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

What is a graph?

In the computer science field, a graph is a means of representing relationships amongst the object. It consists of a set of vertices connected via edges. Vertices are objects on a plane, identified by co-ordinates or some unique id/name while Edges are the connecting links between the vertices having certain weights or the relationship. A graph can be directed or undirected. In a directed graph, the edges are directed from one vertex to other while there is no direction for edges in undirected graph.

The following diagram shows the basic representation of a directed graph:

A graph structure can be used for various purposes, such as finding the shortest path to a certain destination, or it could be used for finding out the degree of relationship between certain vertices, or it could be used for finding out the nearest neighbor.

Now let's dive deep into Flink's Graph API - Gelly.