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Creating a PageRank Analytics Platform Using Spring Boot Microservices

Creating a PageRank Analytics Platform Using Spring Boot Microservices

These slides introduce you to a sample application that combines multiple microservices with a graph processing platform to rank communities of users on Twitter. The problem we’re going to solve is how to discover communities of influencers on Twitter using a set of seed profiles as inputs. To solve this problem without a background in machine learning or social network analytics might be a bit of a stretch, but we’re going to take a stab at it using a little bit of computer science history. We’re going to use a collection of popular tools as a part of this article’s sample application. The tools we’ll use, in the order of importance, will be: Spring Boot, Neo4j, Apache Spark, Docker, RabbitMQ.

Kenny Bastani

January 28, 2016
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  1. Unless otherwise indicated, these slides are © 2016 Pivotal Software,

    Inc. and licensed under a Creative Commons Attribution-NonCommercial license: http://creativecommons.org/licenses/by-nc/3.0/ Creating a PageRank Analytics Platform Using Spring Boot Microservices Kenny Bastani, Spring Developer Advocate, Pivotal @kennybastani
  2. https://github.com/kbastani/spring-boot-graph-processing-example 4 Agenda ! Sample Application Overview • Ranking Twitter

    profiles • PageRank algorithm ! Graph Processing Platform • Apache Spark GraphX ! Building Microservices • Reference architecture • Spring Data Neo4j repositories • Importing Twitter users • Scheduling PageRank jobs on the Twitter graph
  3. https://github.com/kbastani/spring-boot-graph-processing-example 44 Learn More. Stay Connected. ! @kennybastani on Twitter

    Twitter: twitter.com/springcentral YouTube: spring.io/video LinkedIn: spring.io/linkedin Google Plus: spring.io/gplus