Introduction to Apache Flink: Stream Processing for Real Time and Beyond
There’s growing interest in learning how to analyze streaming data in large-scale systems such as web traffic, financial transactions, machine logs, industrial sensors, and many others. But analyzing data streams at scale has been difficult to do well—until now. This practical book delivers a deep introduction to Apache Flink, a highly innovative open source stream processor with a surprising range of capabilities.

Authors Ellen Friedman and Kostas Tzoumas show technical and nontechnical readers alike how Flink is engineered to overcome significant tradeoffs that have limited the effectiveness of other approaches to stream processing. You’ll also learn how Flink has the ability to handle both stream and batch data processing with one technology.

  • Learn the consequences of not doing streaming well—in retail and marketing, IoT, telecom, and banking and finance
  • Explore how to design data architecture to gain the best advantage from stream processing
  • Get an overview of Flink’s capabilities and features, along with examples of how companies use Flink, including in production
  • Take a technical dive into Flink, and learn how it handles time and stateful computation
  • Examine how Flink processes both streaming (unbounded) and batch (bounded) data without sacrificing performance
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Introduction to Apache Flink: Stream Processing for Real Time and Beyond
There’s growing interest in learning how to analyze streaming data in large-scale systems such as web traffic, financial transactions, machine logs, industrial sensors, and many others. But analyzing data streams at scale has been difficult to do well—until now. This practical book delivers a deep introduction to Apache Flink, a highly innovative open source stream processor with a surprising range of capabilities.

Authors Ellen Friedman and Kostas Tzoumas show technical and nontechnical readers alike how Flink is engineered to overcome significant tradeoffs that have limited the effectiveness of other approaches to stream processing. You’ll also learn how Flink has the ability to handle both stream and batch data processing with one technology.

  • Learn the consequences of not doing streaming well—in retail and marketing, IoT, telecom, and banking and finance
  • Explore how to design data architecture to gain the best advantage from stream processing
  • Get an overview of Flink’s capabilities and features, along with examples of how companies use Flink, including in production
  • Take a technical dive into Flink, and learn how it handles time and stateful computation
  • Examine how Flink processes both streaming (unbounded) and batch (bounded) data without sacrificing performance
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Introduction to Apache Flink: Stream Processing for Real Time and Beyond

Introduction to Apache Flink: Stream Processing for Real Time and Beyond

Introduction to Apache Flink: Stream Processing for Real Time and Beyond

Introduction to Apache Flink: Stream Processing for Real Time and Beyond

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Overview

There’s growing interest in learning how to analyze streaming data in large-scale systems such as web traffic, financial transactions, machine logs, industrial sensors, and many others. But analyzing data streams at scale has been difficult to do well—until now. This practical book delivers a deep introduction to Apache Flink, a highly innovative open source stream processor with a surprising range of capabilities.

Authors Ellen Friedman and Kostas Tzoumas show technical and nontechnical readers alike how Flink is engineered to overcome significant tradeoffs that have limited the effectiveness of other approaches to stream processing. You’ll also learn how Flink has the ability to handle both stream and batch data processing with one technology.

  • Learn the consequences of not doing streaming well—in retail and marketing, IoT, telecom, and banking and finance
  • Explore how to design data architecture to gain the best advantage from stream processing
  • Get an overview of Flink’s capabilities and features, along with examples of how companies use Flink, including in production
  • Take a technical dive into Flink, and learn how it handles time and stateful computation
  • Examine how Flink processes both streaming (unbounded) and batch (bounded) data without sacrificing performance

Product Details

ISBN-13: 9781491976586
Publisher: O'Reilly Media, Incorporated
Publication date: 11/04/2016
Pages: 107
Product dimensions: 5.90(w) x 8.80(h) x 0.40(d)

About the Author

Ellen Friedman is a solutions consultant and well-known speaker and author, currently writing mainly about big data topics. She is a committer for the Apache Drill and Apache Mahout projects. With a
PhD in Biochemistry, she has years of experience as a research scientist and has written about a variety of technical topics, including molecular biology, nontraditional inheritance, and oceanography.
Ellen is also coauthor of a book of magic-themed cartoons, A Rabbit Under the Hat (The Edition House). Ellen is on Twitter as
@Ellen_Friedman.

Kostas Tzoumas is cofounder and CEO of data Artisans, the company founded by the original creators of Apache Flink. Kostas is PMC member of Apache Flink and earned a PhD in Computer Science from Aalborg Universitywith postdoctoral experience at TU Berlin. He is author of a number of technical papers and blog articles on stream processing and other data science topics.
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