In this post, I’ll share a demo I gave today to explain some of the processing nodes in the palette of IBM Event Processing.
I’ve found that demonstrations of Event Processing are easier to understand when I don’t need to explain the stream of events I’m processing in the first place. This means I’m always looking for interesting real-world event streams that are widely understood, as they can make for the most effective demos.
With this in mind, today I tried explaining a few of the Event Processing nodes by using them with a live stream of events representing pages that are being created and edited in the English Wikipedia.
Click on the image for a higher-resolution screenshot
Each event contains:
- title of the page
- who made the edit (user ID if logged in, or IP address if anonymous)
- was this the creation of a new page, or an edit of an existing page?
Every edit on Wikipedia results in an event on the Kafka topic, so there are typically a few events a second. It’s not a super-high-throughput topic in Kafka terms, but there are enough events to try out interesting ideas.
Click on the image for a higher-resolution screenshot
Here are a few of the demos I gave today.
This is by no means an exhaustive list of what you could do with this data, but it was enough to let me show what the most commonly-used tools in the palette can do.
