alamb commented on PR #7917: URL: https://github.com/apache/arrow-rs/pull/7917#issuecomment-3133109139
🤖: Benchmark completed
<details><summary>Details</summary>
<p>
```
group
issue-6057
main
-----
----------
----
append_rows 10 large_list(0) of u64(0)
1.00 668.7±7.41ns ?
?/sec 1.01 677.1±1.29ns ? ?/sec
append_rows 10 list(0) of u64(0)
1.00 701.2±1.19ns ?
?/sec 1.01 706.4±2.12ns ? ?/sec
append_rows 4096 4096 string_dictionary(20, 0.5), string_dictionary(30, 0),
string_dictionary(100, 0), i64(0) 1.01 385.6±1.72µs ?
?/sec 1.00 383.6±2.18µs ? ?/sec
append_rows 4096 bool(0, 0.5)
1.00 8.6±0.01µs ?
?/sec 1.00 8.6±0.02µs ? ?/sec
append_rows 4096 bool(0.3, 0.5)
1.00 16.1±0.10µs ?
?/sec 1.00 16.1±0.09µs ? ?/sec
append_rows 4096 i64(0)
1.01 7.8±0.09µs ?
?/sec 1.00 7.7±0.14µs ? ?/sec
append_rows 4096 i64(0.3)
1.01 18.1±0.11µs ?
?/sec 1.00 18.0±0.06µs ? ?/sec
append_rows 4096 large_list(0) of u64(0)
1.00 165.5±0.34µs ?
?/sec 1.01 166.6±0.96µs ? ?/sec
append_rows 4096 large_list(0) sliced to 10 of u64(0)
1.00 955.7±5.22ns ?
?/sec 1.04 993.7±2.20ns ? ?/sec
append_rows 4096 list(0) of u64(0)
1.00 167.9±1.35µs ?
?/sec 1.00 167.3±0.49µs ? ?/sec
append_rows 4096 list(0) sliced to 10 of u64(0)
1.00 1064.7±2.36ns ?
?/sec 1.01 1071.2±2.15ns ? ?/sec
append_rows 4096 string view(1..100, 0)
1.00 117.5±0.37µs ?
?/sec 1.00 117.5±0.22µs ? ?/sec
append_rows 4096 string view(1..100, 0.5)
1.00 102.4±0.23µs ?
?/sec 1.02 104.3±0.40µs ? ?/sec
append_rows 4096 string view(10, 0)
1.00 50.2±0.09µs ?
?/sec 1.00 50.4±0.20µs ? ?/sec
append_rows 4096 string view(100, 0)
1.00 77.9±0.23µs ?
?/sec 1.00 78.2±0.34µs ? ?/sec
append_rows 4096 string view(100, 0.5)
1.00 81.4±0.21µs ?
?/sec 1.01 82.0±0.25µs ? ?/sec
append_rows 4096 string view(30, 0)
1.00 53.7±0.22µs ?
?/sec 1.00 53.5±0.16µs ? ?/sec
append_rows 4096 string(10, 0)
1.00 46.7±0.33µs ?
?/sec 1.00 46.5±0.24µs ? ?/sec
append_rows 4096 string(100, 0)
1.00 77.8±0.16µs ?
?/sec 1.00 77.9±0.35µs ? ?/sec
append_rows 4096 string(100, 0.5)
1.00 87.1±0.39µs ?
?/sec 1.00 87.1±0.24µs ? ?/sec
append_rows 4096 string(20, 0.5), string(30, 0), string(100, 0), i64(0)
1.00 243.5±1.00µs ?
?/sec 1.00 244.1±1.16µs ? ?/sec
append_rows 4096 string(30, 0)
1.00 49.7±0.09µs ?
?/sec 1.00 49.6±0.08µs ? ?/sec
append_rows 4096 string_dictionary(10, 0)
1.00 76.1±0.12µs ?
?/sec 1.00 75.8±0.18µs ? ?/sec
append_rows 4096 string_dictionary(100, 0)
1.01 153.7±1.21µs ?
?/sec 1.00 152.3±0.57µs ? ?/sec
append_rows 4096 string_dictionary(100, 0.5)
1.00 119.2±0.38µs ?
