The production cluster has several servers which you can use to access the various private data sources and do general statistical computation. There are two types: the stat servers, designed for command-line use, and the SWAP servers, designed for Jupyter notebook use. Together, these are called the analytics clients, since they act as clients accessing data from various other databases.
|Host||CPU cores||RAM||Disk Space||GPU?||Data access|
|stat1004||16||32G||7.2TB||no||Hadoop, MariadBB, XML Dumps|
|stat1005||40||64G||7.2TB||yes||Hadoop, MariaDB, XML Dumps|
|stat1006||40||64G||7.2TB||no||MariaDB, XML Dumps|
|stat1007||32||64G||7.2TB||no||Hadoop, MariaDB, XML Dumps|
|notebook1003||32||64G||120GB||no||Hadoop, MariaDB, XML Dumps|
|notebook1004||32||64G||120GB||no||Hadoop, MariaDB, XML Dumps|
You may need to access the internet from the analytics clients (for example, to download a Python script using
pip). By default, this will fail because the machines are tightly firewalled. You'll have to use the HTTP proxy.
Local data storage
First, note that the Analytics clients store data using redundant RAID configurations, but are not otherwise backed up. Your home directory on HDFS (
/user/your-username) is a safer place for important data.
Please ensure that there is enough space on disk before storing big datasets/files. On the Analytics clients, the home directories are stored under the /srv partition, so the command df -h should be used regularly to check space used. There are client nodes that are more crowded than other ones, so please try to use the least used client first (for example, checking with the aforementioned command what stat hosts has more free space).
Checking for available disk space
List of available nodes and their disk space available:
- stat1004 - 7.2TB of total space
- stat1005 - 7.2TB of total space
- stat1006 - 7.2TB of total space
- stat1007 - 7.2TB of total space
- notebook100[3,4] - 120G of total space, not intended to store any data but just as Hadoop client (if needed, store data on HDFS).
On all the Analytics clients the home directories are stored under the /srv partition, so the command df -h should be used regularly to check space used. There are client nodes that are more crowded than other ones, so please try to use the least used client first (for example, checking with the aforementioned command what stat hosts has more free space).
Here an example to clarify the last point, using the stat1007 host:
elukey@stat1007:~$ df -h Filesystem Size Used Avail Use% Mounted on udev 32G 0 32G 0% /dev tmpfs 6.3G 666M 5.7G 11% /run /dev/md0 92G 16G 71G 19% / tmpfs 32G 1.2M 32G 1% /dev/shm tmpfs 5.0M 0 5.0M 0% /run/lock tmpfs 32G 0 32G 0% /sys/fs/cgroup /dev/mapper/stat1007--vg-data 7.2T 6.4T 404G 95% /srv <<=====================================<< tmpfs 6.3G 0 6.3G 0% /run/user/3088 tmpfs 6.3G 0 6.3G 0% /run/user/13926 tmpfs 6.3G 0 6.3G 0% /run/user/20171 fuse_dfs 2.3P 1.8P 511T 78% /mnt/hdfs tmpfs 6.3G 0 6.3G 0% /run/user/18005 tmpfs 6.3G 32K 6.3G 1% /run/user/17677 labstore1006.wikimedia.org:/srv/dumps/xmldatadumps/public 98T 59T 35T 64% /mnt/nfs/dumps-labstore1006.wikimedia.org labstore1007.wikimedia.org:/ 97T 65T 28T 70% /mnt/nfs/dumps-labstore1007.wikimedia.org tmpfs 6.3G 0 6.3G 0% /run/user/22235 tmpfs 6.3G 0 6.3G 0% /run/user/22071 tmpfs 6.3G 0 6.3G 0% /run/user/10668
In this case, the /srv partition is almost full, so it is better to look for another stat1xxx host.
Checking the space used by your files
It is sufficient to ssh to the host that you want to check and execute the following:
# Ensure that I am in my home directory, usually /home/your-username # if not, please do cd /home/your-username elukey@stat1007:~$ pwd /home/elukey elukey@stat1007:~$ du -hs 369M .
For a detailed view:
# Ensure that I am in my home directory, usually /home/your-username # if not, please do cd /home/your-username elukey@stat1007:~$ pwd /home/elukey elukey@stat1007:~$ du -hs * | sort -h [..] 164K dump.out 648K eventlogging_cleaner.log 7.5M refinery 21M python_env 49M webrequest.stats.json 245M spark2-2.3.1-bin-hadoop2.6
It is easy to have a quick view of how much data we are storing, and delete files that are not needed.
If you wish to publish a dataset or report from one of the analytics clients, you can place it in the
/srv/published/ directory, which will make it available on the web in the equivalent place under analytics.wikimedia.org/published/. You can find more information on Analytics/Web publication.
On stat1005 we have deployed an AMD GPU for T148843. The long term plan is to make it available for all the users logging in, but for the moment its access is restricted to the POSIX group
gpu-testers to better test it (and avoid usage contention etc..). Please reach out to the Analytics team if you wish to get added to the group to test the GPU for your use case.
On every stat100x node except stat1007 (still in progress) it is available a Jupyterhub server, see wiki/SWAP. Please note that on stat1005 it is running Jupyterhub 1.1.0 (last upstream), please report any bug if you find one. The goal is to upgrade all the other nodes as soon as they are ready for an OS upgrade.