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Pro Spark Streaming

The Zen of Real-Time Analytics Using Apache Spark
eBook

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<p>Learn the right cutting-edge skills and knowledge to leverage Spark Streaming to implement a wide array of real-time, streaming applications. This book&nbsp;walks you through end-to-end real-time application development using real-world applications, data, and code. Taking an... > mehr
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<p>Learn the right cutting-edge skills and knowledge to leverage Spark Streaming to implement a wide array of real-time, streaming applications. This book&nbsp;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&nbsp;<em>Pro Spark Streaming</em>&nbsp;include social media, the sharing economy, finance, online advertising, telecommunication, and IoT. </p><p></p></p><p></p>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. <em>Pro Spark Streaming </em>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. <em>Pro Spark Streaming</em> will act as the bible of Spark Streaming.<p></p><p><b>What You'll Learn</b></p><ul><li><li>Discover Spark Streaming application development and best practices</li><li>Work with the low-level details of discretized streams</li><li>Optimize production-grade deployments of Spark Streaming via configuration recipes and instrumentation using Graphite, collectd, and Nagios</li><li>Ingest data from disparate sources including MQTT, Flume, Kafka, Twitter, and a custom HTTP receiver</li><li>Integrate and couple with HBase, Cassandra, and Redis</li><li>Take advantage of design patterns for side-effects and maintaining state across the Spark Streaming micro-batch model</li><li>Implement real-time and scalable ETL using data frames, SparkSQL, Hive, and SparkR</li><li>Use streaming machine learning, predictive analytics, and recommendations</li><li>Mesh batch processing with stream processing via the Lambda architecture</li></li></ul><b>Who This Book Is For</b></p><p></p><div><p>Data scientists, big data experts, BI analysts, and data architects.</p></div>
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