ASV: add frame ops benchmarks for varying n_rows/n_columns ratios

[jorisvandenbossche]

Currently, we have a benchmark for frame/frame ops with a wide dataframe (originating from previous (long) PR / discussion about this, xref #32779)

To get a better idea of the trade-offs for future changes to the ops code (eg ArrayManager related), I think it is useful to have this benchmark for a varying rows/columns ratio (it is mostly this ratio that determines how much overhead we have when performing ops column-wise).

So I changed the benchmark to be parametrized over 4 different ratios, from a long to a wide dataframe, and with each case having the same number of total elements in the dataframe.

The shape in the original benchmark was (500, 2000), which is somewhere in between two new cases of (10_000, 1000) and (1000, 10_000), so that should preserve the original intent of the benchmark (the last case of (1000, 10_000) even has a lower row/column ratio, so should even be a "worse" case for the column-wise ops perspective).

cc @jbrockmendel

[jorisvandenbossche]

A run of those benchmarks:

$ asv dev -b FrameWithFrameWide
· Discovering benchmarks
· Running 2 total benchmarks (1 commits * 1 environments * 2 benchmarks)
[  0.00%] ·· Benchmarking existing-py_home_joris_miniconda3_envs_dev_bin_python
[ 25.00%] ··· arithmetic.FrameWithFrameWide.time_op_different_blocks          
[ 25.00%] ··· ============================== =============== =============== =============== ===============
              --                                                          shape                             
              ------------------------------ ---------------------------------------------------------------
                            op                (1000000, 10)   (100000, 100)   (10000, 1000)   (1000, 10000) 
              ============================== =============== =============== =============== ===============
                 <built-in function add>         19.1±0ms        14.9±0ms        14.1±0ms        14.3±0ms   
               <built-in function floordiv>      435±0ms         475±0ms         418±0ms         375±0ms    
                  <built-in function gt>         12.1±0ms        11.8±0ms        12.6±0ms        11.8±0ms   
              ============================== =============== =============== =============== ===============

[ 50.00%] ··· arithmetic.FrameWithFrameWide.time_op_same_blocks               
[ 50.00%] ··· ============================== =============== =============== =============== ===============
              --                                                          shape                             
              ------------------------------ ---------------------------------------------------------------
                            op                (1000000, 10)   (100000, 100)   (10000, 1000)   (1000, 10000) 
              ============================== =============== =============== =============== ===============
                 <built-in function add>         10.6±0ms        11.7±0ms        10.5±0ms        12.3±0ms   
               <built-in function floordiv>      233±0ms         229±0ms         258±0ms         230±0ms    
                  <built-in function gt>         5.64±0ms        6.29±0ms        5.51±0ms        7.50±0ms   
              ============================== =============== =============== =============== ===============

So the floordiv one is quite slow. I could maybe reduce the number of rows with a factor of 10 in that case.

[jreback]

So the floordiv one is quite slow. I could maybe reduce the number of rows with a factor of 10 in that case.
sure

[jbrockmendel]

"as" -> "than"

[jbrockmendel]

nitpick, otherwise LGTM