Data Stream A Complete Guide 2020 Edition
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| Author | : Neha Narkhede |
| Publisher | : "O'Reilly Media, Inc." |
| Total Pages | : 315 |
| Release | : 2017-08-31 |
| Genre | : Computers |
| ISBN | : 1491936118 |
Every enterprise application creates data, whether it’s log messages, metrics, user activity, outgoing messages, or something else. And how to move all of this data becomes nearly as important as the data itself. If you’re an application architect, developer, or production engineer new to Apache Kafka, this practical guide shows you how to use this open source streaming platform to handle real-time data feeds. Engineers from Confluent and LinkedIn who are responsible for developing Kafka explain how to deploy production Kafka clusters, write reliable event-driven microservices, and build scalable stream-processing applications with this platform. Through detailed examples, you’ll learn Kafka’s design principles, reliability guarantees, key APIs, and architecture details, including the replication protocol, the controller, and the storage layer. Understand publish-subscribe messaging and how it fits in the big data ecosystem. Explore Kafka producers and consumers for writing and reading messages Understand Kafka patterns and use-case requirements to ensure reliable data delivery Get best practices for building data pipelines and applications with Kafka Manage Kafka in production, and learn to perform monitoring, tuning, and maintenance tasks Learn the most critical metrics among Kafka’s operational measurements Explore how Kafka’s stream delivery capabilities make it a perfect source for stream processing systems
| Author | : Andrew Psaltis |
| Publisher | : Simon and Schuster |
| Total Pages | : 314 |
| Release | : 2017-05-31 |
| Genre | : Computers |
| ISBN | : 1638357242 |
Summary Streaming Data introduces the concepts and requirements of streaming and real-time data systems. The book is an idea-rich tutorial that teaches you to think about how to efficiently interact with fast-flowing data. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology As humans, we're constantly filtering and deciphering the information streaming toward us. In the same way, streaming data applications can accomplish amazing tasks like reading live location data to recommend nearby services, tracking faults with machinery in real time, and sending digital receipts before your customers leave the shop. Recent advances in streaming data technology and techniques make it possible for any developer to build these applications if they have the right mindset. This book will let you join them. About the Book Streaming Data is an idea-rich tutorial that teaches you to think about efficiently interacting with fast-flowing data. Through relevant examples and illustrated use cases, you'll explore designs for applications that read, analyze, share, and store streaming data. Along the way, you'll discover the roles of key technologies like Spark, Storm, Kafka, Flink, RabbitMQ, and more. This book offers the perfect balance between big-picture thinking and implementation details. What's Inside The right way to collect real-time data Architecting a streaming pipeline Analyzing the data Which technologies to use and when About the Reader Written for developers familiar with relational database concepts. No experience with streaming or real-time applications required. About the Author Andrew Psaltis is a software engineer focused on massively scalable real-time analytics. Table of Contents PART 1 - A NEW HOLISTIC APPROACH Introducing streaming data Getting data from clients: data ingestion Transporting the data from collection tier: decoupling the data pipeline Analyzing streaming data Algorithms for data analysis Storing the analyzed or collected data Making the data available Consumer device capabilities and limitations accessing the data PART 2 - TAKING IT REAL WORLD Analyzing Meetup RSVPs in real time
| Author | : Gel Gepsy |
| Publisher | : Webolicus |
| Total Pages | : 141 |
| Release | : |
| Genre | : Computers |
| ISBN | : |
This book was first published in 2015. Since then, the Wi-Fi technology has evolved tremendously. This 2020 edition has important updates about security. Once hackers take control of your Wi-Fi router, they can attack connected devices such as phones, laptops, computers! Fortunately, it is easy to harden the defense of your home network. There are important steps you should take in order to protect your connected devices. An exhaustive catalog of the latest home security devices has been updated in this 2020 edition. Why would you spend a lot of money to have a home security system installed when you can do it yourself! A chapter about health risks has also been added. Are EMF radiations safe? We regularly post updates on our site http://mediastimulus.com such as security alerts and the latest in Wi-Fi technology. Your feedback is always welcome http://mediastimulus.com/contact/
| Author | : Bill Chambers |
| Publisher | : "O'Reilly Media, Inc." |
| Total Pages | : 594 |
| Release | : 2018-02-08 |
| Genre | : Computers |
| ISBN | : 1491912294 |