?/sec 1.00 119.7±0.26µs ? ?/sec
append_rows 4096 string_dictionary(30, 0)
1.00 80.4±0.38µs ?
?/sec 1.00 80.3±0.17µs ? ?/sec
append_rows 4096 string_dictionary_low_cardinality(10, 0)
1.00 29.2±0.07µs ?
?/sec 1.01 29.5±0.07µs ? ?/sec
append_rows 4096 string_dictionary_low_cardinality(100, 0)
1.00 47.3±0.10µs ?
?/sec 1.01 47.9±0.11µs ? ?/sec
append_rows 4096 string_dictionary_low_cardinality(30, 0)
1.00 29.7±0.05µs ?
?/sec 1.00 29.6±0.17µs ? ?/sec
append_rows 4096 u64(0)
1.00 7.6±0.11µs ?
?/sec 1.00 7.6±0.10µs ? ?/sec
append_rows 4096 u64(0.3)
1.00 14.8±0.10µs ?
?/sec 1.00 14.9±0.10µs ? ?/sec
convert_columns 10 large_list(0) of u64(0)
1.00 918.1±5.61ns ?
?/sec 1.04 954.4±8.20ns ? ?/sec
convert_columns 10 list(0) of u64(0)
1.00 966.0±2.75ns ?
?/sec 1.02 987.4±5.92ns ? ?/sec
convert_columns 4096 4096 string_dictionary(20, 0.5), string_dictionary(30,
0), string_dictionary(100, 0), i64(0) 1.00 385.6±1.95µs ?
?/sec 1.01 388.5±2.20µs ? ?/sec
convert_columns 4096 bool(0, 0.5)
1.00 8.8±0.02µs ?
?/sec 1.01 8.9±0.01µs ? ?/sec
convert_columns 4096 bool(0.3, 0.5)
1.00 16.3±0.06µs ?
?/sec 1.01 16.4±0.07µs ? ?/sec
convert_columns 4096 i64(0)
1.01 8.1±0.13µs ?
?/sec 1.00 8.0±0.12µs ? ?/sec
convert_columns 4096 i64(0.3)
1.00 18.3±0.12µs ?
?/sec 1.00 18.3±0.12µs ? ?/sec
convert_columns 4096 large_list(0) of u64(0)
1.00 166.6±1.68µs ?
?/sec 1.00 166.9±0.50µs ? ?/sec
convert_columns 4096 large_list(0) sliced to 10 of u64(0)
1.00 1227.8±5.54ns ?
?/sec 1.03 1262.3±5.91ns ? ?/sec
convert_columns 4096 list(0) of u64(0)
1.00 168.7±0.94µs ?
?/sec 1.00 168.1±0.43µs ? ?/sec
convert_columns 4096 list(0) sliced to 10 of u64(0)
1.00 1347.1±2.44ns ?
?/sec 1.02 1369.1±5.07ns ? ?/sec
convert_columns 4096 string view(1..100, 0)
1.00 118.1±0.28µs ?
?/sec 1.00 117.9±0.34µs ? ?/sec
convert_columns 4096 string view(1..100, 0.5)
1.00 103.2±0.42µs ?
?/sec 1.02 105.4±0.81µs ? ?/sec
convert_columns 4096 string view(10, 0)
1.00 50.4±0.19µs ?
?/sec 1.00 50.6±0.09µs ? ?/sec
convert_columns 4096 string view(100, 0)
1.00 77.6±0.26µs ?
?/sec 1.00 77.7±0.37µs ? ?/sec
convert_columns 4096 string view(100, 0.5)
1.00 82.3±0.32µs ?
?/sec 1.00 82.4±0.36µs ? ?/sec
convert_columns 4096 string view(30, 0)
1.00 53.7±0.15µs ?
?/sec 1.00 53.7±0.14µs ? ?/sec
convert_columns 4096 string(10, 0)
1.00 46.6±0.10µs ?
?/sec 1.00 46.6±0.09µs ? ?/sec
convert_columns 4096 string(100, 0)
1.00 77.3±0.24µs ?
?/sec 1.00 77.3±0.26µs ? ?/sec
convert_columns 4096 string(100, 0.5)
1.00 87.1±0.24µs ?
