Download or read book Storm Real time Processing Cookbook written by Quinton Anderson and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: A Cookbook with plenty of practical recipes for different uses of Storm. If you are a Java developer with basic knowledge of real-time processing and would like to learn Storm to process unbounded streams of data in real time, then this book is for you.

Download or read book Building Python Real Time Applications with Storm written by Kartik Bhatnagar and published by Packt Publishing Ltd. This book was released on 2015-12-02 with total page 122 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn to process massive real-time data streams using Storm and Python—no Java required! About This Book Learn to use Apache Storm and the Python Petrel library to build distributed applications that process large streams of data Explore sample applications in real-time and analyze them in the popular NoSQL databases MongoDB and Redis Discover how to apply software development best practices to improve performance, productivity, and quality in your Storm projects Who This Book Is For This book is intended for Python developers who want to benefit from Storm's real-time data processing capabilities. If you are new to Python, you'll benefit from the attention to key supporting tools and techniques such as automated testing, virtual environments, and logging. If you're an experienced Python developer, you'll appreciate the thorough and detailed examples What You Will Learn Install Storm and learn about the prerequisites Get to know the components of a Storm topology and how to control the flow of data between them Ingest Twitter data directly into Storm Use Storm with MongoDB and Redis Build topologies and run them in Storm Use an interactive graphical debugger to debug your topology as it's running in Storm Test your topology components outside of Storm Configure your topology using YAML In Detail Big data is a trending concept that everyone wants to learn about. With its ability to process all kinds of data in real time, Storm is an important addition to your big data “bag of tricks.” At the same time, Python is one of the fastest-growing programming languages today. It has become a top choice for both data science and everyday application development. Together, Storm and Python enable you to build and deploy real-time big data applications quickly and easily. You will begin with some basic command tutorials to set up storm and learn about its configurations in detail. You will then go through the requirement scenarios to create a Storm cluster. Next, you'll be provided with an overview of Petrel, followed by an example of Twitter topology and persistence using Redis and MongoDB. Finally, you will build a production-quality Storm topology using development best practices. Style and approach This book takes an easy-to-follow and a practical approach to help you understand all the concepts related to Storm and Python.

Download or read book LLVM Cookbook written by Mayur Pandey and published by Packt Publishing Ltd. This book was released on 2015-05-30 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book is for compiler programmers who are familiar with concepts of compilers and want to indulge in understanding, exploring, and using LLVM infrastructure in a meaningful way in their work. This book is also for programmers who are not directly involved in compiler projects but are often involved in development phases where they write thousands of lines of code. With knowledge of how compilers work, they will be able to code in an optimal way and improve performance with clean code.

Download or read book Practical Real time Data Processing and Analytics written by Shilpi Saxena and published by Packt Publishing Ltd. This book was released on 2017-09-28 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Hadoop MapReduce v2 Cookbook Second Edition written by Thilina Gunarathne and published by Packt Publishing Ltd. This book was released on 2015-02-25 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you are a Big Data enthusiast and wish to use Hadoop v2 to solve your problems, then this book is for you. This book is for Java programmers with little to moderate knowledge of Hadoop MapReduce. This is also a one-stop reference for developers and system admins who want to quickly get up to speed with using Hadoop v2. It would be helpful to have a basic knowledge of software development using Java and a basic working knowledge of Linux.

Download or read book Storm Real time Processing Cookbook written by Quinton Anderson and published by . This book was released on 2013 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: A cookbook with plenty of practical recipes for different uses of Storm.If you are a Java developer with basic knowledge of real-time processing and would like to learn Storm to process unbounded streams of data in real time, then this book is for you.

Download or read book Clojure Cookbook written by Luke VanderHart and published by "O'Reilly Media, Inc.". This book was released on 2014-03-05 with total page 476 pages. Available in PDF, EPUB and Kindle. Book excerpt: With more than 150 detailed recipes, this cookbook shows experienced Clojure developers how to solve a variety of programming tasks with this JVM language. The solutions cover everything from building dynamic websites and working with databases to network communication, cloud computing, and advanced testing strategies. And more than 60 of the world’s best Clojurians contributed recipes. Each recipe includes code that you can use right away, along with a discussion on how and why the solution works, so you can adapt these patterns, approaches, and techniques to situations not specifically covered in this cookbook. Master built-in primitive and composite data structures Create, develop and publish libraries, using the Leiningen tool Interact with the local computer that’s running your application Manage network communication protocols and libraries Use techniques for connecting to and using a variety of databases Build and maintain dynamic websites, using the Ring HTTP server library Tackle application tasks such as packaging, distributing, profiling, and logging Take on cloud computing and heavyweight distributed data crunching Dive into unit, integration, simulation, and property-based testing Clojure Cookbook is a collaborative project with contributions from some of the world’s best Clojurians, whose backgrounds range from aerospace to social media, banking to robotics, AI research to e-commerce.

