Real-time processing is critical for applications, services, and business operations, in a wide range of industry verticals, from telecommunications and digital marketing to web analytics and weather forecasting. This books aims at enabling practitioners from these various industries and general big data developers to use Spark Streaming to implement their real-time processing pipelines.§§Apache Spark has very quickly established itself as the de facto big data processing engine. In recent years, it has moved beyond in-memory batch analytics to include graph processing, declarative queries, and streaming applications. Its micro batch-processing approach to stream processing enables low-latency application pipelines while retaining the familiar functional programming interface, fault-tolerance model, and in-memory operations of Spark.§§Pro Spark Streaming by Zubair Nabi equips the reader with the right skills and knowledge to leverage Spark Streaming to implement a wide array of real-time, streaming applications. The book walks the user through end-to-end real-time application development atop Spark Streaming, uses real-world examples from multiple domains including telecommunications, digital marketing, and manufacturing to illustrate best practices. The author also delves deep the under the hood to guide application and system optimization, gives details of integration with external data sources, including Apache Kafka, MQTT, Flume, and Twitter and discusses interaction with high-level development solutions and libraries, such as SparkSQL, SparkR, and MLlib§§Pro Spark Streaming by Zubair Nabi will include use cases with complete sample code, which will also be uploaded to github. All in all, this book will act as the bible of Spark Streaming.§§