Learn how to use, deploy, and maintain Apache Spark with this comprehensive guide, written by the creators of the open-source cluster-computing framework. With an emphasis on improvements and new features in Spark 2.0, authors Bill Chambers and Matei Zaharia break down Spark topics into distinct sections, each with unique goals. Youâ??ll explore the basic operations and common functions of Sparkâ??s structured APIs, as well as Structured Streaming, a new high-level API for building end-to-end streaming applications. Developers and system administrators will learn the fundamentals of monitoring, tuning, and debugging Spark, and explore machine learning techniques and scenarios for employing MLlib, Sparkâ??s scalable machine-learning library. Get a gentle overview of big data and Spark Learn about DataFrames, SQL, and Datasetsâ??Sparkâ??s core APIsâ??through worked examples Dive into Sparkâ??s low-level APIs, RDDs, and execution of SQL and DataFrames Understand how Spark runs on a cluster Debug, monitor, and tune Spark clusters and applications Learn the power of Structured Streaming, Sparkâ??s stream-processing engine Learn how you can apply MLlib to a variety of problems, including classification or recommendation
| Author | : Bill Bejeck |
| Publisher | : Simon and Schuster |
| Total Pages | : 410 |
| Release | : 2018-08-29 |
| Genre | : Computers |
| ISBN | : 1638356025 |
Summary Kafka Streams in Action teaches you everything you need to know to implement stream processing on data flowing into your Kafka platform, allowing you to focus on getting more from your data without sacrificing time or effort. Foreword by Neha Narkhede, Cocreator of Apache Kafka Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Not all stream-based applications require a dedicated processing cluster. The lightweight Kafka Streams library provides exactly the power and simplicity you need for message handling in microservices and real-time event processing. With the Kafka Streams API, you filter and transform data streams with just Kafka and your application. About the Book Kafka Streams in Action teaches you to implement stream processing within the Kafka platform. In this easy-to-follow book, you'll explore real-world examples to collect, transform, and aggregate data, work with multiple processors, and handle real-time events. You'll even dive into streaming SQL with KSQL! Practical to the very end, it finishes with testing and operational aspects, such as monitoring and debugging. What's inside Using the KStreams API Filtering, transforming, and splitting data Working with the Processor API Integrating with external systems About the Reader Assumes some experience with distributed systems. No knowledge of Kafka or streaming applications required. About the Author Bill Bejeck is a Kafka Streams contributor and Confluent engineer with over 15 years of software development experience. Table of Contents PART 1 - GETTING STARTED WITH KAFKA STREAMS Welcome to Kafka Streams Kafka quicklyPART 2 - KAFKA STREAMS DEVELOPMENT Developing Kafka Streams Streams and state The KTable API The Processor APIPART 3 - ADMINISTERING KAFKA STREAMS Monitoring and performance Testing a Kafka Streams applicationPART 4 - ADVANCED CONCEPTS WITH KAFKA STREAMS Advanced applications with Kafka StreamsAPPENDIXES Appendix A - Additional configuration information Appendix B - Exactly once semantics
| Author | : Tim Walker |
| Publisher | : John Wiley & Sons |
| Total Pages | : 400 |
| Release | : 2021-02-22 |
| Genre | : Business & Economics |
| ISBN | : 1119328063 |
Competitive advantage in banking comes from effective use of technology The Handbook of Banking Technology provides a blueprint for the future of banking, with deep insight into the technologies at the heart of the industry. The rapid evolution of IT brings continual change and demand for investment — yet keeping pace with these changes has become an essential part of doing business. This book describes how banks can harness the power of current and upcoming technology to add business value and gain a competitive advantage; you'll learn how banks are using technology to drive business today, and which emerging trends are likely to drive the evolution of banking over the next decade. Regulation is playing an ever increasing role in banking and the impact of regulatory change on technology and the management of it are discussed — while mandatory changes put pressure on many of our high street banking brands, their ability to adapt and utilise technology will have a fundamental impact on their success in the rapidly changing marketplace. Technology costs can amount to 15 per cent or more of operational costs and bank leaders need to be able to make informed decisions about technology investments in light of the potential benefits. This book explores the depth and breadth of banking technology to help decision makers stay up to date and drive better business. Assess your current technology against the new banking paradigms Procure the systems needed to protect the bottom line Implement newer technology more efficiently and effectively Ensure compliance and drive value with appropriate technology management Technological change is driven by mass adoption of new channels, innovation from new entrants, and by banks themselves as a means of increasing revenue and reducing costs. The Handbook of Banking Technology offers a comprehensive look at the role of technology in banking, and the impact it will have in the coming years.