?/sec 1.00 87.0±0.14µs ? ?/sec
convert_columns 4096 string(20, 0.5), string(30, 0), string(100, 0), i64(0)
1.00 244.5±0.83µs ?
?/sec 1.01 248.1±1.09µs ? ?/sec
convert_columns 4096 string(30, 0)
1.00 50.0±0.08µs ?
?/sec 1.00 49.9±0.15µs ? ?/sec
convert_columns 4096 string_dictionary(10, 0)
1.01 77.9±1.79µs ?
?/sec 1.00 76.8±0.16µs ? ?/sec
convert_columns 4096 string_dictionary(100, 0)
1.01 154.8±1.47µs ?
?/sec 1.00 152.8±1.08µs ? ?/sec
convert_columns 4096 string_dictionary(100, 0.5)
1.01 120.6±0.51µs ?
?/sec 1.00 119.6±0.48µs ? ?/sec
convert_columns 4096 string_dictionary(30, 0)
1.00 81.0±0.21µs ?
?/sec 1.01 81.7±0.20µs ? ?/sec
convert_columns 4096 string_dictionary_low_cardinality(10, 0)
1.00 30.2±0.08µs ?
?/sec 1.01 30.4±0.04µs ? ?/sec
convert_columns 4096 string_dictionary_low_cardinality(100, 0)
1.00 49.1±0.19µs ?
?/sec 1.00 49.1±0.12µs ? ?/sec
convert_columns 4096 string_dictionary_low_cardinality(30, 0)
1.00 30.4±0.12µs ?
?/sec 1.00 30.5±0.08µs ? ?/sec
convert_columns 4096 u64(0)
1.01 7.9±0.12µs ?
?/sec 1.00 7.8±0.11µs ? ?/sec
convert_columns 4096 u64(0.3)
1.00 15.0±0.09µs ?
?/sec 1.00 15.0±0.07µs ? ?/sec
convert_columns_prepared 10 large_list(0) of u64(0)
1.00 709.0±4.02ns ?
?/sec 1.05 744.1±7.35ns ? ?/sec
convert_columns_prepared 10 list(0) of u64(0)
1.00 754.7±1.77ns ?
?/sec 1.01 762.4±2.47ns ? ?/sec
convert_columns_prepared 4096 4096 string_dictionary(20, 0.5),
string_dictionary(30, 0), string_dictionary(100, 0), i64(0) 1.00
385.4±2.15µs ? ?/sec 1.00 385.8±1.87µs ? ?/sec
convert_columns_prepared 4096 bool(0, 0.5)
1.00 8.8±0.01µs ?
?/sec 1.00 8.8±0.04µs ? ?/sec
convert_columns_prepared 4096 bool(0.3, 0.5)
1.01 16.3±0.09µs ?
?/sec 1.00 16.2±0.08µs ? ?/sec
convert_columns_prepared 4096 i64(0)
1.00 7.9±0.11µs ?
?/sec 1.01 8.0±0.01µs ? ?/sec
convert_columns_prepared 4096 i64(0.3)
1.01 18.2±0.10µs ?
?/sec 1.00 18.1±0.09µs ? ?/sec
convert_columns_prepared 4096 large_list(0) of u64(0)
1.00 166.2±1.50µs ?
?/sec 1.00 166.6±0.49µs ? ?/sec
convert_columns_prepared 4096 large_list(0) sliced to 10 of u64(0)
1.00 1027.9±4.14ns ?
?/sec 1.04 1067.5±2.50ns ? ?/sec
convert_columns_prepared 4096 list(0) of u64(0)
1.01 168.5±1.52µs ?
?/sec 1.00 167.4±0.37µs ? ?/sec
convert_columns_prepared 4096 list(0) sliced to 10 of u64(0)
1.00 1139.6±3.10ns ?
?/sec 1.02 1161.2±6.99ns ? ?/sec
convert_columns_prepared 4096 string view(1..100, 0)
1.00 117.7±0.30µs ?
?/sec 1.00 117.7±0.28µs ? ?/sec
convert_columns_prepared 4096 string view(1..100, 0.5)
1.00 103.4±0.38µs ?
