It is considered to check for the following things:
1) Check if your TS disk subsystem would be fast enough.
It is wise to have a RAID-10 of SAS-6 / SAS-12 HDDs,
or even use server-grade SSDs if you can afford it.
Typically, you may have IOPS at above 1000.
2) Consider having dedicated node(s) in your TS cluster
for Data Engine process(es) together with API Server process --
and may be Data Server / Cache Server / Backgrounder ones as well.
The main reason for this is to exclude a concurrency for node cores
between VizQL-heavy transactions and Data Engine-heavy ones.
3) One last thought, and it is very hypothetical:
Since each copy of an extract is uploaded and published to TS
via Alteryx-initiated REST API call (series of calls, actually,
if you uploading a file larger than 64MB) one could test a possibility
to publish the "same" extract to TS (overwriting the one already there)
in a somewhat "overlapping" mode -- starting the next upload/publish task
in another Alteryx flow before the current one is finished.
This would create a "que" of upload/publish REST API transactions,
and if Tableau Server has enough muscles to sustain such a workload,
those transcations could be initiated with as short time-lapse as needed (say 10 minutes).
But of course, this should be carefully tested
on a non-production Tableau Server instance
before even thinking about "go-to-production".
Hope this could help a bit.
How do I check disk configuration? I believe we have RAID-10, but I do not know if it's SAS-6 or SAS-12 or something else nor do I even know what this means, can you help?
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These are questions to ask your HW systems engineer.
Please ask about your physical server(s) vendor model,
general HW config/ RAID config (if any) / HDD model(s).
SAS-6 or SAS-12 meant Serial Attached SCSI interface (6Gbit/s or 12Gbit/s).
If you have RDP access to your TS node(s), you may want
to look at Windows Storage Manager and Device Manager
for info about storage configuration & disk drives / volumes.
It doesn't tell much if you're running TS on a virtual machine, though.
Thank you for the suggestions. I have passed them on to my server admin to see if he can implement some or all of the changes to improve performance.
I don't see anything to optimize further here.
PS The question that thrills me here in this topic
is about which part of the whole publish transaction
is a bottleneck -- whether it an upload or a publish itself.
When I see this behavior it's almost always related to poor network
performance between Tableau Desktop & Server.
Are Desktop & Server on the same local network in the same datacenter? Or
are you using Desktop on your local machine and publishing to a remote
The best test to isolate network issues is to (temporally) install Tableau
Desktop on the same machine as the server and retest. If that results in a
huge performance variance then it's probably the upload speed of your
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