Download or read book Storm Applied written by Matthew Jankowski and published by Simon and Schuster. This book was released on 2015-03-30 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Storm Applied is a practical guide to using Apache Storm for the real-world tasks associated with processing and analyzing real-time data streams. This immediately useful book starts by building a solid foundation of Storm essentials so that you learn how to think about designing Storm solutions the right way from day one. But it quickly dives into real-world case studies that will bring the novice up to speed with productionizing Storm. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. Summary Storm Applied is a practical guide to using Apache Storm for the real-world tasks associated with processing and analyzing real-time data streams. This immediately useful book starts by building a solid foundation of Storm essentials so that you learn how to think about designing Storm solutions the right way from day one. But it quickly dives into real-world case studies that will bring the novice up to speed with productionizing Storm. About the Technology It's hard to make sense out of data when it's coming at you fast. Like Hadoop, Storm processes large amounts of data but it does it reliably and in real time, guaranteeing that every message will be processed. Storm allows you to scale with your data as it grows, making it an excellent platform to solve your big data problems. About the Book Storm Applied is an example-driven guide to processing and analyzing real-time data streams. This immediately useful book starts by teaching you how to design Storm solutions the right way. Then, it quickly dives into real-world case studies that show you how to scale a high-throughput stream processor, ensure smooth operation within a production cluster, and more. Along the way, you'll learn to use Trident for stateful stream processing, along with other tools from the Storm ecosystem. This book moves through the basics quickly. While prior experience with Storm is not assumed, some experience with big data and real-time systems is helpful. What's Inside Mapping real problems to Storm components Performance tuning and scaling Practical troubleshooting and debugging Exactly-once processing with Trident About the Authors Sean Allen, Matthew Jankowski, and Peter Pathirana lead the development team for a high-volume, search-intensive commercial web application at TheLadders. Table of Contents Introducing Storm Core Storm concepts Topology design Creating robust topologies Moving from local to remote topologies Tuning in Storm Resource contention Storm internals Trident

Download or read book Recent Developments in Intelligent Computing Communication and Devices written by Srikanta Patnaik and published by Springer. This book was released on 2018-08-22 with total page 1267 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a collection of high-quality, peer-reviewed research papers presented at the International Conference on Intelligent Computing, Communication and Devices (ICCD 2017), discussing all dimensions of intelligent sciences – intelligent computing, intelligent communication, and intelligent devices. Intelligent computing addresses areas such as intelligent and distributed computing, intelligent grid and cloud computing, internet of things, soft computing and engineering applications, data mining and knowledge discovery, semantic and web technology, hybrid systems, agent computing, bioinformatics, and recommendation systems. Intelligent communication is concerned with communication and network technologies, such as mobile broadband and all optical networks that are the key to groundbreaking inventions of intelligent communication technologies. It includes communication hardware, software and networked intelligence, mobile technologies, machine-to-machine communication networks, speech and natural language processing, routing techniques and network analytics, wireless ad hoc and sensor networks, communications and information security, signal, image and video processing, network management, and traffic engineering. Lastly, intelligent devices are any equipment, instruments, or machines that have their own computing capability. As computing technology becomes more advanced and less expensive, it can be incorporated an increasing number of devices of all kinds. This area covers such as embedded systems, radiofrequency identification (RFID), radiofrequency microelectromechanical system (RF MEMS), very-large-scale integration (VLSI) design and electronic devices, analog and mixed-signal integrated circuit (IC) design and testing, microelectromechanical system (MEMS) and microsystems, solar cells and photonics, nanodevices, single electron and spintronics devices, space electronics, and intelligent robotics.

Download or read book Foundations of Data Intensive Applications written by Supun Kamburugamuve and published by John Wiley & Sons. This book was released on 2021-08-11 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Intelligent Systems written by Chiranji Lal Chowdhary and published by CRC Press. This book was released on 2020-01-06 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume helps to fill the gap between data analytics, image processing, and soft computing practices. Soft computing methods are used to focus on data analytics and image processing to develop good intelligent systems. To this end, readers of this volume will find quality research that presents the current trends, advanced methods, and hybridized techniques relating to data analytics and intelligent systems. The book also features case studies related to medical diagnosis with the use of image processing and soft computing algorithms in particular models. Providing extensive coverage of biometric systems, soft computing, image processing, artificial intelligence, and data analytics, the chapter authors discuss the latest research issues, present solutions to research problems, and look at comparative analysis with earlier results. Topics include some of the most important challenges and discoveries in intelligent systems today, such as computer vision concepts and image identification, data analysis and computational paradigms, deep learning techniques, face and speaker recognition systems, and more.

