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

Maas, Gerard; Garillot, Francois

ISBN 10: 1491944242 / ISBN 13: 9781491944240

Published by O'Reilly Media, 2019

About this Item

Seller Inventory # 26314136-n

Bibliographic Details

• Title: Stream Processing With Apache Spark : Mastering Structured Streaming and Spark Streaming
• Publisher: O'Reilly Media
• Publication Date: 2019
• Language: English
• ISBN 10: 1491944242
• ISBN 13: 9781491944240
• Binding: Soft cover
• Condition: New

About this title

Synopsis

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.

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 newer Structured Streaming API.

• 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

About the Authors

Gerard Maas is a Principal Engineer at Lightbend, where he works on the seamless integration of Structured Streaming and other scalable stream processing technologies into the Lightbend Platform. Previously, he worked at a cloud-native IoT startup, where he led the data processing team on building the streaming pipelines that pushed Spark Streaming to its limits in terms of throughput. Back then, he published the first comprehensive guide to tune Spark Streaming performance.

Gerard has held leading roles at several startups and large enterprises, building data science governance, cloud-native IoT platforms, telecom platforms, and scalable APIs. He is a regular speaker at technology conferences and contributes to small and large open source projects. Gerard has a degree in Computer Engineering from the Simón Bolívar University, Venezuela. You can find him on twitter as @maasg.

François Garillot is based in Seattle, where he works on distributed computing at Facebook. He received a Ph.D. from École Polytechnique in 2011, and worked on Spark Streaming's back-pressure while working at Lightbend in 2015. His interests include type systems, leveraging programming languages to make analytics simpler to express, and a passion for Scala, Spark, and roasted arabica. When not at work, he can be found enjoying the mountains of the Pacific Northwest.