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    Making Sense of Stream Processing: The Philosophy Behind Apache Kafka and Scalable Stream Data - 图书

    2016
    导演:Martin Kleppmann
    How can event streams help make your application more scalable, reliable, and maintainable? In this report, O’Reilly author Martin Kleppmann shows you how stream processing can make your data storage and processing systems more flexible and less complex. Structuring data as a stream of events isn’t new, but with the advent of open source projects such as Apache Kafka and Apache...(展开全部)
    Making Sense of Stream Processing: The Philosophy Behind Apache Kafka and Scalable Stream Data Platforms
    图书

    Kafka: The Definitive Guide: Real-Time Data and Stream Processing at Scale - 图书

    导演:Neha Narkhede
    Neha Narkhede, Confluent联合创始人、CTO,曾在LinkedIn主导基于Kafka和Apache Samza构建流式基础设施,是Kafka作者之一。 Gwen Shapira, Confluent系统架构师,帮助客户构建基于Kafka的系统,在可伸缩数据架构方面拥有十余年经验;曾任Cloudera公司解决方案架构师。另著有《Hadoop应用架构》。 Todd Palino, LinkedIn主任级SRE,负责部署管理大型的Kafka、Zookeeper和Samza集群。 【译者简介】 薛命灯,毕业于厦门大学软件学院,十余年软件开发和架构经验,InfoQ高级社区编辑。译有《硅谷革命》《生产微服务》等书。微信公众号CodeDeep。
    Kafka: The Definitive Guide: Real-Time Data and Stream Processing at Scale
    搜索《Kafka: The Definitive Guide: Real-Time Data and Stream Processing at Scale》
    图书

    Kafka: The Definitive Guide:Real-Time Data and Stream Processing at Scale - 图书

    导演:Neha Narkhede
    Learn how to take full advantage of Apache Kafka, the distributed, publish-subscribe queue for handling real-time data feeds. With this comprehensive book, you'll understand how Kafka works and how it's designed. Authors Neha Narkhede, Gwen Shapira, and Todd Palino show you how to deploy production Kafka clusters; secure, tune, and monitor them; write rock-solid applications th...(展开全部)
    Kafka: The Definitive Guide:Real-Time Data and Stream Processing at Scale
    搜索《Kafka: The Definitive Guide:Real-Time Data and Stream Processing at Scale》
    图书

    Kafka: The Definitive Guide: Real-Time Data and Stream Processing at Scale - 图书

    2018
    导演:Neha Narkhede
    Neha Narkhede, Confluent联合创始人、CTO,曾在LinkedIn主导基于Kafka和Apache Samza构建流式基础设施,是Kafka作者之一。 Gwen Shapira, Confluent系统架构师,帮助客户构建基于Kafka的系统,在可伸缩数据架构方面拥有十余年经验;曾任Cloudera公司解决方案架构师。另著有《Hadoop应用架构》。 Todd Palino, LinkedIn主任级SRE,负责部署管理大型的Kafka、Zookeeper和Samza集群。 【译者简介】 薛命灯,毕业于厦门大学软件学院,十余年软件开发和架构经验,InfoQ高级社区编辑。译有《硅谷革命》《生产微服务》等书。微信公众号CodeDeep。
    Kafka: The Definitive Guide: Real-Time Data and Stream Processing at Scale
    搜索《Kafka: The Definitive Guide: Real-Time Data and Stream Processing at Scale》
    图书

    Kafka: The Definitive Guide:Real-Time Data and Stream Processing at Scale - 图书

    男生小说·都市小说
    导演:Neha Narkhede
    Learn how to take full advantage of Apache Kafka, the distributed, publish-subscribe queue for handling real-time data feeds. With this comprehensive book, you'll understand how Kafka works and how it's designed. Authors Neha Narkhede, Gwen Shapira, and Todd Palino show you how to deploy production Kafka clusters; secure, tune, and monitor them; write rock-solid applications th...(展开全部)
    Kafka: The Definitive Guide:Real-Time Data and Stream Processing at Scale
    搜索《Kafka: The Definitive Guide:Real-Time Data and Stream Processing at Scale》
    图书

    I Heart Logs: Event Data, Stream Processing, and Data Integration - 图书

    2014
    导演:Jay Kreps
    Why a book about logs? That’s easy: the humble log is an abstraction that lies at the heart of many systems, from NoSQL databases to cryptocurrencies. Even though most engineers don’t think much about them, this short book shows you why logs are worthy of your attention. Based on his popular blog posts, LinkedIn principal engineer Jay Kreps shows you how logs work in distribute...(展开全部)
    I Heart Logs: Event Data, Stream Processing, and Data Integration
    搜索《I Heart Logs: Event Data, Stream Processing, and Data Integration》
    图书

    I Heart Logs: Event Data, Stream Processing, and Data Integration - 图书

    2014
    导演:Jay Kreps
    Why a book about logs? That’s easy: the humble log is an abstraction that lies at the heart of many systems, from NoSQL databases to cryptocurrencies. Even though most engineers don’t think much about them, this short book shows you why logs are worthy of your attention. Based on his popular blog posts, LinkedIn principal engineer Jay Kreps shows you how logs work in distribute...(展开全部)
    I Heart Logs: Event Data, Stream Processing, and Data Integration
    搜索《I Heart Logs: Event Data, Stream Processing, and Data Integration》
    图书

    Stream Processing with Apache Flink: Fundamentals, Implementation, and Operation of Streaming - 图书

    导演:Fabian Hueske
    Get started with Apache Flink, the open source framework that enables you to process streaming data—such as user interactions, sensor data, and machine logs—as it arrives. With this practical guide, you’ll learn how to use Apache Flink’s stream processing APIs to implement, continuously run, and maintain real-world applications.Authors Fabian Hueske, one of Flink’s creators, an...(展开全部)
    Stream Processing with Apache Flink: Fundamentals, Implementation, and Operation of Streaming Applications
    搜索《Stream Processing with Apache Flink: Fundamentals, Implementation, and Operation of Streaming Applications》
    图书

    Stream Processing with Apache Flink: Fundamentals, Implementation, and Operation of Streaming - 图书

    导演:Fabian Hueske
    Get started with Apache Flink, the open source framework that enables you to process streaming data—such as user interactions, sensor data, and machine logs—as it arrives. With this practical guide, you’ll learn how to use Apache Flink’s stream processing APIs to implement, continuously run, and maintain real-world applications.Authors Fabian Hueske, one of Flink’s creators, an...(展开全部)
    Stream Processing with Apache Flink: Fundamentals, Implementation, and Operation of Streaming Applications
    搜索《Stream Processing with Apache Flink: Fundamentals, Implementation, and Operation of Streaming Applications》
    图书

    Stream Processing with Apache Spark: Mastering Structured Streaming and Spark Streaming - 图书

    导演:Gerard Maas
    To build analytics tools that provide faster insights, knowing how to process data in real time is a must, and moving from batch processing to stream processing is absolutely required. Fortunately, the Spark in-memory framework/platform for processing data has added an extension devoted to fault-tolerant stream processing: Spark Streaming. If you're familiar with Apache Spark a...(展开全部)
    Stream Processing with Apache Spark: Mastering Structured Streaming and Spark Streaming
    搜索《Stream Processing with Apache Spark: Mastering Structured Streaming and Spark Streaming》
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