ebf01ec3c1
### What changes were proposed in this pull request? https://github.com/apache/spark/pull/32015 added a way to run benchmarks much more easily in the same GitHub Actions build. This PR updates the benchmark results by using the way. **NOTE** that looks like GitHub Actions use four types of CPU given my observations: - Intel(R) Xeon(R) Platinum 8171M CPU 2.60GHz - Intel(R) Xeon(R) CPU E5-2673 v4 2.30GHz - Intel(R) Xeon(R) CPU E5-2673 v3 2.40GHz - Intel(R) Xeon(R) Platinum 8272CL CPU 2.60GHz Given my quick research, seems like they perform roughly similarly: ![Screen Shot 2021-04-03 at 9 31 23 PM](https://user-images.githubusercontent.com/6477701/113478478-f4b57b80-94c3-11eb-9047-f81ca8c59672.png) I couldn't find enough information about Intel(R) Xeon(R) Platinum 8272CL CPU 2.60GHz but the performance seems roughly similar given the numbers. So shouldn't be a big deal especially given that this way is much easier, encourages contributors to run more and guarantee the same number of cores and same memory with the same softwares. ### Why are the changes needed? To have a base line of the benchmarks accordingly. ### Does this PR introduce _any_ user-facing change? No, dev-only. ### How was this patch tested? It was generated from: - [Run benchmarks: * (JDK 11)](https://github.com/HyukjinKwon/spark/actions/runs/713575465) - [Run benchmarks: * (JDK 8)](https://github.com/HyukjinKwon/spark/actions/runs/713154337) Closes #32044 from HyukjinKwon/SPARK-34950. Authored-by: HyukjinKwon <gurwls223@apache.org> Signed-off-by: Max Gekk <max.gekk@gmail.com>
46 lines
3.5 KiB
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46 lines
3.5 KiB
Plaintext
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Hive UDAF vs Spark AF
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OpenJDK 64-Bit Server VM 11.0.10+9-LTS on Linux 5.4.0-1043-azure
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Intel(R) Xeon(R) Platinum 8171M CPU @ 2.60GHz
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hive udaf vs spark af: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
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hive udaf w/o group by 7504 7577 56 0.0 114496.1 1.0X
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spark af w/o group by 37 44 7 1.8 560.2 204.4X
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hive udaf w/ group by 5867 6075 194 0.0 89527.2 1.3X
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spark af w/ group by w/o fallback 40 46 6 1.6 608.7 188.1X
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spark af w/ group by w/ fallback 50 55 5 1.3 764.4 149.8X
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ObjectHashAggregateExec vs SortAggregateExec - typed_count
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OpenJDK 64-Bit Server VM 11.0.10+9-LTS on Linux 5.4.0-1043-azure
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Intel(R) Xeon(R) Platinum 8171M CPU @ 2.60GHz
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object agg v.s. sort agg: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
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sort agg w/ group by 41856 42278 597 2.5 399.2 1.0X
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object agg w/ group by w/o fallback 12479 12754 320 8.4 119.0 3.4X
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object agg w/ group by w/ fallback 25981 26058 109 4.0 247.8 1.6X
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sort agg w/o group by 7351 7473 116 14.3 70.1 5.7X
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object agg w/o group by w/o fallback 7095 7406 490 14.8 67.7 5.9X
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ObjectHashAggregateExec vs SortAggregateExec - percentile_approx
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================================================================================================
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OpenJDK 64-Bit Server VM 11.0.10+9-LTS on Linux 5.4.0-1043-azure
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Intel(R) Xeon(R) Platinum 8171M CPU @ 2.60GHz
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object agg v.s. sort agg: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
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sort agg w/ group by 952 1047 92 2.2 453.9 1.0X
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object agg w/ group by w/o fallback 829 957 90 2.5 395.2 1.1X
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object agg w/ group by w/ fallback 972 1107 128 2.2 463.5 1.0X
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sort agg w/o group by 732 858 98 2.9 349.1 1.3X
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object agg w/o group by w/o fallback 770 897 92 2.7 367.4 1.2X
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