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

Chapter 7.  Flink Graph API - Gelly

We are living in the era of social media where everyone is connected to each other by some means. Every single object is in a relationship with another. Facebook and Twitter are excellent examples of social graphs, where x is friends with y and p is following q, and so on. These graphs are so huge that we need an engine which can process them efficiently. If we are surrounded by such graphs, it is very important to analyze them in order to get more insights about their relationships and next-level relationships.

There are various technologies in the market which help us analyze such graphs, for example, graph databases such as Titan and Neo4J, graph processing libraries such as Spark GraphX and Flink Gelly, and so on. In this chapter, we are going to understand the details of graphs and how we can use Flink Gelly to analyze graph data.

So let's get started.