Concurrent Data Processing in Elixir

2021-07-25
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

2019-03-23
Data Processing Handbook for Complex Biological Data Sources

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  • Author: Gauri Misra
  • Publisher: Academic Press
  • ISBN: 0128172800
  • Category : Medical
  • Languages : en
  • Pages : 188

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 Processing

2013-10-22
Data Processing

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  • Author: Susan Wooldridge
  • Publisher: Elsevier
  • ISBN: 1483105245
  • Category : Technology & Engineering
  • Languages : en
  • Pages : 256

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.

Practical Real-time Data Processing and Analytics

2017-09-28
Practical Real-time Data Processing and Analytics

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  • Author: Shilpi Saxena
  • Publisher: Packt Publishing Ltd
  • ISBN: 1787289869
  • Category : Computers
  • Languages : en
  • Pages : 354

A practical guide to help you tackle different real-time data processing and analytics problems using the best tools for each scenario About This Book Learn about the various challenges in real-time data processing and use the right tools to overcome them This book covers popular tools and frameworks such as Spark, Flink, and Apache Storm to solve all your distributed processing problems A practical guide filled with examples, tips, and tricks to help you perform efficient Big Data processing in real-time Who This Book Is For If you are a Java developer who would like to be equipped with all the tools required to devise an end-to-end practical solution on real-time data streaming, then this book is for you. Basic knowledge of real-time processing would be helpful, and knowing the fundamentals of Maven, Shell, and Eclipse would be great. What You Will Learn Get an introduction to the established real-time stack Understand the key integration of all the components Get a thorough understanding of the basic building blocks for real-time solution designing Garnish the search and visualization aspects for your real-time solution Get conceptually and practically acquainted with real-time analytics Be well equipped to apply the knowledge and create your own solutions In Detail With the rise of Big Data, there is an increasing need to process large amounts of data continuously, with a shorter turnaround time. Real-time data processing involves continuous input, processing and output of data, with the condition that the time required for processing is as short as possible. This book covers the majority of the existing and evolving open source technology stack for real-time processing and analytics. You will get to know about all the real-time solution aspects, from the source to the presentation to persistence. Through this practical book, you'll be equipped with a clear understanding of how to solve challenges on your own. We'll cover topics such as how to set up components, basic executions, integrations, advanced use cases, alerts, and monitoring. You'll be exposed to the popular tools used in real-time processing today such as Apache Spark, Apache Flink, and Storm. Finally, you will put your knowledge to practical use by implementing all of the techniques in the form of a practical, real-world use case. By the end of this book, you will have a solid understanding of all the aspects of real-time data processing and analytics, and will know how to deploy the solutions in production environments in the best possible manner. Style and Approach In this practical guide to real-time analytics, each chapter begins with a basic high-level concept of the topic, followed by a practical, hands-on implementation of each concept, where you can see the working and execution of it. The book is written in a DIY style, with plenty of practical use cases, well-explained code examples, and relevant screenshots and diagrams.

Intelligent Data Analysis

2020-07-13
Intelligent Data Analysis

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  • Author: Deepak Gupta
  • Publisher: John Wiley & Sons
  • ISBN: 1119544459
  • Category : Technology & Engineering
  • Languages : en
  • Pages : 428

This book focuses on methods and tools for intelligent data analysis, aimed at narrowing the increasing gap between data gathering and data comprehension, and emphasis will also be given to solving of problems which result from automated data collection, such as analysis of computer-based patient records, data warehousing tools, intelligent alarming, effective and efficient monitoring, and so on. This book aims to describe the different approaches of Intelligent Data Analysis from a practical point of view: solving common life problems with data analysis tools.

Essentials of Geophysical Data Processing

2021-10-21
Essentials of Geophysical Data Processing

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  • Author: Clark R. Wilson
  • Publisher: Cambridge University Press
  • ISBN: 1108950485
  • Category : Science
  • Languages : en
  • Pages :

A concise introduction to geophysical data processing - many of the techniques associated with the general field of time series analysis - for advanced students, researchers, and professionals. The textbook begins with calculus before transitioning to discrete time series via the sampling theorem, aliasing, use of complex sinusoids, development of the discrete Fourier transform from the Fourier series, and an overview of linear digital filter types and descriptions. Aimed at senior undergraduate and graduate students in geophysics, environmental science, and engineering with no previous background in linear algebra, probability, or statistics, this textbook draws scenarios and datasets from across the world of geophysics, and shows how data processing techniques can be applied to real-world problems using detailed examples, illustrations, and exercises (using MATLAB or similar computing environment). Online supplementary resources include datasets for students, and a solutions manual and all the figures from the book as PowerPoints for course instructors.

