Rapid Analytics: On a Raspberry Pi — Part 3
Update: After talking with some IT folks, I realized that I might just be able to make Rapid Analytics on a Raspberry Pi (RAPi) happen. I need to go back a split the memory better on the Pi AND possibly make mini clusters of Pi. How cool would that be? Stay tuned for more on this project.
It is with heavy heart that I must report that my Rapid Analytics on a Raspberry Pi experiment has failed
. It did not fail from a installation or configuration standpoint - that went extremely well - it failed when I tried running it. It was loading into memory and proceeded to hit a resource brick wall. After 40 minutes of just churning the CPU and going nowhere, I killed the process.
This experiment failed purely from a hardware and memory resource aspect. I knew that Rapid Analytics is resource intensive, and that the odds were against me, but I decided to try it anyway and share my results with you.
Here are a few things I’ve learned from this experiment:
- Raspberry Pi is a very capable computer, you can do a lot with it provided you figure out a way to keep your resource fingerprint small;
- You can run MySQL and Apache from the Pi quite easily and installation is a breeze,
- The ARM optimized version of Java works great on the Pi;
- Rapid Analytics 1.3 can be installed and configured, but hardware limitations prevent it from running;
- You can’t use the run.sh to start up RA, it gives you a VM not supported error, you have to use: sudo /opt/jdk1.8.0/bin/java -Xms256M -Xmx496M -jar run.jar,
- I got an appreciation of what Java can do and how it works, and;
- I cant help myself, I’m addicted to Rapidminer and Raspberry Pi.