This repository provides a tutorial for the Gradoop API.
In this tutorial you will learn to:
- use Gradoop for extensive graph analytics.
- use Gradoop-Operators to answer specific analytical questions.
- execute Gradoop on a shared-nothing Flink cluster.
Please find the tutorial instructions in the Wiki of this repository.
This tutorial is based on pre-compiled Gradoop maven artifacts. To set up the tutorial environment please clone this repository.
git clone https://github.com/dbs-leipzig/gradoop-tutorial.git
A sample dataset is already included in the repository.
You also require:
- Java 8
- Maven 3.*
- Graphviz for result visualization (Online GraphViz tool is available here)
- IDE to code :) preferably IntelliJ IDEA
For more information see the Setup page of the tutorial wiki.
Gradoop is an open source (ALv2) research framework for scalable graph analytics built on top of Apache Flink. It offers a graph data model which extends the widespread property graph model by the concept of logical graphs and further provides operators that can be applied on single logical graphs and collections of logical graphs. The combination of these operators allows the flexible, declarative definition of graph analytical workflows. Gradoop can be easily integrated in a workflow which already uses Flink® operators and Flink® libraries (i.e. Gelly, ML and Table).
The project's documentation can be found in our Gradoop-Wiki.