Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Mastering Kafka Streams And Ksqldb
Download Mastering Kafka Streams And Ksqldb full books in PDF, epub, and Kindle. Read online Mastering Kafka Streams And Ksqldb ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Book Synopsis Mastering Kafka Streams and ksqlDB by : Mitch Seymour
Download or read book Mastering Kafka Streams and ksqlDB written by Mitch Seymour and published by O'Reilly Media. This book was released on 2021-02-04 with total page 435 pages. Available in PDF, EPUB and Kindle. Book excerpt: Working with unbounded and fast-moving data streams has historically been difficult. But with Kafka Streams and ksqlDB, building stream processing applications is easy and fun. This practical guide shows data engineers how to use these tools to build highly scalable stream processing applications for moving, enriching, and transforming large amounts of data in real time. Mitch Seymour, data services engineer at Mailchimp, explains important stream processing concepts against a backdrop of several interesting business problems. You'll learn the strengths of both Kafka Streams and ksqlDB to help you choose the best tool for each unique stream processing project. Non-Java developers will find the ksqlDB path to be an especially gentle introduction to stream processing. Learn the basics of Kafka and the pub/sub communication pattern Build stateless and stateful stream processing applications using Kafka Streams and ksqlDB Perform advanced stateful operations, including windowed joins and aggregations Understand how stateful processing works under the hood Learn about ksqlDB's data integration features, powered by Kafka Connect Work with different types of collections in ksqlDB and perform push and pull queries Deploy your Kafka Streams and ksqlDB applications to production
Book Synopsis Mastering Kafka Streams and ksqlDB by : Mitch Seymour
Download or read book Mastering Kafka Streams and ksqlDB written by Mitch Seymour and published by "O'Reilly Media, Inc.". This book was released on 2021-02-04 with total page 505 pages. Available in PDF, EPUB and Kindle. Book excerpt: Working with unbounded and fast-moving data streams has historically been difficult. But with Kafka Streams and ksqlDB, building stream processing applications is easy and fun. This practical guide shows data engineers how to use these tools to build highly scalable stream processing applications for moving, enriching, and transforming large amounts of data in real time. Mitch Seymour, data services engineer at Mailchimp, explains important stream processing concepts against a backdrop of several interesting business problems. You'll learn the strengths of both Kafka Streams and ksqlDB to help you choose the best tool for each unique stream processing project. Non-Java developers will find the ksqlDB path to be an especially gentle introduction to stream processing. Learn the basics of Kafka and the pub/sub communication pattern Build stateless and stateful stream processing applications using Kafka Streams and ksqlDB Perform advanced stateful operations, including windowed joins and aggregations Understand how stateful processing works under the hood Learn about ksqlDB's data integration features, powered by Kafka Connect Work with different types of collections in ksqlDB and perform push and pull queries Deploy your Kafka Streams and ksqlDB applications to production
Book Synopsis Mastering Kafka Streams and Ksqldb by : Mitch Seymour
Download or read book Mastering Kafka Streams and Ksqldb written by Mitch Seymour and published by . This book was released on 2021-04-13 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Working with unbounded and fast-moving data streams has historically been difficult. But with Kafka Streams and ksqlDB, building stream processing applications is easy and fun. This practical guide explores the world of real-time data systems through the lens of these popular technologies and explains important stream processing concepts against a backdrop of interesting business problems. Mitch Seymour, senior data systems engineer at Mailchimp, introduces you to both Kafka Streams and ksqlDB so that you can choose the best tool for each unique stream processing project. Non-Java developers will find the ksqlDB path to be an especially gentle introduction to stream processing. In this book, you'll learn: Basic and advanced uses of Kafka Streams and ksqlDB How to transform, enrich, and process event streams How to build both stateless and stateful stream processing applications The different notions of time and the role it plays in stream processing How to to build event-driven microservices on top of continuous event streams Features, operational characteristics, deployment patterns, and configuration tips for both technologies
Book Synopsis Kafka Streams in Action by : Bill Bejeck
Download or read book Kafka Streams in Action written by Bill Bejeck and published by Simon and Schuster. This book was released on 2018-08-29 with total page 410 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis Kafka: The Definitive Guide by : Neha Narkhede
