Concurrent Data Processing in Elixir

Concurrent Data Processing in Elixir

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  • Author: Svilen Gospodinov
  • Publisher: Pragmatic Bookshelf
  • ISBN: 1680508962
  • Category : Computers
  • Languages : en
  • Pages : 221

Learn different ways of writing concurrent code in Elixir and increase your application's performance, without sacrificing scalability or fault-tolerance. Most projects benefit from running background tasks and processing data concurrently, but the world of OTP and various libraries can be challenging. Which Supervisor and what strategy to use? What about GenServer? Maybe you need back-pressure, but is GenStage, Flow, or Broadway a better choice? You will learn everything you need to know to answer these questions, start building highly concurrent applications in no time, and write code that's not only fast, but also resilient to errors and easy to scale. Whether you are building a high-frequency stock trading application or a consumer web app, you need to know how to leverage concurrency to build applications that are fast and efficient. Elixir and the OTP offer a range of powerful tools, and this guide will show you how to choose the best tool for each job, and use it effectively to quickly start building highly concurrent applications. Learn about Tasks, supervision trees, and the different types of Supervisors available to you. Understand why processes and process linking are the building blocks of concurrency in Elixir. Get comfortable with the OTP and use the GenServer behaviour to maintain process state for long-running jobs. Easily scale the number of running processes using the Registry. Handle large volumes of data and traffic spikes with GenStage, using back-pressure to your advantage. Create your first multi-stage data processing pipeline using producer, consumer, and producer-consumer stages. Process large collections with Flow, using MapReduce and more in parallel. Thanks to Broadway, you will see how easy it is to integrate with popular message broker systems, or even existing GenStage producers. Start building the high-performance and fault-tolerant applications Elixir is famous for today. What You Need: You'll need Elixir 1.9+ and Erlang/OTP 22+ installed on a Mac OS X, Linux, or Windows machine.


Data Processing Handbook for Complex Biological Data Sources

Data Processing Handbook for Complex Biological Data Sources

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  • Author: Gauri Misra
  • Publisher: Academic Press
  • ISBN: 0128172800
  • Category : Science
  • Languages : en
  • Pages : 191

Data Processing Handbook for Complex Biological Data provides relevant and to the point content for those who need to understand the different types of biological data and the techniques to process and interpret them. The book includes feedback the editor received from students studying at both undergraduate and graduate levels, and from her peers. In order to succeed in data processing for biological data sources, it is necessary to master the type of data and general methods and tools for modern data processing. For instance, many labs follow the path of interdisciplinary studies and get their data validated by several methods. Researchers at those labs may not perform all the techniques themselves, but either in collaboration or through outsourcing, they make use of a range of them, because, in the absence of cross validation using different techniques, the chances for acceptance of an article for publication in high profile journals is weakened. - Explains how to interpret enormous amounts of data generated using several experimental approaches in simple terms, thus relating biology and physics at the atomic level - Presents sample data files and explains the usage of equations and web servers cited in research articles to extract useful information from their own biological data - Discusses, in detail, raw data files, data processing strategies, and the web based sources relevant for data processing


Data-Intensive Text Processing with MapReduce

Data-Intensive Text Processing with MapReduce

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  • Author: Jimmy Lin
  • Publisher: Springer Nature
  • ISBN: 3031021363
  • Category : Computers
  • Languages : en
  • Pages : 171

Our world is being revolutionized by data-driven methods: access to large amounts of data has generated new insights and opened exciting new opportunities in commerce, science, and computing applications. Processing the enormous quantities of data necessary for these advances requires large clusters, making distributed computing paradigms more crucial than ever. MapReduce is a programming model for expressing distributed computations on massive datasets and an execution framework for large-scale data processing on clusters of commodity servers. The programming model provides an easy-to-understand abstraction for designing scalable algorithms, while the execution framework transparently handles many system-level details, ranging from scheduling to synchronization to fault tolerance. This book focuses on MapReduce algorithm design, with an emphasis on text processing algorithms common in natural language processing, information retrieval, and machine learning. We introduce the notion of MapReduce design patterns, which represent general reusable solutions to commonly occurring problems across a variety of problem domains. This book not only intends to help the reader "think in MapReduce", but also discusses limitations of the programming model as well. Table of Contents: Introduction / MapReduce Basics / MapReduce Algorithm Design / Inverted Indexing for Text Retrieval / Graph Algorithms / EM Algorithms for Text Processing / Closing Remarks


Introduction to Computers and Data Processing

Introduction to Computers and Data Processing

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  • Author: Gary B. Shelly
  • Publisher: Brooks/Cole
  • ISBN:
  • Category : Computers
  • Languages : en
  • Pages : 516

Alberta Authorized Resource for grade 10-12 ca 1980-1997.


