Time Series DCOS Demo: Crime Buster!

Overview

In this demo we take the crime dataset from the City of Chicago, turn it into a streaming data source and process the data in two paths:

• an online path, using a time series database (InfluxDB) and visualize the crime types in Grafana.
• an offline part, using Spark jobs to create an overlay heat map of aggregated crimes on Google Maps.

Usage

First you need to clone this repo:

$ git clone https://github.com/mesosphere/time-series-demo.git && cd time-series-demo/

Then you can set up and launch the components:

1. Set up Kafka and Spark.
2. Set up and launch the Crime Data Producer.
3. Set up InfluxDB and Grafana online path, configure it and launch it.
4. Set up Kubernetes and the offline reporting Web app and launch it.

We've also recorded a walkthrough of the set up and launch steps as asciicasts:

You can also check out the overview deployment doc for more details.

Dependencies

• Mesosphere DCOS 1.3 {ALL}
  • Marathon 0.11.1 {ALL}
  • Spark 1.5 {ALL}
  • Kubernetes 1.0.6 {OFFLINE}
  • InfluxDB 0.9.4 {ONLINE}
  • Grafana 2.1.3 {ONLINE}
• heatmap.js 2.0 {OFFLINE}
• AWS S3 and the CLI {OFFLINE}
• Docker Hub
  • Offline reporting Web UI {OFFLINE}
  • S3 fetcher {OFFLINE}

To do:

• Create video walkthrough (Michael H9)
• Add real timestamps to InfluxDB data (Michael G)