Download or read book Kafka: The Definitive Guide written by Neha Narkhede and published by "O'Reilly Media, Inc.". This book was released on 2017-08-31 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis Kafka Streams - Real-time Stream Processing by : Prashant Kumar Pandey
Download or read book Kafka Streams - Real-time Stream Processing written by Prashant Kumar Pandey and published by Learning Journal. This book was released on 2019-03-26 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book Kafka Streams - Real-time Stream Processing helps you understand the stream processing in general and apply that skill to Kafka streams programming. This book is focusing mainly on the new generation of the Kafka Streams library available in the Apache Kafka 2.x. The primary focus of this book is on Kafka Streams. However, the book also touches on the other Apache Kafka capabilities and concepts that are necessary to grasp the Kafka Streams programming. Who should read this book? Kafka Streams: Real-time Stream Processing is written for software engineers willing to develop a stream processing application using Kafka Streams library. I am also writing this book for data architects and data engineers who are responsible for designing and building the organization’s data-centric infrastructure. Another group of people is the managers and architects who do not directly work with Kafka implementation, but they work with the people who implement Kafka Streams at the ground level. What should you already know? This book assumes that the reader is familiar with the basics of Java programming language. The source code and examples in this book are using Java 8, and I will be using Java 8 lambda syntax, so experience with lambda will be helpful. Kafka Streams is a library that runs on Kafka. Having a good fundamental knowledge of Kafka is essential to get the most out of Kafka Streams. I will touch base on the mandatory Kafka concepts for those who are new to Kafka. The book also assumes that you have some familiarity and experience in running and working on the Linux operating system.
Download or read book Kafka in Action written by Dylan Scott and published by Simon and Schuster. This book was released on 2022-02-15 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: Kafka in Action is a practical, hands-on guide to building Kafka-based data pipelines. Filled with real-world use cases and scenarios, this book probes Kafka's most common use cases, ranging from simple logging through managing streaming data systems for message routing, analytics, and more. In systems that handle big data, streaming data, or fast data, it's important to get your data pipelines right. Apache Kafka is a wicked-fast distributed streaming platform that operates as more than just a persistent log or a flexible message queue. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
Book Synopsis Stream Processing with Apache Flink by : Fabian Hueske
Download or read book Stream Processing with Apache Flink written by Fabian Hueske and published by O'Reilly Media. This book was released on 2019-04-11 with total page 311 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get started with Apache Flink, the open source framework that powers some of the world’s largest stream processing applications. With this practical book, you’ll explore the fundamental concepts of parallel stream processing and discover how this technology differs from traditional batch data processing. Longtime Apache Flink committers Fabian Hueske and Vasia Kalavri show you how to implement scalable streaming applications with Flink’s DataStream API and continuously run and maintain these applications in operational environments. Stream processing is ideal for many use cases, including low-latency ETL, streaming analytics, and real-time dashboards as well as fraud detection, anomaly detection, and alerting. You can process continuous data of any kind, including user interactions, financial transactions, and IoT data, as soon as you generate them. Learn concepts and challenges of distributed stateful stream processing Explore Flink’s system architecture, including its event-time processing mode and fault-tolerance model Understand the fundamentals and building blocks of the DataStream API, including its time-based and statefuloperators Read data from and write data to external systems with exactly-once consistency Deploy and configure Flink clusters Operate continuously running streaming applications
