Been playing lately with understanding some performance aspects of PA (obviously comparing v11 vs v12, but this post won’t be about this).

Ideally you should be always be comparing your specific TM1 model on different software versions, hardware, etc, but sometimes it’s worth having a very simple model that doesn’t contain any sensitive data, but is ’larger’ than the sample models.

So that’s exactly what tm1bench is: a very simple model that can have a lot of data.

It’s a very simple model with just 3 cubes:

• Sales by Customer, Product, Month, Version with some rule based calculations
• Price by Product, Month, Version
• Discount by Customer, Month, Version

The number of elements in dimensions and amount of data is parametrised in tm1bench Setup process, so you can set up a sample model with 10m, 50m, 100m or more cells in Sales cube to run your tests against.

There’s a couple of tests included:

• loading data single threaded - tm1bench Test sales data load
• loading data in multiple threads - tm1bench Test sales data load parallel
• reading data from Sales cube to check how fast rule calculations work - tm1bench Test sales data read