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

Download or read book Kafka in Action written by Dylan Scott and published by Simon and Schuster. This book was released on 2022-03-22 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master the wicked-fast Apache Kafka streaming platform through hands-on examples and real-world projects. In Kafka in Action you will learn: Understanding Apache Kafka concepts Setting up and executing basic ETL tasks using Kafka Connect Using Kafka as part of a large data project team Performing administrative tasks Producing and consuming event streams Working with Kafka from Java applications Implementing Kafka as a message queue Kafka in Action is a fast-paced introduction to every aspect of working with Apache Kafka. Starting with an overview of Kafka's core concepts, you'll immediately learn how to set up and execute basic data movement tasks and how to produce and consume streams of events. Advancing quickly, you’ll soon be ready to use Kafka in your day-to-day workflow, and start digging into even more advanced Kafka topics. About the technology Think of Apache Kafka as a high performance software bus that facilitates event streaming, logging, analytics, and other data pipeline tasks. With Kafka, you can easily build features like operational data monitoring and large-scale event processing into both large and small-scale applications. About the book Kafka in Action introduces the core features of Kafka, along with relevant examples of how to use it in real applications. In it, you’ll explore the most common use cases such as logging and managing streaming data. When you’re done, you’ll be ready to handle both basic developer- and admin-based tasks in a Kafka-focused team. What's inside Kafka as an event streaming platform Kafka producers and consumers from Java applications Kafka as part of a large data project About the reader For intermediate Java developers or data engineers. No prior knowledge of Kafka required. About the author Dylan Scott is a software developer in the insurance industry. Viktor Gamov is a Kafka-focused developer advocate. At Confluent, Dave Klein helps developers, teams, and enterprises harness the power of event streaming with Apache Kafka. Table of Contents PART 1 GETTING STARTED 1 Introduction to Kafka 2 Getting to know Kafka PART 2 APPLYING KAFK 3 Designing a Kafka project 4 Producers: Sourcing data 5 Consumers: Unlocking data 6 Brokers 7 Topics and partitions 8 Kafka storage 9 Management: Tools and logging PART 3 GOING FURTHER 10 Protecting Kafka 11 Schema registry 12 Stream processing with Kafka Streams and ksqlDB

Download or read book Kafka Streams in Action Second Edition written by Bill Bejeck and published by Simon and Schuster. This book was released on 2024-05-28 with total page 502 pages. Available in PDF, EPUB and Kindle. Book excerpt: Everything you need to implement stream processing on Apache Kafka? using Kafka Streams and the kqsIDB event streaming database. This totally revised new edition of Kafka Streams in Action has been expanded to cover more of the Kafka platform used for building event-based applications. You'll also find full coverage of ksqlDB, an event streaming database purpose-built for stream processing applications. In Kafka Streams in Action, Second Edition you'll learn how to: Design streaming applications in Kafka Streams with the KStream and the Processor API Integrate external systems with Kafka Connect Enforce data compatibility with Schema Registry Build applications that respond immediately to events in either Kafka Streams or ksqlDB Craft materialized views over streams with ksqlDB Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology The lightweight Kafka Streams library provides exactly the power and simplicity you need for event-based applications, real-time event processing, and message handling in microservices. The ksqlDB database makes it a snap to create applications that respond immediately to events, such as real-time push and pull updates. About the book Kafka Streams in Action, Second Edition 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 also dive into processing event data with ksqlDB. Practical to the very end, it finishes with testing and operational aspects, such as monitoring, debugging, and gives you the opportunity to explore a few end-to-end projects. About the reader Assumes experience with building Java applications, concepts like threading, serialization, and with distributed systems. No knowledge of Kafka or streaming applications required. About the author Bill Bejeck is a Confluent engineer and a Kafka Streams contributor with over 15 years of software development experience. Bill is also a committer on the Apache Kafka project.

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

Download or read book Event Streams in Action written by Valentin Crettaz and published by Simon and Schuster. This book was released on 2019-05-10 with total page 485 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Event Streams in Action is a foundational book introducing the ULP paradigm and presenting techniques to use it effectively in data-rich environments. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Many high-profile applications, like LinkedIn and Netflix, deliver nimble, responsive performance by reacting to user and system events as they occur. In large-scale systems, this requires efficiently monitoring, managing, and reacting to multiple event streams. Tools like Kafka, along with innovative patterns like unified log processing, help create a coherent data processing architecture for event-based applications. About the Book Event Streams in Action teaches you techniques for aggregating, storing, and processing event streams using the unified log processing pattern. In this hands-on guide, you'll discover important application designs like the lambda architecture, stream aggregation, and event reprocessing. You'll also explore scaling, resiliency, advanced stream patterns, and much more! By the time you're finished, you'll be designing large-scale data-driven applications that are easier to build, deploy, and maintain. What's inside Validating and monitoring event streams Event analytics Methods for event modeling Examples using Apache Kafka and Amazon Kinesis About the Reader For readers with experience coding in Java, Scala, or Python. About the Author Alexander Dean developed Snowplow, an open source event processing and analytics platform. Valentin Crettaz is an independent IT consultant with 25 years of experience. Table of Contents PART 1 - EVENT STREAMS AND UNIFIED LOGS Introducing event streams The unified log 24 Event stream processing with Apache Kafka Event stream processing with Amazon Kinesis Stateful stream processing PART 2- DATA ENGINEERING WITH STREAMS Schemas Archiving events Railway-oriented processing Commands PART 3 - EVENT ANALYTICS Analytics-on-read Analytics-on-write

