kkewwei commented on issue #16626:
URL: https://github.com/apache/lucene/issues/16626#issuecomment-5535560897

   I add msm with sort tasks: 
   
https://github.com/mikemccand/luceneutil/commit/03d3ac2bc8c53e0c3d5770fb07ca6f44d31d1132
   
   After 19 benchmark rounds, the final results are:
   ```
                               TaskQPS baseline      StdDevQPS 
my_modified_version      StdDev                Pct diff p-value
             MSM16M15HighLowDaySort      239.70      (9.3%)      181.68      
(4.5%)  -24.2% ( -34% -  -11%) 0.000
                MSM5M3MediumDaySort       15.25      (4.9%)       14.97      
(4.1%)   -1.9% ( -10% -    7%) 0.194
                MSM8M2MediumDaySort        7.59      (3.9%)        7.47      
(5.3%)   -1.5% ( -10% -    7%) 0.313
               MSM16M2MediumDaySort        1.85      (3.1%)        1.83      
(3.4%)   -0.7% (  -6% -    5%) 0.496
                 MSM16M15LowDaySort      233.17      (7.7%)      232.04      
(4.4%)   -0.5% ( -11% -   12%) 0.806
                  MSM5M2HighDaySort        1.70      (3.2%)        1.69      
(2.2%)   -0.1% (  -5% -    5%) 0.890
                           PKLookup      168.96      (8.4%)      168.76      
(9.0%)   -0.1% ( -16% -   18%) 0.966
                  MSM5M3HighDaySort        2.48      (4.3%)        2.50      
(4.5%)    0.6% (  -7% -    9%) 0.679
                 MSM16M2HighDaySort        0.71      (2.9%)        0.71      
(2.3%)    0.7% (  -4% -    6%) 0.398
                  MSM8M2HighDaySort        1.07      (3.4%)        1.09      
(2.7%)    1.2% (  -4% -    7%) 0.233
               MSM5M3HighLowDaySort       24.12      (5.9%)       24.49      
(4.1%)    1.6% (  -8% -   12%) 0.334
               MSM8M7HighLowDaySort      167.15      (4.4%)      174.85      
(4.3%)    4.6% (  -3% -   13%) 0.001
                   MSM8M7LowDaySort      339.61      (4.7%)      367.36      
(4.5%)    8.2% (  -1% -   18%) 0.000
                MSM5M2MediumDaySort       39.03      (5.6%)       42.39      
(4.8%)    8.6% (  -1% -   20%) 0.000
                  MSM5M4HighDaySort       13.34      (5.7%)       14.72      
(2.9%)   10.3% (   1% -   20%) 0.000
                   MSM5M4LowDaySort      430.93      (6.4%)      496.01      
(8.0%)   15.1% (   0% -   31%) 0.000
                   MSM5M3LowDaySort      358.04      (6.9%)      419.98      
(4.8%)   17.3% (   5% -   31%) 0.000
                   MSM3M2LowDaySort      509.79      (6.0%)      601.72      
(6.5%)   18.0% (   5% -   32%) 0.000
                MSM3M2MediumDaySort       62.26      (4.8%)       76.27      
(4.2%)   22.5% (  12% -   33%) 0.000
                  MSM3M2HighDaySort       52.29      (4.7%)       66.02      
(4.9%)   26.2% (  15% -   37%) 0.000
               MSM3M2HighLowDaySort       44.56      (5.9%)       65.51      
(7.6%)   47.0% (  31% -   64%) 0.000
                MSM5M4MediumDaySort        8.91      (6.1%)       13.78      
(3.2%)   54.7% (  42% -   68%) 0.000
                MSM8M7MediumDaySort        7.36      (7.5%)       11.88      
(4.7%)   61.5% (  45% -   79%) 0.000
                  MSM8M7HighDaySort        1.51      (5.9%)        2.45      
(5.6%)   62.6% (  48% -   78%) 0.000
              MSM16M15MediumDaySort       16.27      (9.1%)       26.47      
(6.6%)   62.6% (  42% -   86%) 0.000
               MSM5M4HighLowDaySort        9.38      (6.2%)       15.28      
(5.3%)   62.9% (  48% -   79%) 0.000
                MSM16M15HighDaySort        2.95     (11.1%)        5.03      
(6.3%)   70.6% (  47% -   99%) 0.000 
   ```
   
   Most cases show significant improvements, suggesting the optimization is 
worthwhile. The only exception is `MSM16M15HighLowDaySort`.
   
   Next, I plan to:
   
   1. Investigate how to optimize `WANDScorer` to support this feature.
   2. Identify the cause of the performance regression in 
`MSM16M15HighLowDaySort`.
   


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