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Before you can build analytics tools to gain quick insights, you first need to know how to process data in real time. With this practical guide, developers familiar with Apache Spark will learn how to put this in-memory framework to use for streaming data. Youβll discover how Spark enables you to write streaming jobs in almost the same way you write batch jobs.
Authors Gerard Maas and François Garillot help you explore the theoretical underpinnings of Apache Spark. This comprehensive guide features two sections that compare and contrast the streaming APIs Spark now supports: the original Spark Streaming library and the n
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Book ID Asin: 1491944242
Book Title: Stream Processing with Apache Spark: Mastering Structured Streaming and Spark Streaming
Book Author: Gerard Maas,Francois Garillot
Book Format: unknownBook Price: unknown
Book Category: Books, Computers & Technology, Databases & Big Data and unknown
Book Rating: 21 ratings
Stream Processing with Apache Spark: Mastering Structured Streaming and Spark Streaming by Gerard Maas,Francois Garillot Book Review
Name: Jediator
Rating: 1.0 out of 5 stars
Title: Lack of Practical Use cases and Code Examples
Date: Reviewed in the United States on December 22, 2020
Review: It looks like the authors put this book together by gathering other books and academic publications, instead of from their own projects and experiences. I brought this book because it has good ratings and the need for a Spark project, but got really disappointed because it is practically useless when you what to use it as a project reference book. I ended up getting more valuable information from Spark's online documentation. For instance, the concept of micro-batch vs. continuous streaming processing, the two most important concepts in Spark streaming, were no where to find. There is not a single line of code or examples for the micro-batch foreach API. I won't even recommend this for beginners since it just jumps from topic to topic with buzzwords and no consistency.
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