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Author: Jeffrey Scott Vitter Publisher: Now Publishers Inc ISBN: 1601981066 Category : Computers Languages : en Pages : 192
Book Description
Describes several useful paradigms for the design and implementation of efficient external memory (EM) algorithms and data structures. The problem domains considered include sorting, permuting, FFT, scientific computing, computational geometry, graphs, databases, geographic information systems, and text and string processing.
Author: Jeffrey Scott Vitter Publisher: Now Publishers Inc ISBN: 1601981066 Category : Computers Languages : en Pages : 192
Book Description
Describes several useful paradigms for the design and implementation of efficient external memory (EM) algorithms and data structures. The problem domains considered include sorting, permuting, FFT, scientific computing, computational geometry, graphs, databases, geographic information systems, and text and string processing.
Author: Dzejla Medjedovic Publisher: Simon and Schuster ISBN: 1638356564 Category : Computers Languages : en Pages : 302
Book Description
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
Author: Ulrich Meyer Publisher: Springer ISBN: 3540365745 Category : Computers Languages : en Pages : 429
Book Description
Algorithms that have to process large data sets have to take into account that the cost of memory access depends on where the data is stored. Traditional algorithm design is based on the von Neumann model where accesses to memory have uniform cost. Actual machines increasingly deviate from this model: while waiting for memory access, nowadays, microprocessors can in principle execute 1000 additions of registers; for hard disk access this factor can reach six orders of magnitude. The 16 coherent chapters in this monograph-like tutorial book introduce and survey algorithmic techniques used to achieve high performance on memory hierarchies; emphasis is placed on methods interesting from a theoretical as well as important from a practical point of view.
Author: Clifford A. Shaffer Publisher: ISBN: Category : Computers Languages : en Pages : 536
Book Description
This practical text contains fairly "traditional" coverage of data structures with a clear and complete use of algorithm analysis, and some emphasis on file processing techniques as relevant to modern programmers. It fully integrates OO programming with these topics, as part of the detailed presentation of OO programming itself.Chapter topics include lists, stacks, and queues; binary and general trees; graphs; file processing and external sorting; searching; indexing; and limits to computation.For programmers who need a good reference on data structures.
Author: Frank Dehne Publisher: Springer ISBN: 3540484477 Category : Computers Languages : en Pages : 381
Book Description
The papers in this volume were presented at the Sixth Workshop on Algorithms and Data Structures (WADS '99). The workshop took place August 11 - 14, 1999, in Vancouver, Canada. The workshop alternates with the Scandinavian Workshop on Algorithms Theory (SWAT), continuing the tradition of SWAT and WADS starting with SWAT'88 and WADS'89. In response to the program committee's call for papers, 71 papers were submitted. From these submissions, the program committee selected 32 papers for presentation at the workshop. In addition to these submitted papers, the program committee invited the following researchers to give plenary lectures at the workshop: C. Leiserson, N. Magnenat-Thalmann, M. Snir, U. Vazarani, and 1. Vitter. On behalf of the program committee, we would like to express our appreciation to the six plenary lecturers who accepted our invitation to speak, to all the authors who submitted papers to W ADS'99, and to the Pacific Institute for Mathematical Sciences for their sponsorship. Finally, we would like to express our gratitude to all the people who reviewed papers at the request of the program committee. August 1999 F. Dehne A. Gupta J.-R. Sack R. Tamassia VI Conference Chair: A. Gupta Program Committee Chairs: F. Dehne, A. Gupta, J.-R. Sack, R. Tamassia Program Committee: A. Andersson, A. Apostolico, G. Ausiello, G. Bilardi, K. Clarkson, R. Cleve, M. Cosnard, L. Devroye, P. Dymond, M. Farach-Colton, P. Fraigniaud, M. Goodrich, A.
Author: Mark Allen Weiss Publisher: ISBN: 9780321189967 Category : C++ (Computer program language) Languages : en Pages : 588
Book Description
In this second edition of his successful book, experienced teacher and author Mark Allen Weiss continues to refine and enhance his innovative approach to algorithms and data structures. Written for the advanced data structures course, this text highlights theoretical topics such as abstract data types and the efficiency of algorithms, as well as performance and running time. Before covering algorithms and data structures, the author provides a brief introduction to C++ for programmers unfamiliar with the language. Dr Weiss's clear writing style, logical organization of topics, and extensive use of figures and examples to demonstrate the successive stages of an algorithm make this an accessible, valuable text. New to this Edition *An appendix on the Standard Template Library (STL) *C++ code, tested on multiple platforms, that conforms to the ANSI ISO final draft standard 0201361221B04062001
Author: Steve Scargall Publisher: Apress ISBN: 1484249321 Category : Computers Languages : en Pages : 384
Book Description
Beginning and experienced programmers will use this comprehensive guide to persistent memory programming. You will understand how persistent memory brings together several new software/hardware requirements, and offers great promise for better performance and faster application startup times—a huge leap forward in byte-addressable capacity compared with current DRAM offerings. This revolutionary new technology gives applications significant performance and capacity improvements over existing technologies. It requires a new way of thinking and developing, which makes this highly disruptive to the IT/computing industry. The full spectrum of industry sectors that will benefit from this technology include, but are not limited to, in-memory and traditional databases, AI, analytics, HPC, virtualization, and big data. Programming Persistent Memory describes the technology and why it is exciting the industry. It covers the operating system and hardware requirements as well as how to create development environments using emulated or real persistent memory hardware. The book explains fundamental concepts; provides an introduction to persistent memory programming APIs for C, C++, JavaScript, and other languages; discusses RMDA with persistent memory; reviews security features; and presents many examples. Source code and examples that you can run on your own systems are included. What You’ll Learn Understand what persistent memory is, what it does, and the value it brings to the industry Become familiar with the operating system and hardware requirements to use persistent memory Know the fundamentals of persistent memory programming: why it is different from current programming methods, and what developers need to keep in mind when programming for persistence Look at persistent memory application development by example using the Persistent Memory Development Kit (PMDK)Design and optimize data structures for persistent memoryStudy how real-world applications are modified to leverage persistent memoryUtilize the tools available for persistent memory programming, application performance profiling, and debugging Who This Book Is For C, C++, Java, and Python developers, but will also be useful to software, cloud, and hardware architects across a broad spectrum of sectors, including cloud service providers, independent software vendors, high performance compute, artificial intelligence, data analytics, big data, etc.
Author: Clifford A. Shaffer Publisher: Courier Corporation ISBN: 0486173569 Category : Computers Languages : en Pages : 607
Book Description
Comprehensive treatment focuses on creation of efficient data structures and algorithms and selection or design of data structure best suited to specific problems. This edition uses Java as the programming language.
Author: James M. Abello Publisher: American Mathematical Soc. ISBN: 9780821870938 Category : Mathematics Languages : en Pages : 330
Book Description
This volume presents new research results and current techniques for the design and analysis of external memory algorithms. Topics presented include problems in computational geometry, graph theory, data compression, disk scheduling, linear algebra, statistics, software libraries, text and string processing, visualization, wavelets, and industrial applications.
Author: Jeffrey Scott Vitter
Author: Jeffrey Scott Vitter
Author: Pat Morin
Author: Dzejla Medjedovic
Author: Ulrich Meyer
Author: Clifford A. Shaffer
Author: Frank Dehne
Author: Mark Allen Weiss
Author: Steve Scargall
Author: Clifford A. Shaffer
Author: James M. Abello