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 4.  Data Processing Using the Table API

In the earlier chapters, we talked about batch and stream data processing APIs provided by Apache Flink. In this chapter, we are going to talk about Table API which is a SQL interface for data processing in Flink. Table API operates on a table interface which can be created from a dataset and datastream. Once the dataset/datastream is registered as a table, we are free to apply relational operations such as aggregations, joins, and selections.

Tables can also be queried like regular SQL queries. Once the operations are performed, we need to convert the table back to either a dataset or datastream. Apache Flink internally uses another open source project called Apache Calcite https://calcite.apache.org/ for optimizing these query transformations.

In this chapter, we are going to cover the following topics:

  • Registering tables

  • Accessing the registered table

  • Operators

  • Data types

  • SQL

Now let's get started.

In order to use Table API, the very first thing...