Knowledge Graphs and Big Data Processing

Knowledge Graphs and Big Data Processing

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  • Author: Valentina Janev
  • Publisher: Springer Nature
  • ISBN: 3030531996
  • Category : Computers
  • Languages : en
  • Pages : 212

This open access book is part of the LAMBDA Project (Learning, Applying, Multiplying Big Data Analytics), funded by the European Union, GA No. 809965. Data Analytics involves applying algorithmic processes to derive insights. Nowadays it is used in many industries to allow organizations and companies to make better decisions as well as to verify or disprove existing theories or models. The term data analytics is often used interchangeably with intelligence, statistics, reasoning, data mining, knowledge discovery, and others. The goal of this book is to introduce some of the definitions, methods, tools, frameworks, and solutions for big data processing, starting from the process of information extraction and knowledge representation, via knowledge processing and analytics to visualization, sense-making, and practical applications. Each chapter in this book addresses some pertinent aspect of the data processing chain, with a specific focus on understanding Enterprise Knowledge Graphs, Semantic Big Data Architectures, and Smart Data Analytics solutions. This book is addressed to graduate students from technical disciplines, to professional audiences following continuous education short courses, and to researchers from diverse areas following self-study courses. Basic skills in computer science, mathematics, and statistics are required.


Visualizing Data

Visualizing Data

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  • Author: Ben Fry
  • Publisher: "O'Reilly Media, Inc."
  • ISBN: 0596519303
  • Category : Computers
  • Languages : en
  • Pages : 384

Provides information on the methods of visualizing data on the Web, along with example projects and code.


Radar Data Processing With Applications

Radar Data Processing With Applications

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  • Author: He You
  • Publisher: John Wiley & Sons
  • ISBN: 1118956869
  • Category : Technology & Engineering
  • Languages : en
  • Pages : 556

Radar Data Processing with Applications Radar Data Processing with Applications He You, Xiu Jianjuan, Guan Xin, Naval Aeronautical and Astronautical University, China A summary of thirty years’ worth of research, this book is a systematic introduction to the theory, development, and latest research results of radar data processing technology. Highlights of the book include sections on data pre-processing technology, track initiation, and data association. Readers are also introduced to maneuvering target tracking, multiple target tracking termination, and track management theory. In order to improve data analysis, the authors have also included group tracking registration algorithms and a performance evaluation of radar data processing. Presents both classical theory and development methods of radar data processing Provides state-of-the-art research results, including data processing for modern radars and tracking performance evaluation theory Includes coverage of performance evaluation, registration algorithm for radar networks, data processing of passive radar, pulse Doppler radar, and phased array radar Features applications for those engaged in information engineering, radar engineering, electronic countermeasures, infrared techniques, sonar techniques, and military command Radar Data Processing with Applications is a handy guide for engineers and industry professionals specializing in the development of radar equipment and data processing. It is also intended as a reference text for electrical engineering graduate students and researchers specializing in signal processing and radars.


Storage Systems

Storage Systems

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  • Author: Alexander Thomasian
  • Publisher: Academic Press
  • ISBN: 0323908098
  • Category : Science
  • Languages : en
  • Pages : 748

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


Data Processing

Data Processing

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  • Author: Susan Wooldridge
  • Publisher: Elsevier
  • ISBN: 1483105245
  • Category : Technology & Engineering
  • Languages : en
  • Pages : 272

Data Processing: Made Simple, Second Edition presents discussions of a number of trends and developments in the world of commercial data processing. The book covers the rapid growth of micro- and mini-computers for both home and office use; word processing and the 'automated office'; the advent of distributed data processing; and the continued growth of database-oriented systems. The text also discusses modern digital computers; fundamental computer concepts; information and data processing requirements of commercial organizations; and the historical perspective of the computer industry. The computer hardware and software and the development and implementation of a computer system are considered. The book tackles careers in data processing; the tasks carried out by the data processing department; and the way in which the data processing department fits in with the rest of the organization. The text concludes by examining some of the problems of running a data processing department, and by suggesting some possible solutions. Computer science students will find the book invaluable.


Processing Data

Processing Data

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  • Author: Linda Brookover Bourque
  • Publisher: SAGE
  • ISBN: 9780803947412
  • Category : Science
  • Languages : en
  • Pages : 102

This volume highlights the theory that decisions made during the design of a data collection instrument influence the kind of data and the format of the data that are available for analysis. Opening with a discussion on the selection of the data collection technique(s) and how this impacts on data processing and the data for later analysis, the book covers key issues such as: should you create your own instrument for a questionnaire? how do you test a questionnaire? what are the characteristics of good data processing? how to deal with missing data? how to scale an evaluation and create subfiles for analysis? In addition, each major section concludes with examples and when appropriate, directs the reader to commonly available computer software that can aid in data processing.