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Practical Real-time Data Processing and Analytics

You're reading from   Practical Real-time Data Processing and Analytics Distributed Computing and Event Processing using Apache Spark, Flink, Storm, and Kafka

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Product type Paperback
Published in Sep 2017
Publisher Packt
ISBN-13 9781787281202
Length 360 pages
Edition 1st Edition
Languages
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Authors (2):
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Shilpi Saxena Shilpi Saxena
Author Profile Icon Shilpi Saxena
Shilpi Saxena
Saurabh Gupta Saurabh Gupta
Author Profile Icon Saurabh Gupta
Saurabh Gupta
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Toc

Table of Contents (14) Chapters Close

Preface 1. Introducing Real-Time Analytics FREE CHAPTER 2. Real Time Applications – The Basic Ingredients 3. Understanding and Tailing Data Streams 4. Setting up the Infrastructure for Storm 5. Configuring Apache Spark and Flink 6. Integrating Storm with a Data Source 7. From Storm to Sink 8. Storm Trident 9. Working with Spark 10. Working with Spark Operations 11. Spark Streaming 12. Working with Apache Flink 13. Case Study

Gelly


Gelly is a graph API for Flink. In Gelly, graphs can be created, transformed, and modified. Gelly API provides all the basic and advanced functions of graph analytics. You can also select the different graph algorithms.

Gelly API

Gelly provides the API with the ability to take actions on graphs. We will discuss the API's in the follwing section.

Graph representation

A graph is represented by a DataSet of Vertices and Edges. Graph nodes are represented by Vertex type. A vertex is defined by unique ID and value. A NullValue can be defined for a Vertex with no value. The following are the methods used for creating vertex in a graph:

Vertex<String, Long> v = new Vertex<String, Long>("vertex 1", 8L);
Vertex<String, NullValue> v = new Vertex<String, NullValue>("vertex 1", NullValue.getInstance());

Graph edges are represented by edge type. An edge is defined by source ID (ID of source vertex), target ID (ID of target vertex), and optional value. The source and target IDs...

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