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 and want to learn how to implement it for streaming jobs, this practical book is a must.
Understand how Spark Streaming fits in the big picture Learn core concepts such as Spark RDDs, Spark Streaming clusters, and the fundamentals of a DStream Discover how to create a robust deployment Dive into streaming algorithmics Learn how to tune, measure, and monitor Spark Streaming
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Big Data Processing with Apache Spark Название: Big Data Processing with Apache Spark Автор: Srini Penchikala Издательство: Год: 2018 Страниц: 104 Формат: PDF Размер: 10 Mb Язык: English...
Practical Apache Spark: Using the Scala API Название: Practical Apache Spark: Using the Scala API Автор: Subhashini Chellappan, Dharanitharan Ganesan Издательство: Apress Год: 2019 Страниц:...
Learning Spark: Lightning-Fast Big Data Analysis Название: Learning Spark: Lightning-Fast Big Data Analysis Автор: Holden Karau, Andy Konwinski, Patrick Wendell Издательство: O'Reilly Media ISBN:...
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Stream Processing with Apache Spark (Early Release) 
