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Data Structures for Data-Intensive Applications by Manos Athanassoulis,Stratos Idreos,Dennis Shasha Pdf
Data structures are the means by which software programs store and retrieve data. This monograph focuses on key-value data structures, which are widely used for data-intensive applications thanks to the versatility of the key-value data model. Key-value data structures constitute the core of any data-driven system. They provide the means to store, search, and modify data residing at various levels of the storage and memory hierarchy. Designing efficient data structures for given workloads has long been a focus of research and practice in both academia and industry. Data Structures for Data-Intensive Applications explains the space of data structure design choices, how to select the appropriate data structure depending on the goals and workload of an application at hand, and how the ever-evolving hardware and data properties require innovations in data structure design. The overarching goal is to help the reader both select the best existing data structures and design and build new ones.
Designing Data-Intensive Applications by Martin Kleppmann Pdf
Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords? In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications. Peer under the hood of the systems you already use, and learn how to use and operate them more effectively Make informed decisions by identifying the strengths and weaknesses of different tools Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity Understand the distributed systems research upon which modern databases are built Peek behind the scenes of major online services, and learn from their architectures
Data Structures for Data-Intensive Applications by Manos Athanassoulis,Stratos Idreos,Dennis Shasha Pdf
Outlines the underlying design dimensions of data structures and how they can be combined to support workloads. The systematization of the design space and the accompanying guidelines enables readers to select a fitting data structure or to invent a new data structure for a given workload.
Foundations of Data Intensive Applications by Supun Kamburugamuve,Saliya Ekanayake Pdf
PEEK “UNDER THE HOOD” OF BIG DATA ANALYTICS The world of big data analytics grows ever more complex. And while many people can work superficially with specific frameworks, far fewer understand the fundamental principles of large-scale, distributed data processing systems and how they operate. In Foundations of Data Intensive Applications: Large Scale Data Analytics under the Hood, renowned big-data experts and computer scientists Drs. Supun Kamburugamuve and Saliya Ekanayake deliver a practical guide to applying the principles of big data to software development for optimal performance. The authors discuss foundational components of large-scale data systems and walk readers through the major software design decisions that define performance, application type, and usability. You???ll learn how to recognize problems in your applications resulting in performance and distributed operation issues, diagnose them, and effectively eliminate them by relying on the bedrock big data principles explained within. Moving beyond individual frameworks and APIs for data processing, this book unlocks the theoretical ideas that operate under the hood of every big data processing system. Ideal for data scientists, data architects, dev-ops engineers, and developers, Foundations of Data Intensive Applications: Large Scale Data Analytics under the Hood shows readers how to: Identify the foundations of large-scale, distributed data processing systems Make major software design decisions that optimize performance Diagnose performance problems and distributed operation issues Understand state-of-the-art research in big data Explain and use the major big data frameworks and understand what underpins them Use big data analytics in the real world to solve practical problems
Handbook of Data Structures and Applications by Dinesh P. Mehta,Sartaj Sahni Pdf
The Handbook of Data Structures and Applications was first published over a decade ago. This second edition aims to update the first by focusing on areas of research in data structures that have seen significant progress. While the discipline of data structures has not matured as rapidly as other areas of computer science, the book aims to update those areas that have seen advances. Retaining the seven-part structure of the first edition, the handbook begins with a review of introductory material, followed by a discussion of well-known classes of data structures, Priority Queues, Dictionary Structures, and Multidimensional structures. The editors next analyze miscellaneous data structures, which are well-known structures that elude easy classification. The book then addresses mechanisms and tools that were developed to facilitate the use of data structures in real programs. It concludes with an examination of the applications of data structures. Four new chapters have been added on Bloom Filters, Binary Decision Diagrams, Data Structures for Cheminformatics, and Data Structures for Big Data Stores, and updates have been made to other chapters that appeared in the first edition. The Handbook is invaluable for suggesting new ideas for research in data structures, and for revealing application contexts in which they can be deployed. Practitioners devising algorithms will gain insight into organizing data, allowing them to solve algorithmic problems more efficiently.