Download or read book Apache Kafka 1 0 Cookbook written by Raúl Estrada and published by Packt Publishing Ltd. This book was released on 2017-12-22 with total page 243 pages. Available in PDF, EPUB and Kindle. Book excerpt: Simplify real-time data processing by leveraging the power of Apache Kafka 1.0 About This Book Use Kafka 1.0 features such as Confluent platforms and Kafka streams to build efficient streaming data applications to handle and process your data Integrate Kafka with other Big Data tools such as Apache Hadoop, Apache Spark, and more Hands-on recipes to help you design, operate, maintain, and secure your Apache Kafka cluster with ease Who This Book Is For This book is for developers and Kafka administrators who are looking for quick, practical solutions to problems encountered while operating, managing or monitoring Apache Kafka. If you are a developer, some knowledge of Scala or Java will help, while for administrators, some working knowledge of Kafka will be useful. What You Will Learn Install and configure Apache Kafka 1.0 to get optimal performance Create and configure Kafka Producers and Consumers Operate your Kafka clusters efficiently by implementing the mirroring technique Work with the new Confluent platform and Kafka streams, and achieve high availability with Kafka Monitor Kafka using tools such as Graphite and Ganglia Integrate Kafka with third-party tools such as Elasticsearch, Logstash, Apache Hadoop, Apache Spark, and more In Detail Apache Kafka provides a unified, high-throughput, low-latency platform to handle real-time data feeds. This book will show you how to use Kafka efficiently, and contains practical solutions to the common problems that developers and administrators usually face while working with it. This practical guide contains easy-to-follow recipes to help you set up, configure, and use Apache Kafka in the best possible manner. You will use Apache Kafka Consumers and Producers to build effective real-time streaming applications. The book covers the recently released Kafka version 1.0, the Confluent Platform and Kafka Streams. The programming aspect covered in the book will teach you how to perform important tasks such as message validation, enrichment and composition.Recipes focusing on optimizing the performance of your Kafka cluster, and integrate Kafka with a variety of third-party tools such as Apache Hadoop, Apache Spark, and Elasticsearch will help ease your day to day collaboration with Kafka greatly. Finally, we cover tasks related to monitoring and securing your Apache Kafka cluster using tools such as Ganglia and Graphite. If you're looking to become the go-to person in your organization when it comes to working with Apache Kafka, this book is the only resource you need to have. Style and approach Following a cookbook recipe-based approach, we'll teach you how to solve everyday difficulties and struggles you encounter using Kafka through hands-on examples.

Download or read book Apache Spark for Data Science Cookbook written by Padma Priya Chitturi and published by Packt Publishing Ltd. This book was released on 2016-12-22 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over insightful 90 recipes to get lightning-fast analytics with Apache Spark About This Book Use Apache Spark for data processing with these hands-on recipes Implement end-to-end, large-scale data analysis better than ever before Work with powerful libraries such as MLLib, SciPy, NumPy, and Pandas to gain insights from your data Who This Book Is For This book is for novice and intermediate level data science professionals and data analysts who want to solve data science problems with a distributed computing framework. Basic experience with data science implementation tasks is expected. Data science professionals looking to skill up and gain an edge in the field will find this book helpful. What You Will Learn Explore the topics of data mining, text mining, Natural Language Processing, information retrieval, and machine learning. Solve real-world analytical problems with large data sets. Address data science challenges with analytical tools on a distributed system like Spark (apt for iterative algorithms), which offers in-memory processing and more flexibility for data analysis at scale. Get hands-on experience with algorithms like Classification, regression, and recommendation on real datasets using Spark MLLib package. Learn about numerical and scientific computing using NumPy and SciPy on Spark. Use Predictive Model Markup Language (PMML) in Spark for statistical data mining models. In Detail Spark has emerged as the most promising big data analytics engine for data science professionals. The true power and value of Apache Spark lies in its ability to execute data science tasks with speed and accuracy. Spark's selling point is that it combines ETL, batch analytics, real-time stream analysis, machine learning, graph processing, and visualizations. It lets you tackle the complexities that come with raw unstructured data sets with ease. This guide will get you comfortable and confident performing data science tasks with Spark. You will learn about implementations including distributed deep learning, numerical computing, and scalable machine learning. You will be shown effective solutions to problematic concepts in data science using Spark's data science libraries such as MLLib, Pandas, NumPy, SciPy, and more. These simple and efficient recipes will show you how to implement algorithms and optimize your work. Style and approach This book contains a comprehensive range of recipes designed to help you learn the fundamentals and tackle the difficulties of data science. This book outlines practical steps to produce powerful insights into Big Data through a recipe-based approach.

