issue_comments: 1012599465

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https://github.com/pydata/xarray/pull/5734#issuecomment-1012599465 https://api.github.com/repos/pydata/xarray/issues/5734 1012599465 IC_kwDOAMm_X848Wwqp 14371165 2022-01-13T23:06:43Z 2022-01-13T23:10:12Z MEMBER

This is a strict improvement now, well done!

before after ratio [4c865d60] [9b13c974] - 18.7±0.3ms 11.0±0.1ms 0.59 groupby.GroupByDask.time_agg_small_num_groups('sum', 2) - 24.3±1ms 13.8±0.2ms 0.57 groupby.ResampleDask.time_agg_small_num_groups('mean', 2) - 22.0±0.2ms 12.0±0.3ms 0.54 groupby.ResampleDask.time_agg_small_num_groups('mean', 1) - 13.5±0.4ms 7.28±0.3ms 0.54 groupby.GroupByDask.time_agg_small_num_groups('sum', 1) - 33.7±0.4ms 14.2±0.3ms 0.42 groupby.ResampleDask.time_agg_small_num_groups('sum', 2) - 30.7±0.4ms 11.9±0.2ms 0.39 groupby.ResampleDask.time_agg_small_num_groups('sum', 1) - 104±1ms 8.21±0.08ms 0.08 groupby.Resample.time_agg_large_num_groups('sum', 1) - 119±1ms 8.84±0.2ms 0.07 groupby.Resample.time_agg_large_num_groups('sum', 2) - 115±2ms 8.45±0.2ms 0.07 groupby.Resample.time_agg_large_num_groups('mean', 1) - 134±1ms 9.60±0.2ms 0.07 groupby.Resample.time_agg_large_num_groups('mean', 2) - 257±3ms 10.2±0.3ms 0.04 groupby.GroupBy.time_agg_large_num_groups('mean', 2) - 260±5ms 9.99±0.2ms 0.04 groupby.GroupBy.time_agg_large_num_groups('sum', 2) - 190±6ms 6.47±0.2ms 0.03 groupby.GroupBy.time_agg_large_num_groups('mean', 1) - 193±2ms 6.31±0.2ms 0.03 groupby.GroupBy.time_agg_large_num_groups('sum', 1) - 368±5ms 10.9±0.2ms 0.03 groupby.GroupByDask.time_agg_large_num_groups('mean', 2) - 494±2ms 13.7±0.3ms 0.03 groupby.ResampleDask.time_agg_large_num_groups('mean', 2) - 451±8ms 12.3±0.3ms 0.03 groupby.ResampleDask.time_agg_large_num_groups('mean', 1) - 318±3ms 7.13±0.04ms 0.02 groupby.GroupByDask.time_agg_large_num_groups('mean', 1) - 531±6ms 10.6±0.2ms 0.02 groupby.GroupByDask.time_agg_large_num_groups('sum', 2) - 814±10ms 14.0±0.4ms 0.02 groupby.ResampleDask.time_agg_large_num_groups('sum', 2) - 760±8ms 12.0±0.3ms 0.02 groupby.ResampleDask.time_agg_large_num_groups('sum', 1) - 490±6ms 7.13±0.2ms 0.01 groupby.GroupByDask.time_agg_large_num_groups('sum', 1)

Earlier benchmarks:

``` before after ratio [5d30f96e] [0ad0dfde] - 16.7±0.3ms 10.3±0.5ms 0.62 groupby.GroupByDask.time_agg_small_num_groups('sum', 2) - 21.5±0.8ms 13.1±0.5ms 0.61 groupby.ResampleDask.time_agg_small_num_groups('mean', 1) - 24.5±1ms 14.4±0.8ms 0.59 groupby.ResampleDask.time_agg_small_num_groups('mean', 2) - 12.8±0.6ms 7.08±0.3ms 0.55 groupby.GroupByDask.time_agg_small_num_groups('sum', 1) - 28.9±0.9ms 13.2±0.4ms 0.46 groupby.ResampleDask.time_agg_small_num_groups('sum', 1) - 31.5±0.5ms 14.2±1ms 0.45 groupby.ResampleDask.time_agg_small_num_groups('sum', 2) - 110±4ms 10.6±0.4ms 0.10 groupby.Resample.time_agg_large_num_groups('sum', 2) - 96.2±5ms 8.80±0.4ms 0.09 groupby.Resample.time_agg_large_num_groups('mean', 1) - 127±3ms 10.9±0.6ms 0.09 groupby.Resample.time_agg_large_num_groups('mean', 2) - 95.9±2ms 7.44±0.4ms 0.08 groupby.Resample.time_agg_large_num_groups('sum', 1) - 211±6ms 9.99±0.4ms 0.05 groupby.GroupBy.time_agg_large_num_groups('mean', 2) - 219±8ms 10.4±1ms 0.05 groupby.GroupBy.time_agg_large_num_groups('sum', 2) - 154±3ms 6.86±0.4ms 0.04 groupby.GroupBy.time_agg_large_num_groups('mean', 1) - 163±3ms 6.83±0.2ms 0.04 groupby.GroupBy.time_agg_large_num_groups('sum', 1) - 330±3ms 10.6±0.6ms 0.03 groupby.GroupByDask.time_agg_large_num_groups('mean', 2) - 446±10ms 14.2±0.3ms 0.03 groupby.ResampleDask.time_agg_large_num_groups('mean', 2) - 413±9ms 12.1±0.5ms 0.03 groupby.ResampleDask.time_agg_large_num_groups('mean', 1) - 265±2ms 7.52±0.2ms 0.03 groupby.GroupByDask.time_agg_large_num_groups('mean', 1) - 469±10ms 10.3±0.5ms 0.02 groupby.GroupByDask.time_agg_large_num_groups('sum', 2) - 739±10ms 14.0±0.8ms 0.02 groupby.ResampleDask.time_agg_large_num_groups('sum', 2) - 678±10ms 12.0±1ms 0.02 groupby.ResampleDask.time_agg_large_num_groups('sum', 1) - 434±20ms 7.05±0.5ms 0.02 groupby.GroupByDask.time_agg_large_num_groups('sum', 1) before after ratio [5d30f96e] [0ad0dfde] + 3.89±0.1ms 6.62±0.4ms 1.70 groupby.GroupBy.time_agg_small_num_groups('sum', 1) ``` 
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