Back around the December – January time frame, I was trying to implement the Lambda Architecture as described by Nathan Marz. At that time, the early-release version of his upcoming Big Data book was just at chapter 5 or 6, but my goal was to tackle what seemed liked the harder part — real-time (Storm). The book chapters hadn’t yet caught up to it. A few slide decks mentioned their current implementations of a fully thought-out, end-to-end Lambda Architecture implementation that included Storm, but no reliable, easy-to-deploy code was readily available from the interwebs.
In installing Storm, it quickly seemed apparent that having Kafka running upstream of it was one way to support both real-time and batch processing of incoming data, and probably the one of least resistance. So I added installing Kafka to my to-do list.
Cutting edge technology means dealing with rough edges. I downloaded the latest versions of the relevant software components, but the integration of all of them didn’t work. As I found out, the reason was that versions of components that finally worked together with each other for me were not the most recent, but instead maybe a version or two behind.
The code that I ended up with to get Kafka and Storm working together on a toy example using the Twitter Dev Stream is on github here: