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
Credits
About the Author
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface

History


Flink started as a research project named Stratosphere with the goal of building a next generation big data analytics platform at universities in the Berlin area. It was accepted as an Apache Incubator project on April 16, 2014. Initial versions of Stratosphere were based on a research paper by Nephele at http://stratosphere.eu/assets/papers/Nephele_09.pdf.

The following diagram shows how the evolution of Stratosphere happened over time:

The very first version of Stratosphere was focused on having a runtime, optimizer, and the Java API. Later, as the platform got more mature, it started supporting execution on various local environments as well as on YARN. From version 0.6, Stratosphere was renamed Flink. The latest versions of Flink are focused on supporting various features such as batch processing, stream processing, graph processing, machine learning, and so on.

Flink 0.7 introduced the most important feature of Flink that is, Flink's streaming API. Initially release only had the Java API. Later releases started supporting Scala API as well. Now let's look the current architecture of Flink in the next section.