Performance drop between 2.0.9.1 and 2.0.9.15
Posted: Tue Nov 14, 2023 3:10 pm
Hi all,
We are in the process of upgrading from 2.0.9.1 (tm1s.exe 11.8.00000.33) to 2.0.9.15 (tm1s.exe 11.8.01700.1) but are encountering performance issues with large datasets on the new version. All objects were copied from old to new so the cubes, dimensions, TI processes, etc. are identical on both versions.
The new server is higher spec than the old server.
Old
CPU: Intel Xeon E5-2660 v4 x 2
RAM: 128Gb
New
CPU: Intel Xeon Gold 6134 x 2
RAM: 150Gb
Small/medium data sets are OK and run more quickly - as expected with the improved server specs.
But large datasets - via ODBO (MDX queries) or large CSVs - take significantly longer.
One ODBO process takes c.6mins on the old version but c.7.5hrs on the new one! The source is an external cube hosted by our EPOS provider and accessed via a web address. The MDX query, like the rest of the process, is identical in both versions.
Our largest CSV (c.16m rows) is located on the actual servers (2 identical copies at the moment, one on each server) and takes c.1hr on the old version but I killed it after c11.5hrs because it hadn't finished on the new one.
I have tried searching for this issue on the internet and have checked the cube properties with regards to VMM per IBM help pages but, as with all the objects, the cube properties are also identical for both versions. VMM is blank for all cubes. Nothing else jumps out on a Google search.
Both TM1 servers are virtualised and exist in the same server room, albeit on different physical servers, with the same internet connectivity utilised by the ODBO processes targetting the external cube.
Has anyone else experienced an unexpected drop in performance between these (or any) versions with large datasets or has any ideas of what might be causing it?
I appreciate that ODBO has been deprecated between those versions (surely the performance can't have tanked THAT badly), but we aren't in a position to be able to change the source in the short term.
But that doesn't explain the drop in performance loading from large CSVs located on the same server.
Any help or advice would be greatly appreciated.
Martin
We are in the process of upgrading from 2.0.9.1 (tm1s.exe 11.8.00000.33) to 2.0.9.15 (tm1s.exe 11.8.01700.1) but are encountering performance issues with large datasets on the new version. All objects were copied from old to new so the cubes, dimensions, TI processes, etc. are identical on both versions.
The new server is higher spec than the old server.
Old
CPU: Intel Xeon E5-2660 v4 x 2
RAM: 128Gb
New
CPU: Intel Xeon Gold 6134 x 2
RAM: 150Gb
Small/medium data sets are OK and run more quickly - as expected with the improved server specs.
But large datasets - via ODBO (MDX queries) or large CSVs - take significantly longer.
One ODBO process takes c.6mins on the old version but c.7.5hrs on the new one! The source is an external cube hosted by our EPOS provider and accessed via a web address. The MDX query, like the rest of the process, is identical in both versions.
Our largest CSV (c.16m rows) is located on the actual servers (2 identical copies at the moment, one on each server) and takes c.1hr on the old version but I killed it after c11.5hrs because it hadn't finished on the new one.
I have tried searching for this issue on the internet and have checked the cube properties with regards to VMM per IBM help pages but, as with all the objects, the cube properties are also identical for both versions. VMM is blank for all cubes. Nothing else jumps out on a Google search.
Both TM1 servers are virtualised and exist in the same server room, albeit on different physical servers, with the same internet connectivity utilised by the ODBO processes targetting the external cube.
Has anyone else experienced an unexpected drop in performance between these (or any) versions with large datasets or has any ideas of what might be causing it?
I appreciate that ODBO has been deprecated between those versions (surely the performance can't have tanked THAT badly), but we aren't in a position to be able to change the source in the short term.
But that doesn't explain the drop in performance loading from large CSVs located on the same server.
Any help or advice would be greatly appreciated.
Martin