Download or read book Effective Kafka written by Emil Koutanov and published by . This book was released on 2020-03-17 with total page 466 pages. Available in PDF, EPUB and Kindle. Book excerpt: The software architecture landscape has evolved dramatically over the past decade. Microservices have displaced monoliths. Data and applications are increasingly becoming distributed and decentralised. But composing disparate systems is a hard problem. More recently, software practitioners have been rapidly converging on event-driven architecture as a sustainable way of dealing with complexity - integrating systems without increasing their coupling.In Effective Kafka, Emil Koutanov explores the fundamentals of Event-Driven Architecture - using Apache Kafka - the world's most popular and supported open-source event streaming platform.You'll learn: - The fundamentals of event-driven architecture and event streaming platforms- The background and rationale behind Apache Kafka, its numerous potential uses and applications- The architecture and core concepts - the underlying software components, partitioning and parallelism, load-balancing, record ordering and consistency modes- Installation of Kafka and related tooling - using standalone deployments, clusters, and containerised deployments with Docker- Using CLI tools to interact with and administer Kafka classes, as well as publishing data and browsing topics- Using third-party web-based tools for monitoring a cluster and gaining insights into the event streams- Building stream processing applications in Java 11 using off-the-shelf client libraries- Patterns and best-practice for organising the application architecture, with emphasis on maintainability and testability of the resulting code- The numerous gotchas that lurk in Kafka's client and broker configuration, and how to counter them- Theoretical background on distributed and concurrent computing, exploring factors affecting their liveness and safety- Best-practices for running multi-tenanted clusters across diverse engineering teams, how teams collaborate to build complex systems at scale and equitably share the cluster with the aid of quotas- Operational aspects of running Kafka clusters at scale, performance tuning and methods for optimising network and storage utilisation- All aspects of Kafka security -including network segregation, encryption, certificates, authentication and authorization.The coverage is progressively delivered and carefully aimed at giving you a journey-like experience into becoming proficient with Apache Kafka and Event-Driven Architecture. The goal is to get you designing and building applications. And by the conclusion of this book, you will be a confident practitioner and a Kafka evangelist within your organisation - wielding the knowledge necessary to teach others.
Book Synopsis Mastering Blockchain by : Lorne Lantz
Download or read book Mastering Blockchain written by Lorne Lantz and published by "O'Reilly Media, Inc.". This book was released on 2020-11-13 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: The future will be increasingly distributed. As the publicity surrounding Bitcoin and blockchain has shown, distributed technology and business models are gaining popularity. Yet the disruptive potential of this technology is often obscured by hype and misconception. This detailed guide distills the complex, fast moving ideas behind blockchain into an easily digestible reference manual, showing what's really going on under the hood. Finance and technology pros will learn how a blockchain works as they explore the evolution and current state of the technology, including the functions of cryptocurrencies and smart contracts. This book is for anyone evaluating whether to invest time in the cryptocurrency and blockchain industry. Go beyond buzzwords and see what the technology really has to offer. Learn why Bitcoin was fundamentally important in blockchain's birth Learn how Ethereum has created a fertile ground for new innovations like Decentralized Finance (DeFi), Non-Fungible Tokens (NFTs) and Flash Loans Discover the secrets behind cryptocurrency prices and different forces that affect the highly volatile cryptocurrency markets Learn how cryptocurrencies are used by criminals to carry out nefarious activities Discover how enterprise and governments are leveraging the blockchain including Facebook Understand the challenges of scaling and forking a blockchain Learn how different blockchains work Learn the language of blockchain as industry terms are explained
Book Synopsis 97 Things Every Data Engineer Should Know by : Tobias Macey
Download or read book 97 Things Every Data Engineer Should Know written by Tobias Macey and published by "O'Reilly Media, Inc.". This book was released on 2021-06-11 with total page 243 pages. Available in PDF, EPUB and Kindle. Book excerpt: Take advantage of today's sky-high demand for data engineers. With this in-depth book, current and aspiring engineers will learn powerful real-world best practices for managing data big and small. Contributors from notable companies including Twitter, Google, Stitch Fix, Microsoft, Capital One, and LinkedIn share their experiences and lessons learned for overcoming a variety of specific and often nagging challenges. Edited by Tobias Macey, host of the popular Data Engineering Podcast, this book presents 97 concise and useful tips for cleaning, prepping, wrangling, storing, processing, and ingesting data. Data engineers, data architects, data team managers, data scientists, machine learning engineers, and software engineers will greatly benefit from the wisdom and experience of their peers. Topics include: The Importance of Data Lineage - Julien Le Dem Data Security for Data Engineers - Katharine Jarmul The Two Types of Data Engineering and Data Engineers - Jesse Anderson Six Dimensions for Picking an Analytical Data Warehouse - Gleb Mezhanskiy The End of ETL as We Know It - Paul Singman Building a Career as a Data Engineer - Vijay Kiran Modern Metadata for the Modern Data Stack - Prukalpa Sankar Your Data Tests Failed! Now What? - Sam Bail