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 315 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

Download or read book Streaming Data written by Andrew Psaltis and published by Simon and Schuster. This book was released on 2017-05-31 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Akka in Action written by Raymond Roestenburg and published by Simon and Schuster. This book was released on 2016-09-20 with total page 681 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Akka in Action is a comprehensive tutorial on building message-oriented systems using Akka. The book takes a hands-on approach, where each new concept is followed by an example that shows you how it works, how to implement the code, and how to (unit) test it. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Akka makes it relatively easy to build applications in the cloud or on devices with many cores that efficiently use the full capacity of the computing power available. It's a toolkit that provides an actor programming model, a runtime, and required support tools for building scalable applications. About the Book Akka in Action shows you how to build message-oriented systems with Akka. This comprehensive, hands-on tutorial introduces each concept with a working example. You'll start with the big picture of how Akka works, and then quickly build and deploy a fully functional REST service out of actors. You'll explore test-driven development and deploying and scaling fault-tolerant systems. After mastering the basics, you'll discover how to model immutable messages, implement domain models, and apply techniques like event sourcing and CQRS. You'l also find a tutorial on building streaming applications using akka-stream and akka-http. Finally, you'l get practical advice on how to customize and extend your Akka system. What's Inside Getting concurrency right Testing and performance tuning Clustered and cloud-based applications Covers Akka version 2.4 About the Reader This book assumes that you're comfortable with Java and Scala. No prior experience with Akka required. About the Authors A software craftsman and architect, Raymond Roestenburg is an Akka committer. Rob Bakker specializes in concurrent back-end systems and systems integration. Rob Williams has more than 20 years of product development experience. Table of Contents Introducing Akka Up and running Test-driven development with actors Fault tolerance Futures Your first distributed Akka app Configuration, logging, and deployment Structural patterns for actors Routing messages Message channels Finite-state machines and agents System integration Streaming Clustering Actor persistence Performance tips Looking ahead

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

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.

Download or read book Grokking Streaming Systems written by Josh Fischer and published by Simon and Schuster. This book was released on 2022-04-19 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: A friendly, framework-agnostic tutorial that will help you grok how streaming systems work—and how to build your own! In Grokking Streaming Systems you will learn how to: Implement and troubleshoot streaming systems Design streaming systems for complex functionalities Assess parallelization requirements Spot networking bottlenecks and resolve back pressure Group data for high-performance systems Handle delayed events in real-time systems Grokking Streaming Systems is a simple guide to the complex concepts behind streaming systems. This friendly and framework-agnostic tutorial teaches you how to handle real-time events, and even design and build your own streaming job that’s a perfect fit for your needs. Each new idea is carefully explained with diagrams, clear examples, and fun dialogue between perplexed personalities! About the technology Streaming systems minimize the time between receiving and processing event data, so they can deliver responses in real time. For applications in finance, security, and IoT where milliseconds matter, streaming systems are a requirement. And streaming is hot! Skills on platforms like Spark, Heron, and Kafka are in high demand. About the book Grokking Streaming Systems introduces real-time event streaming applications in clear, reader-friendly language. This engaging book illuminates core concepts like data parallelization, event windows, and backpressure without getting bogged down in framework-specific details. As you go, you’ll build your own simple streaming tool from the ground up to make sure all the ideas and techniques stick. The helpful and entertaining illustrations make streaming systems come alive as you tackle relevant examples like real-time credit card fraud detection and monitoring IoT services. What's inside Implement and troubleshoot streaming systems Design streaming systems for complex functionalities Spot networking bottlenecks and resolve backpressure Group data for high-performance systems About the reader No prior experience with streaming systems is assumed. Examples in Java. About the author Josh Fischer and Ning Wang are Apache Committers, and part of the committee for the Apache Heron distributed stream processing engine. Table of Contents PART 1 GETTING STARTED WITH STREAMING 1 Welcome to Grokking Streaming Systems 2 Hello, streaming systems! 3 Parallelization and data grouping 4 Stream graph 5 Delivery semantics 6 Streaming systems review and a glimpse ahead PART 2 STEPPING UP 7 Windowed computations 8 Join operations 9 Backpressure 10 Stateful computation 11 Wrap-up: Advanced concepts in streaming systems

