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Bücher von Raul Estrada

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  • - Leverage Apache Kafka 2.0 to simplify real-time data processing for distributed applications
    von Raul Estrada
    43,00 €

    Learn how to use Apache Kafka for efficient processing of distributed applications. This book focuses on programming rather than configuration management of Kafka clusters or Dev Ops. Each chapter focuses on a practical aspect and tries to avoid the tedious theoretical sections. By the end of this book, you will be familiar with solving ...

  • - Over 100 practical recipes on using distributed enterprise messaging to handle real-time data
    von Raul Estrada
    50,00 €

    Apache Kafka is an open source stream processing platform to handle real-time data feeds. This book is a highly practical guide to help you understand the fundamentals as well as the advanced applications of Apache Kafka as an enterprise messaging service. It begins with configuring the basic Kafka APIs, and then shows you how to set up Kafka ...

  • - A Guide to Apache Spark, Mesos, Akka, Cassandra, and Kafka
    von Raul Estrada & Isaac Ruiz
    38,00 €

    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: ScalaThe engine: Spark (SQL, MLib, Streaming, GraphX)The container: Mesos, DockerThe view: AkkaThe storage: CassandraThe message broker: KafkaWhat You Will Learn:Make big data architecture without using complex Greek letter architecturesBuild a cheap but effective cluster infrastructureMake queries, reports, and graphs that business demandsManage and exploit unstructured and No-SQL data sourcesUse tools to monitor the performance of your architectureIntegrate all technologies and decide which ones replace and which ones reinforceWho 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

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