Designing Data-Intensive Applications by Martin Kleppmann Pdf
Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords? In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications. Peer under the hood of the systems you already use, and learn how to use and operate them more effectively Make informed decisions by identifying the strengths and weaknesses of different tools Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity Understand the distributed systems research upon which modern databases are built Peek behind the scenes of major online services, and learn from their architectures
DATA STRUCTURES IN C++ by N. S. KUTTI,P. Y. PADHYE Pdf
This compact and comprehensive book provides an introduction to data structures from an object-oriented perspective using the powerful language C++ as the programming vehicle. It is designed as an ideal text for the students before they start designing algorithms in C++. The book begins with an overview of C++, then it goes on to analyze the basic concepts of data structures, and finally focusses the reader's attention on abstract data structures. In so doing, the text uses simple examples to explain the meaning of each data type. Throughout, an attempt has been made to enable students to progress gradually from simple object-oriented abstract data structures to more advanced data structures. A large number of worked examples and the end-of-chapter exercises help the students reinforce the knowledge gained.Intended as a one-semester course for undergraduate students in computer science and for those who offer this course in engineering and management, the book should also prove highly useful to those IT professionals who have a keen interest in the subject.
Cloud Computing for Data-Intensive Applications by Xiaolin Li,Judy Qiu Pdf
This book presents a range of cloud computing platforms for data-intensive scientific applications. It covers systems that deliver infrastructure as a service, including: HPC as a service; virtual networks as a service; scalable and reliable storage; algorithms that manage vast cloud resources and applications runtime; and programming models that enable pragmatic programming and implementation toolkits for eScience applications. Many scientific applications in clouds are also introduced, such as bioinformatics, biology, weather forecasting and social networks. Most chapters include case studies. Cloud Computing for Data-Intensive Applications targets advanced-level students and researchers studying computer science and electrical engineering. Professionals working in cloud computing, networks, databases and more will also find this book useful as a reference.
Handbook of Data Intensive Computing by Borko Furht,Armando Escalante Pdf
Data Intensive Computing refers to capturing, managing, analyzing, and understanding data at volumes and rates that push the frontiers of current technologies. The challenge of data intensive computing is to provide the hardware architectures and related software systems and techniques which are capable of transforming ultra-large data into valuable knowledge. Handbook of Data Intensive Computing is written by leading international experts in the field. Experts from academia, research laboratories and private industry address both theory and application. Data intensive computing demands a fundamentally different set of principles than mainstream computing. Data-intensive applications typically are well suited for large-scale parallelism over the data and also require an extremely high degree of fault-tolerance, reliability, and availability. Real-world examples are provided throughout the book. Handbook of Data Intensive Computing is designed as a reference for practitioners and researchers, including programmers, computer and system infrastructure designers, and developers. This book can also be beneficial for business managers, entrepreneurs, and investors.
Algorithms and Data Structures for Massive Datasets by Dzejla Medjedovic,Emin Tahirovic Pdf
Massive modern datasets make traditional data structures and algorithms grind to a halt. This fun and practical guide introduces cutting-edge techniques that can reliably handle even the largest distributed datasets. In Algorithms and Data Structures for Massive Datasets you will learn: Probabilistic sketching data structures for practical problems Choosing the right database engine for your application Evaluating and designing efficient on-disk data structures and algorithms Understanding the algorithmic trade-offs involved in massive-scale systems Deriving basic statistics from streaming data Correctly sampling streaming data Computing percentiles with limited space resources Algorithms and Data Structures for Massive Datasets reveals a toolbox of new methods that are perfect for handling modern big data applications. You’ll explore the novel data structures and algorithms that underpin Google, Facebook, and other enterprise applications that work with truly massive amounts of data. These effective techniques can be applied to any discipline, from finance to text analysis. Graphics, illustrations, and hands-on industry examples make complex ideas practical to implement in your projects—and there’s no mathematical proofs to puzzle over. Work through this one-of-a-kind guide, and you’ll find the sweet spot of saving space without sacrificing your data’s accuracy. About the technology Standard algorithms and data structures may become slow—or fail altogether—when applied to large distributed datasets. Choosing algorithms designed for big data saves time, increases accuracy, and reduces processing cost. This unique book distills cutting-edge research papers into practical techniques for sketching, streaming, and organizing massive datasets on-disk and in the cloud. About the book Algorithms and Data Structures for Massive Datasets introduces