These applications have been designed to showcase different aspects of data driven development on OpenShift. They cover various topics and all include complete instructions on architecture, installation, and usage. You will also find videos and slide decks that you may use to present these applications in your own settings.
Ophicleide is an application that can ingest text data from URL sources and process it with Word2vec to create data models. These resulting models can be then queried for word similarity. It contains a REST based training server and a browser based front end for user interaction.
The value-at-risk notebook is a simple example of how to run Jupyter notebooks on OpenShift, Monte Carlo simulations in Spark, and how to interactively explore data to find better ways to model it.
This demo shows how to use the Fabric8 Maven Plugin to deploy a Spark cluster on Openshift.
Graf Zahl is a demonstration application using Spark's Structured Streaming feature to read data from an Apache Kafka topic. It presents a web UI to view the top-k words found on the topic.
jGraf Zahl is a Java implementation of the Graf Zahl application. It is a demonstration of using Spark's Structured Streaming feature to read data from an Apache Kafka topic. It presents a web UI to view the top-k words found on the topic.
This is an example of how to connect your application to data in Ceph using S3 API.
This is a very simple Jupyter notebook application which runs on OpenShift. It shows how to read a file from a remote HDFS filesystem with PySpark.
This is an example of how to connect your application to data in S3.
This source-to-image Java application combines the Apache Spark Pi estimation example with the popular Spring Boot framework. It provides an HTTP microservice which will calculate the value of Pi on demand.
This demo shows how it's possible to integrate AMQP based products with Apache Spark Streaming. It uses the AMQP Spark Streaming connector, which is able to get messages from an AMQP source and pushing them to the Spark engine as micro batches for real time analytics