?/sec 1.02 105.1±0.38µs ? ?/sec
convert_columns_prepared 4096 string view(10, 0)
1.00 50.5±0.14µs ?
?/sec 1.00 50.4±0.07µs ? ?/sec
convert_columns_prepared 4096 string view(100, 0)
1.00 77.1±0.31µs ?
?/sec 1.02 78.6±0.25µs ? ?/sec
convert_columns_prepared 4096 string view(100, 0.5)
1.00 81.9±0.29µs ?
?/sec 1.00 82.2±0.27µs ? ?/sec
convert_columns_prepared 4096 string view(30, 0)
1.00 53.7±0.17µs ?
?/sec 1.00 53.6±0.16µs ? ?/sec
convert_columns_prepared 4096 string(10, 0)
1.00 46.5±0.23µs ?
?/sec 1.00 46.7±0.15µs ? ?/sec
convert_columns_prepared 4096 string(100, 0)
1.00 77.9±0.27µs ?
?/sec 1.00 78.0±0.34µs ? ?/sec
convert_columns_prepared 4096 string(100, 0.5)
1.00 87.2±0.49µs ?
?/sec 1.00 87.4±0.15µs ? ?/sec
convert_columns_prepared 4096 string(20, 0.5), string(30, 0), string(100,
0), i64(0) 1.00 245.9±1.29µs
? ?/sec 1.00 245.8±0.87µs ? ?/sec
convert_columns_prepared 4096 string(30, 0)
1.00 49.8±0.09µs ?
?/sec 1.00 49.8±0.12µs ? ?/sec
convert_columns_prepared 4096 string_dictionary(10, 0)
1.00 76.3±0.17µs ?
?/sec 1.00 76.5±0.20µs ? ?/sec
convert_columns_prepared 4096 string_dictionary(100, 0)
1.00 153.9±0.77µs ?
?/sec 1.00 153.4±1.27µs ? ?/sec
convert_columns_prepared 4096 string_dictionary(100, 0.5)
1.00 119.8±0.68µs ?
?/sec 1.00 119.7±0.49µs ? ?/sec
convert_columns_prepared 4096 string_dictionary(30, 0)
1.00 80.4±0.32µs ?
?/sec 1.00 80.7±0.32µs ? ?/sec
convert_columns_prepared 4096 string_dictionary_low_cardinality(10, 0)
1.00 29.4±0.10µs ?
?/sec 1.01 29.7±0.05µs ? ?/sec
convert_columns_prepared 4096 string_dictionary_low_cardinality(100, 0)
1.00 47.5±0.13µs ?
?/sec 1.01 47.9±0.09µs ? ?/sec
convert_columns_prepared 4096 string_dictionary_low_cardinality(30, 0)
1.00 29.8±0.07µs ?
?/sec 1.01 30.1±0.07µs ? ?/sec
convert_columns_prepared 4096 u64(0)
1.00 7.7±0.12µs ?
?/sec 1.00 7.8±0.12µs ? ?/sec
convert_columns_prepared 4096 u64(0.3)
1.00 14.9±0.09µs ?
?/sec 1.00 14.9±0.07µs ? ?/sec
convert_rows 10 large_list(0) of u64(0)
1.00 1580.2±5.72ns ?
?/sec 1.05 1657.8±9.70ns ? ?/sec
convert_rows 10 list(0) of u64(0)
1.00 1769.6±4.63ns ?
?/sec 1.00 1769.1±3.46ns ? ?/sec
convert_rows 4096 4096 string_dictionary(20, 0.5), string_dictionary(30, 0),
string_dictionary(100, 0), i64(0) 1.00 301.0±1.37µs ?
?/sec 1.00 300.0±1.19µs ? ?/sec
convert_rows 4096 bool(0, 0.5)
1.00 16.0±0.07µs ?
?/sec 1.00 16.0±0.03µs ? ?/sec
convert_rows 4096 bool(0.3, 0.5)
1.00 16.0±0.02µs ?
?/sec 1.00 16.0±0.04µs ? ?/sec
convert_rows 4096 i64(0)
1.00 32.9±0.12µs ?