processing and analytics techniques for large distributed data. Packed with industry stories and entertaining illustrations, this friendly guide makes even complex concepts easy to understand. You’ll explore real-world examples as you learn to map powerful algorithms like Bloom filters, Count-min sketch, HyperLogLog, and LSM-trees to your own use cases. What's inside Probabilistic sketching data structures Choosing the right database engine Designing efficient on-disk data structures and algorithms Algorithmic tradeoffs in massive-scale systems Computing percentiles with limited space resources About the reader Examples in Python, R, and pseudocode. About the author Dzejla Medjedovic earned her PhD in the Applied Algorithms Lab at Stony Brook University, New York. Emin Tahirovic earned his PhD in biostatistics from University of Pennsylvania. Illustrator Ines Dedovic earned her PhD at the Institute for Imaging and Computer Vision at RWTH Aachen University, Germany. Table of Contents 1 Introduction PART 1 HASH-BASED SKETCHES 2 Review of hash tables and modern hashing 3 Approximate membership: Bloom and quotient filters 4 Frequency estimation and count-min sketch 5 Cardinality estimation and HyperLogLog PART 2 REAL-TIME ANALYTICS 6 Streaming data: Bringing everything together 7 Sampling from data streams 8 Approximate quantiles on data streams PART 3 DATA STRUCTURES FOR DATABASES AND EXTERNAL MEMORY ALGORITHMS 9 Introducing the external memory model 10 Data structures for databases: B-trees, Bε-trees, and LSM-trees 11 External memory sorting
PHP 7 Data Structures and Algorithms by Mizanur Rahman Pdf
Increase your productivity by implementing data structures About This Book Gain a complete understanding of data structures using a simple approach Analyze algorithms and learn when you should apply each solution Explore the true potential of functional data structures Who This Book Is For This book is for those who want to learn data structures and algorithms with PHP for better control over application-solution, efficiency, and optimization. A basic understanding of PHP data types, control structures, and other basic features is required What You Will Learn Gain a better understanding of PHP arrays as a basic data structure and their hidden power Grasp how to analyze algorithms and the Big O Notation Implement linked lists, double linked lists, stack, queues, and priority queues using PHP Work with sorting, searching, and recursive algorithms Make use of greedy, dynamic, and pattern matching algorithms Implement tree, heaps, and graph algorithms Apply PHP functional data structures and built-in data structures and algorithms In Detail PHP has always been the the go-to language for web based application development, but there are materials and resources you can refer to to see how it works. Data structures and algorithms help you to code and execute them effectively, cutting down on processing time significantly. If you want to explore data structures and algorithms in a practical way with real-life projects, then this book is for you. The book begins by introducing you to data structures and algorithms and how to solve a problem from beginning to end using them. Once you are well aware of the basics, it covers the core aspects like arrays, listed lists, stacks and queues. It will take you through several methods of finding efficient algorithms and show you which ones you should implement in each scenario. In addition to this, you will explore the possibilities of functional data structures using PHP and go through advanced algorithms and graphs as well as dynamic programming. By the end, you will be confident enough to tackle both basic and advanced data structures, understand how they work, and know when to use them in your day-to-day work Style and approach An easy-to-follow guide full of examples of implementation of data structures and real world examples to solve the problems faced. Each topic is first explained in general terms and then implemented using step by step explanation so that developers can understand each part of the discussion without any problem.
Data Structures Demystified by Jim Keogh,Ken Davidson Pdf
Whether you are an entry-level or seasoned designer or programmer, learn all about data structures in this easy-to-understand, self-teaching guide that can be directly applied to any programming language. From memory and addresses to hashtables, authors Keogh and Davidson, provide clear explanations that demystify this “algebra of programming.”
Michael T. Goodrich,Roberto Tamassia,David M. Mount
Author : Michael T. Goodrich,Roberto Tamassia,David M. Mount Publisher : John Wiley & Sons Page : 739 pages File Size : 45,8 Mb Release : 2011-02-22 Category : Computers ISBN : 9780470383278
Data Structures and Algorithms in C++ by Michael T. Goodrich,Roberto Tamassia,David M. Mount Pdf
An updated, innovative approach to data structures and algorithms Written by an author team of experts in their fields, this authoritative guide demystifies even the most difficult mathematical concepts so that you can gain a clear understanding of data structures and algorithms in C++. The unparalleled author team incorporates the object-oriented design paradigm using C++ as the implementation language, while also providing intuition and analysis of fundamental algorithms. Offers a unique multimedia format for learning the fundamentals of data structures and algorithms Allows you to visualize key analytic concepts, learn about the most recent insights in the field, and do data structure design Provides clear approaches for developing programs Features a clear, easy-to-understand writing style that breaks down even the most difficult mathematical concepts Building on the success of the first edition, this new version offers you an innovative approach to fundamental data structures and algorithms.