Book Synopsis Design Patterns for Cloud Native Applications by : Kasun Indrasiri
Download or read book Design Patterns for Cloud Native Applications written by Kasun Indrasiri and published by "O'Reilly Media, Inc.". This book was released on 2021-05-17 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the immense cost savings and scalability the cloud provides, the rationale for building cloud native applications is no longer in question. The real issue is how. With this practical guide, developers will learn about the most commonly used design patterns for building cloud native applications using APIs, data, events, and streams in both greenfield and brownfield development. You'll learn how to incrementally design, develop, and deploy large and effective cloud native applications that you can manage and maintain at scale with minimal cost, time, and effort. Authors Kasun Indrasiri and Sriskandarajah Suhothayan highlight use cases that effectively demonstrate the challenges you might encounter at each step. Learn the fundamentals of cloud native applications Explore key cloud native communication, connectivity, and composition patterns Learn decentralized data management techniques Use event-driven architecture to build distributed and scalable cloud native applications Explore the most commonly used patterns for API management and consumption Examine some of the tools and technologies you'll need for building cloud native systems
Book Synopsis Oracle Streams 11g Data Replication by : Kirtikumar Deshpande
Download or read book Oracle Streams 11g Data Replication written by Kirtikumar Deshpande and published by McGraw Hill Professional. This book was released on 2010-12-22 with total page 576 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master Oracle Streams 11g Replication Enable real-time information access and data sharing across your distributed framework using the expert information in this Oracle Press guide. Oracle Streams 11g Data Replication explains how to set up and administer a unified enterprise data sharing infrastructure. Learn how to capture, propagate, and apply database changes, transform data, and handle data conflicts. Monitoring, optimizing, and troubleshooting techniques are also covered in this comprehensive volume. Understand Oracle Streams components and architecture Gain in-depth knowledge about capturing, propagating, and applying data manipulation language (DML) and data definition language (DDL) changes Learn how to access and modify the contents of Logical Change Records Build custom procedures for data transformations Configure Oracle Streams replication for the database, schemas, and tables Tune Oracle Streams performance for improved throughput Manage and monitor Oracle Streams using Oracle Enterprise Manager Grid Control Learn from several practical examples and scripts
Book Synopsis Flow Architectures by : James Urquhart
Download or read book Flow Architectures written by James Urquhart and published by "O'Reilly Media, Inc.". This book was released on 2021-01-06 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: Software development today is embracing events and streaming data, which optimizes not only how technology interacts but also how businesses integrate with one another to meet customer needs. This phenomenon, called flow, consists of patterns and standards that determine which activity and related data is communicated between parties over the internet. This book explores critical implications of that evolution: What happens when events and data streams help you discover new activity sources to enhance existing businesses or drive new markets? What technologies and architectural patterns can position your company for opportunities enabled by flow? James Urquhart, global field CTO at VMware, guides enterprise architects, software developers, and product managers through the process. Learn the benefits of flow dynamics when businesses, governments, and other institutions integrate via events and data streams Understand the value chain for flow integration through Wardley mapping visualization and promise theory modeling Walk through basic concepts behind today's event-driven systems marketplace Learn how today's integration patterns will influence the real-time events flow in the future Explore why companies should architect and build software today to take advantage of flow in coming years
Book Synopsis Building Event-Driven Microservices by : Adam Bellemare
