Book Image

Learning Apache Flink

By : Tanmay Deshpande
Book Image

Learning Apache Flink

By: Tanmay Deshpande

Overview of this book

<p>With the advent of massive computer systems, organizations in different domains generate large amounts of data on a real-time basis. The latest entrant to big data processing, Apache Flink, is designed to process continuous streams of data at a lightning fast pace.</p> <p>This book will be your definitive guide to batch and stream data processing with Apache Flink. The book begins with introducing the Apache Flink ecosystem, setting it up and using the DataSet and DataStream API for processing batch and streaming datasets. Bringing the power of SQL to Flink, this book will then explore the Table API for querying and manipulating data. In the latter half of the book, readers will get to learn the remaining ecosystem of Apache Flink to achieve complex tasks such as event processing, machine learning, and graph processing. The final part of the book would consist of topics such as scaling Flink solutions, performance optimization and integrating Flink with other tools such as ElasticSearch.</p> <p>Whether you want to dive deeper into Apache Flink, or want to investigate how to get more out of this powerful technology, you’ll find everything you need inside.</p>
Table of Contents (17 chapters)
Learning Apache Flink
About the Author
About the Reviewers
Customer Feedback

What is complex event processing?

CEP analyzes streams of disparate events occurring with high frequency and low latency. These days, streaming events can be found in various industries, for example:

  • In the oil and gas domain, sensor data comes from various drilling tools or from upstream oil pipeline equipment

  • In the security domain, activity data, malware information, and usage pattern data come from various end points

  • In the wearable domain, data comes from various wrist bands with information about your heart beat rate, your activity, and so on

  • In the banking domain, data comes from credit card usage, banking activities, and so on

It is very important to analyze variation patterns to get notified in real time about any change in the regular assembly. CEP can understand patterns across the streams of events, sub-events, and their sequences. CEP helps to identify meaningful patterns and complex relationships among unrelated events, and sends notifications in real and near real time to prevent...