Описание: With the revised second edition of this hands-on guide, up-and-coming data scientists will learn how to use the Agile Data Science development methodology to build data applications with Python, Apache Spark, Kafka, and other tools.
Start building Java-based web applications now, even if you're a complete newcomer to Java. Comprehensive and example-driven, this book is all you need to develop dynamic Java-based web applications using JSP, connect to databases with JSF, and put them into action using the popular open source Java web server, Apache Tomcat.
Beginning Jakarta EE Web Development is a comprehensive introduction to building Java-based web applications using JSP, JSF, MySQL, and the Apache Tomcat web application server. Other APIs including JSON, JSTL, and XML parser are covered along the way.
Key concepts are made easy to grasp with numerous working examples and a walk-through of the development of a complete ecommerce project. This book is written for professionals by practicing Java web application professionals and experts.
What You Will Learn
Build Java-based web applications using JSP and JSF with Eclipse Jakarta EE
Configure your database with MySQL
Define XML documents for your applications
Use the Apache MyFaces APIs to create JSF applications
Integrate and implement JSF and JSP together
Build an online ecommerce web application
Who This Book Is For
Programmers new to programming in Java and programming in general.
Автор: McCormick Название: Building High Integrity Applications with SPARK ISBN: 1107656842 ISBN-13(EAN): 9781107656840 Издательство: Cambridge Academ Рейтинг: Цена: 8078.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The formally defined programming language SPARK provides a means to guarantee that a computer program has no errors. This makes it a natural system for designing safety- and security-critical applications. This first introduction to SPARK 2014 will allow students and developers to master the basic concepts for building systems with SPARK.
Описание: This practical guide takes a hands-on approach to implementation and associated methodologies to have you up and running with all that Amazon Kinesis has to offer. You`ll work with use cases and practical examples to be able to ingest, process, analyze, and stream real-time data in no time.
Описание: Part I: Heron Fundamentals.- 1. Stream Processing.- 2. Heron Basics.- 3. Study Heron Code.- Part II: Write Heron Topologies.- 4. Migrate Storm Topology to Heron.- 5. Write Topology Code.- 6. Heron Topology Features.- 7. Heron Streamlet API.- Part III: Operate Heron Clus.- 8. Manage a Topology.- 9. Manage Multiple Topologies.- Part IV: Heron Insights.- 10. Explore Heron.- 11. Extending the Heron Metrics Sink.- 12. Extending Heron Scheduler.- 13. Extending Heron Scheduler.
Автор: Nabi Название: Pro Spark Streaming ISBN: 1484214803 ISBN-13(EAN): 9781484214800 Издательство: Springer Рейтинг: Цена: 3766.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Learn the right cutting-edge skills and knowledge to leverage Spark Streaming to implement a wide array of real-time, streaming applications. Pro Spark Streaming walks you through end-to-end real-time application development using real-world applications, data, and code. Taking an application-first approach, each chapter introduces use cases from a specific industry and uses publicly available datasets from that domain to unravel the intricacies of production-grade design and implementation. The domains covered in the book include social media, the sharing economy, finance, online advertising, telecommunication, and IoT. In the last few years, Spark has become synonymous with big data processing. DStreams enhance the underlying Spark processing engine to support streaming analysis with a novel micro-batch processing model. Pro Spark Streaming by Zubair Nabi will enable you to become a specialist of latency sensitive applications by leveraging the key features of DStreams, micro-batch processing, and functional programming. To this end, the book includes ready-to-deploy examples and actual code. Pro Spark Streaming will act as the bible of Spark Streaming.What You'll Learn:Spark Streaming application development and best practicesLow-level details of discretized streamsThe application and vitality of streaming analytics to a number of industries and domainsOptimization of production-grade deployments of Spark Streaming via configuration recipes and instrumentation using Graphite, collectd, and NagiosIngestion of data from disparate sources including MQTT, Flume, Kafka, Twitter, and a custom HTTP receiverIntegration and coupling with HBase, Cassandra, and RedisDesign patterns for side-effects and maintaining state across the Spark Streaming micro-batch modelReal-time and scalable ETL using data frames, SparkSQL, Hive, and SparkRStreaming machine learning, predictive analytics, and recommendationsMeshing batch processing with stream processing via the Lambda architectureWho This Book Is For:
The audience includes data scientists, big data experts, BI analysts, and data architects.
Название: Data mining in time series and streaming databases ISBN: 9813228032 ISBN-13(EAN): 9789813228030 Издательство: World Scientific Publishing Рейтинг: Цена: 12672.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
This compendium is a completely revised version of an earlier book, Data Mining in Time Series Databases, by the same editors. It provides a unique collection of new articles written by leading experts that account for the latest developments in the field of time series and data stream mining.
The emerging topics covered by the book include weightless neural modeling for mining data streams, using ensemble classifiers for imbalanced and evolving data streams, document stream mining with active learning, and many more. In particular, it addresses the domain of streaming data, which has recently become one of the emerging topics in Data Science, Big Data, and related areas. Existing titles do not provide sufficient information on this topic.
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