MySQL Cluster running on Raspberry Pi

MySQL Cluster running on Raspberry Pi
MySQL Cluster running on Raspberry Pi

I start a long weekend tonight and it’s the kids’ last day of school before their school holidays and so last night felt like the right time to play a bit. This week I received my Raspberry Pi – if you haven’t heard of it then you should take a look at the Raspberry Pi FAQ – basically it’s a ridiculously cheap ($25 or $35 if you want the top of the range model) ARM based PC that’s the size of a credit card.

A knew I had to have one to play with but what to do with it? Why not start by porting MySQL Cluster onto it? We always claim that Cluster runs on commodity hardware – surely this would be the ultimate test of that claim.

I chose the customised version of Debian – you have to copy it onto the SD memory card that acts as the storage for the Pi. Once up and running on the Pi, the first step was to increase the size of the main storage partition – it starts at about 2 Gbytes – using gparted. I then had to compile MySQL Cluster – ARM isn’t a supported platform and so there are no pre-built binaries. I needed to install a couple of packages before I could get very far:

Compilation initially got about 80% through before failing and so if you try this yourself then save yourself some time by applying the patch from this bug report before starting. The build scripts wouldn’t work but I was able to just run make…

As I knew that memory was tight I tried to come up with a config.ini file that cut down on how much memory would be needed (note that is the Raspberry Pi while is an 8GByte Linux x86-64 PC – doesn’t seem a very fair match!):

Running the management node worked pretty easily but then I had problems starting the data nodes – checking how much memory I had available gave me a hint as to why!

OK – so 157 Mbytes of memory available and no swap space, not ideal and so the next step was to use gparted again to create swap partitions on the SD card as well a massive 1Gbyte on my MySQL branded USB stick (need to persuade marketing to be a bit more generous with those). A quick edit of /etc/fstab and a restart and things were looking in better shape:

Next to start up the management node and 1 data node on the Pi as well as a second data node on the Linux server “ws2” (I want High Availability after all – OK so running the management node on the same host as a data node is a single point of failure)…

I could then confirm that everything was up and running:


Next step is to run a MySQL Server so that I can actually test the Cluster – if I tried running that on the Pi then it caused problems (157 Mbytes of RAM doesn’t stretch as far as it used to) – on ws2:

Check that it really has connected to the Cluster:

Finally, just need to check that I can read and write data…

OK – so is there any real application to this? Well, probably not other than providing a cheap development environment – imagine scaling out to 48 data nodes, that would cost $1,680 (+ the cost of some SD cards)! More practically might be management nodes – we know that they need very few resources. As a reminder – this is not a supported platform!

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17 thoughts on “MySQL Cluster running on Raspberry Pi

  1. Did you do any stress tests to see IO throughput ? I’ve done the same with a cassandra cluster, the IO looks like a bit of a problem.

    1. No – no stress testing, at this point. Would really need multiple Pis to do that properly.


  2. I had wanted multiple Pis to try a cluster.
    I suggested something like this (not with Pi obviously) maybe 8 years ago to Mikael Ronström.

  3. You can increase the RAM available by replacing the the boot.elf with one of the others in the same directory. By default 128MB will be assigned to the video chip set, by replacing the boot.elf you can knock this down to 32MB giving you ~224MB system memory.

  4. Thanks Andrew Morgan for this Infos.

    Got the v 7.3 compiled on PI successfully.
    Running on 512MB PI´s Using 3 PI´s

    That works and been enoth for some standard DEV Stages and smaler Prod Stages..

    2 issued minor seen here during Mysql cluster Build on PI( no cross compile ):

    – PI´s ARM Mysql cluster Build environment not ready for non-BMP characters
    -> patch missing

    – PI´s ARM Mysql cluster Build environment not ready NDB Atomic functions
    -> arm arch patch missing for ndb memcached

    IO :
    use an Powered USB HUB and you´ll have an better thruput at IO.
    I am using lvm2 mirrored usb sticks with XFS for NDB .
    Usb2 based is enoth for DEV stages and some smal Prod sites..

    My Itention why Mysql Cluster on PI :

    Since Ages ago Mysql Cluster I ran 2 x 2HE sized AMD systems for the same DEv Cluster consuming +600watt power 7×24.. and an lot of Noise …

    Now the same Dev Cluster on PI consume only 30watt 7×24 with NO more Noise any more.

    If my PIs go overload i´ll just add more sql / ndb nodes…

    Kind regards

    Horst Venzke, Remsnet LTD

  5. Hello,

    I keep getting compile errors at the storage/ndb/src/kernel/mv/mt.cpp step. (About 45% into the compile process). Errors are wmb, mb, rmb was not declared in this scope.
    Any ideas?

    1. Hi Andrew,

      Did some more digging, and this turns out to be the “memory barrier” assembly functions, wich are only defined for the x86 architecture. w and r stand for write and read respectively.
      I got around the problem by bascially commenting out these calls in the mt.cpp . Not sure how stable/reliable this will make the ndb, but at least it compiled and it is working.

      1. Hi Damian

        Could you share with us some information about stability of your solution to error: ‘rmb was not declared in this scope’

        I have the same error as you and i will do the same thing you did 😉

        1. Hi Sebastian,
          Forgot which version it was, but it was ndb. It was stable for basic playing around. I didn’t invest more time into it due to low RAM on the PI.
          However, I just picked up 10 PI 2s, so will try to do 8 node cluster (paired with another 8 nodes on the xen for redundancy)
          I currently use 2×4 set up with 4 old laptops (1GB ram each) and 4 VMs. PI 2s come with 1GB or ram so might get somewhere with that.

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