral coverage applicable to any storage network Includes a special case-study section citing real-world applications and examples The first vendor-neutral volume to cover storage network performance tuning and optimization Exacting performance monitoring and analysis maximizes the efficiency and cost-effectiveness of existing storage networks Meets the needs of network administrators, storage engineers, and IT professionals faced with shrinking budgets and growing data storage demands
Winner of the Shingo Publication Award Accelerate your organization to win in the marketplace. How can we apply technology to drive business value? For years, we've been told that the performance of software delivery teams doesn't matter―that it can't provide a competitive advantage to our companies. Through four years of groundbreaking research to include data collected from the State of DevOps reports conducted with Puppet, Dr. Nicole Forsgren, Jez Humble, and Gene Kim set out to find a way to measure software delivery performance―and what drives it―using rigorous statistical methods. This book presents both the findings and the science behind that research, making the information accessible for readers to apply in their own organizations. Readers will discover how to measure the performance of their teams, and what capabilities they should invest in to drive higher performance. This book is ideal for management at every level.
This book comprehensively introduces data deduplication technologies for storage systems. It first presents the overview of data deduplication including its theoretical basis, basic workflow, application scenarios and its key technologies, and then the book focuses on each key technology of the deduplication to provide an insight into the evolution of the technology over the years including chunking algorithms, indexing schemes, fragmentation reduced schemes, rewriting algorithm and security solution. In particular, the state-of-the-art solutions and the newly proposed solutions are both elaborated. At the end of the book, the author discusses the fundamental trade-offs in each of deduplication design choices and propose an open-source deduplication prototype. The book with its fundamental theories and complete survey can guide the beginners, students and practitioners working on data deduplication in storage system. It also provides a compact reference in the perspective of key data deduplication technologies for those researchers in developing high performance storage solutions.
This IBM® Redpaper Redbookspublication provides an overview of the IBM Elastic Storage® Server (IBM ESS) and IBM Elastic Storage System (also IBM ESS). These scalable, high-performance data and file management solution, are built on IBM Spectrum® Scale technology. Providing reliability, performance, and scalability, IBM ESS can be implemented for a range of diverse requirements. The latest IBM ESS 3500 is the most innovative system that provides investment protection to expand or build a new Global Data Platform and use current storage. The system allows enhanced, non-disruptive upgrades to grow from flash to hybrid or from hard disk drives (HDDs) to hybrid. IBM ESS can scale up or out with two different storage mediums in the environment, and it is ready for technologies like 200 Gb Ethernet or InfiniBand NDR-200 connectivity. This publication helps you to understand the solution and its architecture. It describes ordering the best solution for your environment, planning the installation and integration of the solution into your environment, and correctly maintaining your solution. The solution is created from the following combination of physical and logical components: Hardware Operating system Storage Network Applications Knowledge of the IBM Elastic Storage Server and IBM Elastic Storage System components is key for planning an environment. This paper is targeted toward technical professionals (consultants, technical support staff, IT Architects, and IT specialists) who are responsible for delivering cost-effective cloud services and big data solutions. The content of this paper can help you to uncover insights among client's data so that you can take appropriate actions to optimize business results, product development, and scientific discoveries.
Your Python code may run correctly, but you need it to run faster. Updated for Python 3, this expanded edition shows you how to locate performance bottlenecks and significantly speed up your code in high-data-volume programs. By exploring the fundamental theory behind design choices, High Performance Python helps you gain a deeper understanding of Python’s implementation. How do you take advantage of multicore architectures or clusters? Or build a system that scales up and down without losing reliability? Experienced Python programmers will learn concrete solutions to many issues, along with war stories from companies that use high-performance Python for social media analytics, productionized machine learning, and more. Get a better grasp of NumPy, Cython, and profilers Learn how Python abstracts the underlying computer architecture Use profiling to find bottlenecks in CPU time and memory usage Write efficient programs by choosing appropriate data structures Speed up matrix and vector computations Use tools to compile Python down to machine code Manage multiple I/O and computational operations concurrently Convert multiprocessing code to run on local or remote clusters Deploy code faster using tools like Docker
As computation continues to move into the cloud, the computing platform of interest no longer resembles a pizza box or a refrigerator, but a warehouse full of computers. These new large datacenters are quite different from traditional hosting facilities of earlier times and cannot be viewed simply as a collection of co-located servers. Large portions of the hardware and software resources in these facilities must work in concert to efficiently deliver good levels of Internet service performance, something that can only be achieved by a holistic approach to their design and deployment. In other words, we must treat the datacenter itself as one massive warehouse-scale computer (WSC). We describe the architecture of WSCs, the main factors influencing their design, operation, and cost structure, and the characteristics of their software base. We hope it will be useful to architects and programmers of today’s WSCs, as well as those of future many-core platforms which may one day implement the equivalent of today’s WSCs on a single board. Notes for the Second Edition After nearly four years of substantial academic and industrial developments in warehouse-scale computing, we are delighted to present our first major update to this lecture. The increased popularity of public clouds has made WSC software techniques relevant to a larger pool of programmers since our first edition. Therefore, we expanded Chapter 2 to reflect our better understanding of WSC software systems and the toolbox of software techniques for WSC programming. In Chapter 3, we added to our coverage of the evolving landscape of wimpy vs. brawny server trade-offs, and we now present an overview of WSC interconnects and storage systems that was promised but lacking in the original edition. Thanks largely to the help of our new co-author, Google Distinguished Engineer Jimmy Clidaras, the material on facility mechanical and power distribution design has been updated and greatly extended (see Chapters 4 and 5). Chapters 6 and 7 have also been revamped significantly. We hope this revised edition continues to meet the needs of educators and professionals in this area.