Imaging Technologies and Data Processing for Food Engineers

2016-01-19
Imaging Technologies and Data Processing for Food Engineers

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  • Author: Nesli Sozer
  • Publisher: Springer
  • ISBN: 3319247352
  • Category : Technology & Engineering
  • Languages : en
  • Pages : 353

Food products are complex in nature which makes their analysis difficult. Different scientific disciplines such as biochemistry, microbiology, and nutrition, together with engineering concepts are involved in their characterization. However, imaging of food materials and data analysis has gained more importance due to innovations in the food industry, as well as the emergence of food nanotechnology. Image analysis protocols and techniques can be used in food structure analysis and process monitoring. Therefore, food structure imaging is crucial for various sections of the food chain starting from the raw material to the end product. This book provides information on imaging techniques such as electron microscopy, laser microscopy, x-ray tomography, raman and infrared imaging, together with data analysis protocols. It addresses the most recent advances in imaging technologies and data analysis of grains, liquid food systems (i.e. emulsions and gels), semi-solid and solid foams (i.e. bakery products, dough, expanded snacks), protein films, fruits and vegetable confectionery and nuts. This book also: Provides in-depth view of raw material characterization and process control Covers structure-functionality and structure-texture relationships Reviews applications to emerging areas of food science with an insight into future trends

Introduction to Computers and Data Processing

1980
Introduction to Computers and Data Processing

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

Streaming Systems

2018-07-16
Streaming Systems

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  • Author: Tyler Akidau
  • Publisher: "O'Reilly Media, Inc."
  • ISBN: 1491983825
  • Category : Computers
  • Languages : en
  • Pages : 391

Streaming data is a big deal in big data these days. As more and more businesses seek to tame the massive unbounded data sets that pervade our world, streaming systems have finally reached a level of maturity sufficient for mainstream adoption. With this practical guide, data engineers, data scientists, and developers will learn how to work with streaming data in a conceptual and platform-agnostic way. Expanded from Tyler Akidau’s popular blog posts "Streaming 101" and "Streaming 102", this book takes you from an introductory level to a nuanced understanding of the what, where, when, and how of processing real-time data streams. You’ll also dive deep into watermarks and exactly-once processing with co-authors Slava Chernyak and Reuven Lax. You’ll explore: How streaming and batch data processing patterns compare The core principles and concepts behind robust out-of-order data processing How watermarks track progress and completeness in infinite datasets How exactly-once data processing techniques ensure correctness How the concepts of streams and tables form the foundations of both batch and streaming data processing The practical motivations behind a powerful persistent state mechanism, driven by a real-world example How time-varying relations provide a link between stream processing and the world of SQL and relational algebra

Data Processing and Reconciliation for Chemical Process Operations

1999-10-25
Data Processing and Reconciliation for Chemical Process Operations

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  • Author: José A. Romagnoli
  • Publisher: Elsevier
  • ISBN: 9780080530277
  • Category : Technology & Engineering
  • Languages : en
  • Pages : 270

Computer techniques have made online measurements available at every sampling period in a chemical process. However, measurement errors are introduced that require suitable techniques for data reconciliation and improvements in accuracy. Reconciliation of process data and reliable monitoring are essential to decisions about possible system modifications (optimization and control procedures), analysis of equipment performance, design of the monitoring system itself, and general management planning. While the reconciliation of the process data has been studied for more than 20 years, there is no single source providing a unified approach to the area with instructions on implementation. Data Processing and Reconciliation for Chemical Process Operations is that source. Competitiveness on the world market as well as increasingly stringent environmental and product safety regulations have increased the need for the chemical industry to introduce such fast and low cost improvements in process operations. Introduces the first unified approach to this important field Bridges theory and practice through numerous worked examples and industrial case studies Provides a highly readable account of all aspects of data classification and reconciliation Presents the reader with material, problems, and directions for further study