Download or read book Building Event-Driven Microservices written by Adam Bellemare and published by "O'Reilly Media, Inc.". This book was released on 2020-07-02 with total page 347 pages. Available in PDF, EPUB and Kindle. Book excerpt: Organizations today often struggle to balance business requirements with ever-increasing volumes of data. Additionally, the demand for leveraging large-scale, real-time data is growing rapidly among the most competitive digital industries. Conventional system architectures may not be up to the task. With this practical guide, you’ll learn how to leverage large-scale data usage across the business units in your organization using the principles of event-driven microservices. Author Adam Bellemare takes you through the process of building an event-driven microservice-powered organization. You’ll reconsider how data is produced, accessed, and propagated across your organization. Learn powerful yet simple patterns for unlocking the value of this data. Incorporate event-driven design and architectural principles into your own systems. And completely rethink how your organization delivers value by unlocking near-real-time access to data at scale. You’ll learn: How to leverage event-driven architectures to deliver exceptional business value The role of microservices in supporting event-driven designs Architectural patterns to ensure success both within and between teams in your organization Application patterns for developing powerful event-driven microservices Components and tooling required to get your microservice ecosystem off the ground
Book Synopsis Cloud Design Patterns by : Alex Homer
Download or read book Cloud Design Patterns written by Alex Homer and published by Microsoft patterns & practices. This book was released on 2014-02-17 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cloud applications have a unique set of characteristics. They run on commodity hardware, provide services to untrusted users, and deal with unpredictable workloads. These factors impose a range of problems that you, as a designer or developer, need to resolve. Your applications must be resilient so that they can recover from failures, secure to protect services from malicious attacks, and elastic in order to respond to an ever changing workload. This guide demonstrates design patterns that can help you to solve the problems you might encounter in many different areas of cloud application development. Each pattern discusses design considerations, and explains how you can implement it using the features of Windows Azure. The patterns are grouped into categories: availability, data management, design and implementation, messaging, performance and scalability, resilience, management and monitoring, and security. You will also see more general guidance related to these areas of concern. It explains key concepts such as data consistency and asynchronous messaging. In addition, there is useful guidance and explanation of the key considerations for designing features such as data partitioning, telemetry, and hosting in multiple datacenters. These patterns and guidance can help you to improve the quality of applications and services you create, and make the development process more efficient. Enjoy!
Download or read book Big Data SMACK written by Raul Estrada and published by Apress. This book was released on 2016-09-29 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to integrate full-stack open source big data architecture and to choose the correct technology—Scala/Spark, Mesos, Akka, Cassandra, and Kafka—in every layer. Big data architecture is becoming a requirement for many different enterprises. So far, however, the focus has largely been on collecting, aggregating, and crunching large data sets in a timely manner. In many cases now, organizations need more than one paradigm to perform efficient analyses. Big Data SMACK explains each of the full-stack technologies and, more importantly, how to best integrate them. It provides detailed coverage of the practical benefits of these technologies and incorporates real-world examples in every situation. This book focuses on the problems and scenarios solved by the architecture, as well as the solutions provided by every technology. It covers the six main concepts of big data architecture and how integrate, replace, and reinforce every layer: The language: Scala The engine: Spark (SQL, MLib, Streaming, GraphX) The container: Mesos, Docker The view: Akka The storage: Cassandra The message broker: Kafka What You Will Learn: Make big data architecture without using complex Greek letter architectures Build a cheap but effective cluster infrastructure Make queries, reports, and graphs that business demands Manage and exploit unstructured and No-SQL data sources Use tools to monitor the performance of your architecture Integrate all technologies and decide which ones replace and which ones reinforce Who This Book Is For: Developers, data architects, and data scientists looking to integrate the most successful big data open stack architecture and to choose the correct technology in every layer
