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

Execution environment

In order to start writing a Flink program, we first need to get an existing execution environment or create one. Depending upon what you are trying to do, Flink supports:

  • Getting an already existing Flink environment

  • Creating a local environment

  • Creating a remote environment

Typically, you only need to use getExecutionEnvironment(). This will do the right thing based on your context. If you are executing on a local environment in an IDE then it will start a local execution environment. Otherwise, if you are executing the JAR then the Flink cluster manager will execute the program in a distributed manner.

If you want to create a local or remote environment on your own then you can also choose do so by using methods such as createLocalEnvironment() and createRemoteEnvironment (String host, int port, String, and .jar files).