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

Chapter 3.  Data Processing Using the Batch Processing API

Even though many people appreciate the potential value of streaming data processing in most industries, there are many use cases where people don't feel it is necessary to process the data in a streaming manner. In all such cases, batch processing is the way to go. So far Hadoop has been the default choice for data processing. However, Flink also supports batch data processing by DataSet API.

For Flink, batch processing is a special case of stream processing. Here is a very interesting article explaining this thought in detail at http://data-artisans.com/batch-is-a-special-case-of-streaming/.

In this chapter, we are going to look at the details regarding DataSet API. This includes the following topics:

  • Data sources

  • Transformations

  • Data sinks

  • Connectors

As we learnt in the previous chapter, any Flink program works on a certain defined anatomy as follows:

The DataSet API is not an exception to this flow. We will look at each step in detail...