So you are energized about HPCC Systems and ready to take the leap and “Jump In!” There are three things you will need to do.
- Install the server components and boot up your own supercomputer.
- Load up some data.
- Install the ECL programming interface and “do something!”
This post only deals with Step 1: Boot it Up. The obvious questions are… “From a standing start, how easy is it to install and boot up the HPCC Systems platform?” “Do I need to be a Linux expert?” “How long does it take to be up and running?” All good questions. The answers in order are “Easy”, “No” and “Less than 5 mins” (for a one node). When you want to scale up to a multinode environment there is some additional configuration but for the purposes of “Jumping in” you don’t need to care. This is because of two key reasons:
- A suitable one node with enough memory and processors is almost always sufficient for initial data science projects.
- Any ECL you hack together will be the same regardless of whether it is a 1 node or a 1000 nodes!
So a one node is a great place to start small; scaling up from there to a massive multi-node supercomputer is easy enough. For the purpose of booting up a single node HPCC System, you can download and boot up the HPCC Systems VM or if you have spare 64bit hardware burning a hole on your back shelf somewhere (you know you do!). I will install it by hand on an Ubuntu 12.04 desktop so you can see for yourself, without smoke and mirrors. It is so easy even a 10 year old can install it, so my youngest daughter has kindly agreed to narrate it for me to spice things up for fun! There are 5 simple steps to install the platform:
- Download the platform install from the HPCC Systems website.
- Install the platform: sudo dpkg -i hpcc…
- Resolve dependancies: sudo apt-get install -f
- Start the platform: sudo service hpcc-init start
- Open ECLWatch web admin tool.
There you have it! Your own supercomputer platform in 5 mins or less! Formal installation instructions can be found at Installing and running the HPCC Systems platform. So what next? Step 2: Load some data! Stay tuned!