TY - BOOK ID - 8285719 TI - Pro Spark Streaming : The Zen of Real-Time Analytics Using Apache Spark PY - 2016 SN - 1484214803 148421479X PB - Berkeley, CA : Apress : Imprint: Apress, DB - UniCat KW - Computer science. KW - Data mining. KW - Application software. KW - Computer Science. KW - Computer Appl. in Administrative Data Processing. KW - Data Mining and Knowledge Discovery. KW - Streaming technology (Telecommunications) KW - Big data. KW - Spark (Electronic resource : Apache Software Foundation) KW - Data sets, Large KW - Large data sets KW - Streamed media KW - Streaming media KW - Streaming resources KW - Apache Spark (Electronic resource : Apache Software Foundation) KW - Application computer programs KW - Application computer software KW - Applications software KW - Apps (Computer software) KW - Computer software KW - Algorithmic knowledge discovery KW - Factual data analysis KW - KDD (Information retrieval) KW - Knowledge discovery in data KW - Knowledge discovery in databases KW - Mining, Data KW - Database searching KW - Informatics KW - Science KW - Data transmission systems KW - Multimedia systems KW - Data sets KW - Information systems. KW - Big Data. UR - https://www.unicat.be/uniCat?func=search&query=sysid:8285719 AB - Learn the right cutting-edge skills and knowledge to leverage Spark Streaming to implement a wide array of real-time, streaming applications. This book 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 Pro Spark Streaming 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 Discover Spark Streaming application development and best practices Work with the low-level details of discretized streams Optimize production-grade deployments of Spark Streaming via configuration recipes and instrumentation using Graphite, collectd, and Nagios Ingest data from disparate sources including MQTT, Flume, Kafka, Twitter, and a custom HTTP receiver Integrate and couple with HBase, Cassandra, and Redis Take advantage of design patterns for side-effects and maintaining state across the Spark Streaming micro-batch model Implement real-time and scalable ETL using data frames, SparkSQL, Hive, and SparkR Use streaming machine learning, predictive analytics, and recommendations Mesh batch processing with stream processing via the Lambda architecture Who This Book Is For Data scientists, big data experts, BI analysts, and data architects. ER -