Download or read book Real Time Analytics written by Byron Ellis and published by John Wiley & Sons. This book was released on 2014-06-23 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: Construct a robust end-to-end solution for analyzing and visualizing streaming data Real-time analytics is the hottest topic in data analytics today. In Real-Time Analytics: Techniques to Analyze and Visualize Streaming Data, expert Byron Ellis teaches data analysts technologies to build an effective real-time analytics platform. This platform can then be used to make sense of the constantly changing data that is beginning to outpace traditional batch-based analysis platforms. The author is among a very few leading experts in the field. He has a prestigious background in research, development, analytics, real-time visualization, and Big Data streaming and is uniquely qualified to help you explore this revolutionary field. Moving from a description of the overall analytic architecture of real-time analytics to using specific tools to obtain targeted results, Real-Time Analytics leverages open source and modern commercial tools to construct robust, efficient systems that can provide real-time analysis in a cost-effective manner. The book includes: A deep discussion of streaming data systems and architectures Instructions for analyzing, storing, and delivering streaming data Tips on aggregating data and working with sets Information on data warehousing options and techniques Real-Time Analytics includes in-depth case studies for website analytics, Big Data, visualizing streaming and mobile data, and mining and visualizing operational data flows. The book's "recipe" layout lets readers quickly learn and implement different techniques. All of the code examples presented in the book, along with their related data sets, are available on the companion website.

Download or read book Stream Processing with Apache Spark written by Gerard Maas and published by "O'Reilly Media, Inc.". This book was released on 2019-06-05 with total page 396 pages. Available in PDF, EPUB and Kindle. Book excerpt: Before you can build analytics tools to gain quick insights, you first need to know how to process data in real time. With this practical guide, developers familiar with Apache Spark will learn how to put this in-memory framework to use for streaming data. You’ll discover how Spark enables you to write streaming jobs in almost the same way you write batch jobs. Authors Gerard Maas and François Garillot help you explore the theoretical underpinnings of Apache Spark. This comprehensive guide features two sections that compare and contrast the streaming APIs Spark now supports: the original Spark Streaming library and the newer Structured Streaming API. Learn fundamental stream processing concepts and examine different streaming architectures Explore Structured Streaming through practical examples; learn different aspects of stream processing in detail Create and operate streaming jobs and applications with Spark Streaming; integrate Spark Streaming with other Spark APIs Learn advanced Spark Streaming techniques, including approximation algorithms and machine learning algorithms Compare Apache Spark to other stream processing projects, including Apache Storm, Apache Flink, and Apache Kafka Streams

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 Spark The Definitive Guide written by Bill Chambers and published by "O'Reilly Media, Inc.". This book was released on 2018-02-08 with total page 594 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Building Data Streaming Applications with Apache Kafka written by Manish Kumar and published by Packt Publishing Ltd. This book was released on 2017-08-18 with total page 269 pages. Available in PDF, EPUB and Kindle. Book excerpt: Design and administer fast, reliable enterprise messaging systems with Apache Kafka About This Book Build efficient real-time streaming applications in Apache Kafka to process data streams of data Master the core Kafka APIs to set up Apache Kafka clusters and start writing message producers and consumers A comprehensive guide to help you get a solid grasp of the Apache Kafka concepts in Apache Kafka with pracitcalpractical examples Who This Book Is For If you want to learn how to use Apache Kafka and the different tools in the Kafka ecosystem in the easiest possible manner, this book is for you. Some programming experience with Java is required to get the most out of this book What You Will Learn Learn the basics of Apache Kafka from scratch Use the basic building blocks of a streaming application Design effective streaming applications with Kafka using Spark, Storm &, and Heron Understand the importance of a low -latency , high- throughput, and fault-tolerant messaging system Make effective capacity planning while deploying your Kafka Application Understand and implement the best security practices In Detail Apache Kafka is a popular distributed streaming platform that acts as a messaging queue or an enterprise messaging system. It lets you publish and subscribe to a stream of records, and process them in a fault-tolerant way as they occur. This book is a comprehensive guide to designing and architecting enterprise-grade streaming applications using Apache Kafka and other big data tools. It includes best practices for building such applications, and tackles some common challenges such as how to use Kafka efficiently and handle high data volumes with ease. This book first takes you through understanding the type messaging system and then provides a thorough introduction to Apache Kafka and its internal details. The second part of the book takes you through designing streaming application using various frameworks and tools such as Apache Spark, Apache Storm, and more. Once you grasp the basics, we will take you through more advanced concepts in Apache Kafka such as capacity planning and security. By the end of this book, you will have all the information you need to be comfortable with using Apache Kafka, and to design efficient streaming data applications with it. Style and approach A step-by –step, comprehensive guide filled with practical and real- world examples

Download or read book Streaming Systems written by Tyler Akidau and published by "O'Reilly Media, Inc.". This book was released on 2018-07-16 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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