Stream Processing with Apache Spark: Mastering Structured Streaming and Spark Streaming

Stream Processing with Apache Spark: Mastering Structured Streaming and Spark Streaming

eBook Details:

  • Paperback: 452 pages
  • Publisher: WOW! eBook; 1st edition (June 17, 2019)
  • Language: English
  • ISBN-10: 1491944242
  • ISBN-13: 978-1491944240

eBook Description:

Stream Processing with Apache Spark: Mastering Structured Streaming and Spark Streaming

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. You’ll discover how Spark enables you to write streaming jobs in almost the same way you write batch jobs.

  • Learn fundamental stream processing concepts and examine different streaming architectures
  • Explore Structured Streaming through practical examples; learn different aspects of stream processing in detail
  • Create and operate streaming jobs and applications with Spark Streaming; integrate Spark Streaming with other Spark APIs
  • Learn advanced Spark Streaming techniques, including approximation algorithms and machine learning algorithms
  • Compare Apache Spark to other stream processing projects, including Apache Storm, Apache Flink, and Apache Kafka Streams

Authors Gerard Maas and François Garillot help you explore the theoretical underpinnings of Apache Spark. This Stream Processing with Apache Spark comprehensive guide features two sections that compare and contrast the streaming APIs Spark now supports: the original Spark Streaming library and the newer Structured Streaming API.

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1 Response

  1. March 3, 2020

    […] Spark distributed data processing platform provides an easy-to-implement tool for ingesting, streaming, and processing data from any source. […]

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