Download or read book ArcGIS Pro 3 x Cookbook written by Tripp Corbin, GISP and published by Packt Publishing Ltd. This book was released on 2024-05-03 with total page 564 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leverage the powerful tools in Esri's ArcGIS Pro to perform geospatial analysis Key Features Harness the power of ArcGIS Pro to build informative maps showcasing your GIS data Analyze geospatial data through proximity, spatial statistics, and hotspot analysis Increase data entry efficiency and quality with advanced geodatabase behavior Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionArcGIS Pro, Esri's newest desktop GIS application, offers powerful tools for visualizing, maintaining, and analyzing data. This cookbook will help existing ArcMap users transition to ArcGIS Pro and teach new users how to utilize its GIS tools effectively. You’ll learn how to create geodatabases, convert data formats, link tables from outside sources, edit 2D and 3D data, ensure data integrity with topology, and enable advanced geodatabase behavior. By the end, you'll be able to effectively use ArcGIS Pro as your primary desktop GIS application, maintaining, analyzing, and displaying data using common methods and tools.What you will learn Navigate the new ArcGIS Pro ribbon interface Create and publish 2D and 3D maps Edit data using standard tools and topology Link data together using joins, relates, and relationship classes Create a new geodatabase and validate data using domains, subtypes, attribute rules, and contingent values Convert data formats and project data to new coordinate systems Perform proximity analysis and map clusters with hotspot analysis Conduct advanced 3D analysis with 3D Analyst extension Who this book is for This book is for GIS professionals, architects, specialists, analysts, and technicians looking to learn how to use ArcGIS Pro and the powerful data editing, analysis, and creation tools it offers. Those who are just getting started with ArcGIS Pro and wish to expand their skills, as well as those who want to migrate to this platform will also find this book helpful. While some basic GIS experience is helpful, it’s not a prerequisite.

Download or read book Real Time Big Data Analytics written by Sumit Gupta and published by Packt Publishing Ltd. This book was released on 2016-02-26 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: Design, process, and analyze large sets of complex data in real time About This Book Get acquainted with transformations and database-level interactions, and ensure the reliability of messages processed using Storm Implement strategies to solve the challenges of real-time data processing Load datasets, build queries, and make recommendations using Spark SQL Who This Book Is For If you are a Big Data architect, developer, or a programmer who wants to develop applications/frameworks to implement real-time analytics using open source technologies, then this book is for you. What You Will Learn Explore big data technologies and frameworks Work through practical challenges and use cases of real-time analytics versus batch analytics Develop real-word use cases for processing and analyzing data in real-time using the programming paradigm of Apache Storm Handle and process real-time transactional data Optimize and tune Apache Storm for varied workloads and production deployments Process and stream data with Amazon Kinesis and Elastic MapReduce Perform interactive and exploratory data analytics using Spark SQL Develop common enterprise architectures/applications for real-time and batch analytics In Detail Enterprise has been striving hard to deal with the challenges of data arriving in real time or near real time. Although there are technologies such as Storm and Spark (and many more) that solve the challenges of real-time data, using the appropriate technology/framework for the right business use case is the key to success. This book provides you with the skills required to quickly design, implement and deploy your real-time analytics using real-world examples of big data use cases. From the beginning of the book, we will cover the basics of varied real-time data processing frameworks and technologies. We will discuss and explain the differences between batch and real-time processing in detail, and will also explore the techniques and programming concepts using Apache Storm. Moving on, we'll familiarize you with “Amazon Kinesis” for real-time data processing on cloud. We will further develop your understanding of real-time analytics through a comprehensive review of Apache Spark along with the high-level architecture and the building blocks of a Spark program. You will learn how to transform your data, get an output from transformations, and persist your results using Spark RDDs, using an interface called Spark SQL to work with Spark. At the end of this book, we will introduce Spark Streaming, the streaming library of Spark, and will walk you through the emerging Lambda Architecture (LA), which provides a hybrid platform for big data processing by combining real-time and precomputed batch data to provide a near real-time view of incoming data. Style and approach This step-by-step is an easy-to-follow, detailed tutorial, filled with practical examples of basic and advanced features. Each topic is explained sequentially and supported by real-world examples and executable code snippets.

Download or read book Big Data Analytics written by Ladjel Bellatreche and published by Springer Nature. This book was released on 2021-01-02 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 8th International Conference on Big Data Analytics, BDA 2020, which took place during December 15-18, 2020, in Sonepat, India. The 11 full and 3 short papers included in this volume were carefully reviewed and selected from 48 submissions; the book also contains 4 invited and 3 tutorial papers. The contributions were organized in topical sections named as follows: data science systems; data science architectures; big data analytics in healthcare; information interchange of Web data resources; and business analytics.

Download or read book The Stances of e Government written by Puneet Kumar and published by CRC Press. This book was released on 2018-11-01 with total page 206 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the three inevitable facets of e-government, namely policies, processes and technologies. The policies discusses the genesis and revitalization of government policies; processes talks about ongoing e-government practices across developing countries; technology reveals the inclusion of novel technologies.