| Author | : Tyler Akidau |
| Publisher | : "O'Reilly Media, Inc." |
| Total Pages | : 362 |
| Release | : 2018-07-16 |
| Genre | : Computers |
| ISBN | : 1491983825 |
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
| Author | : Gwen Shapira |
| Publisher | : "O'Reilly Media, Inc." |
| Total Pages | : 499 |
| Release | : 2021-11-05 |
| Genre | : Computers |
| ISBN | : 1492043036 |
Every enterprise application creates data, whether it consists of log messages, metrics, user activity, or outgoing messages. Moving all this data is just as important as the data itself. With this updated edition, application architects, developers, and production engineers new to the Kafka streaming platform will learn how to handle data in motion. Additional chapters cover Kafka's AdminClient API, transactions, new security features, and tooling changes. Engineers from Confluent and LinkedIn responsible for developing Kafka explain how to deploy production Kafka clusters, write reliable event-driven microservices, and build scalable stream processing applications with this platform. Through detailed examples, you'll learn Kafka's design principles, reliability guarantees, key APIs, and architecture details, including the replication protocol, the controller, and the storage layer. You'll examine: Best practices for deploying and configuring Kafka Kafka producers and consumers for writing and reading messages Patterns and use-case requirements to ensure reliable data delivery Best practices for building data pipelines and applications with Kafka How to perform monitoring, tuning, and maintenance tasks with Kafka in production The most critical metrics among Kafka's operational measurements Kafka's delivery capabilities for stream processing systems
| Author | : Huijun Wu |
| Publisher | : Springer Nature |
| Total Pages | : 208 |
| Release | : 2021-04-20 |
| Genre | : Computers |
| ISBN | : 3030600947 |
This book provides both a basic understanding of stream processing in general, and practical guidance for development and research with Apache Heron in particular. It delivers to developers of streaming applications basic and systematic knowledge about Heron, which is today only scattered across project documents, technique blogs and code snippets on the Web. The book is organized in four parts: Part I describes basic knowledge about stream processing, Apache Storm, and Apache Heron (Incubating), and also introduces the Heron source repository. Part II then goes into details and describes two data models to write Heron topologies and often used topology features, including stateful processing. This part is especially targeted at software developers who write topologies using Heron APIs. Next, part III describes Heron tools, including the command-line interface and the user interface, needed to manage a single topology or multiple topologies in a data center. This part is particularly aimed at operators who deploy and manage running jobs. Eventually, part IV describes the Heron source code and how to customize or extend Heron. This part is especially suggested for software engineers who would like to contribute code to the Heron repository and who are curious about Heron insights. Overall, this book aims at professionals who want to process streaming data based on Apache Heron. A basic knowledge of Java and Bash commands for Linux is assumed.
| Author | : Ian Gorton |
| Publisher | : "O'Reilly Media, Inc." |
| Total Pages | : 339 |
| Release | : 2022-06-30 |
| Genre | : Computers |
| ISBN | : 1098106016 |
In many systems, scalability becomes the primary driver as the user base grows. Attractive features and high utility breed success, which brings more requests to handle and more data to manage. But organizations reach a tipping point when design decisions that made sense under light loads suddenly become technical debt. This practical book covers design approaches and technologies that make it possible to scale an application quickly and cost-effectively. Author Ian Gorton takes software architects and developers through the foundational principles of distributed systems. You'll explore the essential ingredients of scalable solutions, including replication, state management, load balancing, and caching. Specific chapters focus on the implications of scalability for databases, microservices, and event-based streaming systems. You will focus on: Foundations of scalable systems: Learn basic design principles of scalability, its costs, and architectural tradeoffs Designing scalable services: Dive into service design, caching, asynchronous messaging, serverless processing, and microservices Designing scalable data systems: Learn data system fundamentals, NoSQL databases, and eventual consistency versus strong consistency Designing scalable streaming systems: Explore stream processing systems and scalable event-driven processing