?/sec 1.00 33.0±0.08µs ? ?/sec
convert_rows 4096 i64(0.3)
1.00 33.0±0.10µs ?
?/sec 1.00 33.0±0.07µs ? ?/sec
convert_rows 4096 large_list(0) of u64(0)
1.00 260.2±2.14µs ?
?/sec 1.00 260.2±0.97µs ? ?/sec
convert_rows 4096 large_list(0) sliced to 10 of u64(0)
1.00 2.0±0.00µs ?
?/sec 1.00 2.0±0.01µs ? ?/sec
convert_rows 4096 list(0) of u64(0)
1.00 264.5±2.58µs ?
?/sec 1.00 265.6±0.60µs ? ?/sec
convert_rows 4096 list(0) sliced to 10 of u64(0)
1.00 2.1±0.01µs ?
?/sec 1.06 2.2±0.01µs ? ?/sec
convert_rows 4096 string view(1..100, 0)
1.00 169.0±0.27µs ?
?/sec 1.02 171.8±0.42µs ? ?/sec
convert_rows 4096 string view(1..100, 0.5)
1.00 132.9±0.30µs ?
?/sec 1.02 136.1±0.29µs ? ?/sec
convert_rows 4096 string view(10, 0)
1.00 72.6±0.15µs ?
?/sec 1.01 73.0±0.12µs ? ?/sec
convert_rows 4096 string view(100, 0)
1.00 122.3±0.74µs ?
?/sec 1.00 122.2±0.50µs ? ?/sec
convert_rows 4096 string view(100, 0.5)
1.00 110.7±0.31µs ?
?/sec 1.01 111.8±0.27µs ? ?/sec
convert_rows 4096 string view(30, 0)
1.00 79.4±1.49µs ?
?/sec 1.03 81.9±0.15µs ? ?/sec
convert_rows 4096 string(10, 0)
1.00 61.0±0.14µs ?
?/sec 1.00 60.9±0.13µs ? ?/sec
convert_rows 4096 string(100, 0)
1.00 107.8±0.55µs ?
?/sec 1.00 108.1±0.40µs ? ?/sec
convert_rows 4096 string(100, 0.5)
1.00 102.8±0.18µs ?
?/sec 1.01 103.4±0.31µs ? ?/sec
convert_rows 4096 string(20, 0.5), string(30, 0), string(100, 0), i64(0)
1.00 295.3±3.46µs ?
?/sec 1.02 299.9±2.00µs ? ?/sec
convert_rows 4096 string(30, 0)
1.00 73.3±0.21µs ?
?/sec 1.01 73.8±0.26µs ? ?/sec
convert_rows 4096 string_dictionary(10, 0)
1.00 61.2±0.16µs ?
?/sec 1.00 61.1±0.12µs ? ?/sec
convert_rows 4096 string_dictionary(100, 0)
1.00 108.4±0.37µs ?
?/sec 1.00 108.8±0.62µs ? ?/sec
convert_rows 4096 string_dictionary(100, 0.5)
1.00 103.2±0.33µs ?
?/sec 1.00 103.4±0.25µs ? ?/sec
convert_rows 4096 string_dictionary(30, 0)
1.00 73.9±0.25µs ?
?/sec 1.00 74.2±0.36µs ? ?/sec
convert_rows 4096 string_dictionary_low_cardinality(10, 0)
1.00 61.1±0.12µs ?
?/sec 1.00 61.2±0.09µs ? ?/sec
convert_rows 4096 string_dictionary_low_cardinality(100, 0)
1.00 107.3±0.43µs ?
?/sec 1.01 107.9±1.02µs ? ?/sec
convert_rows 4096 string_dictionary_low_cardinality(30, 0)
1.00 74.0±0.21µs ?
?/sec 1.01 74.5±0.33µs ? ?/sec
convert_rows 4096 u64(0)
1.00 30.1±0.08µs ?
?/sec 1.00 30.0±0.06µs ? ?/sec
convert_rows 4096 u64(0.3)
1.00 30.2±0.06µs ?
?/sec 1.00 30.2±0.04µs ? ?/sec
iterate rows
1.00 2.6±0.00µs ?
?/sec 1.00 2.6±0.00µs ? ?/sec
```
</p>
</details>
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