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fn write_stream(col: &ColumnRef) { | |
let mut buf = Vec::with_capacity(1000*1000); | |
let s = col.data_type().create_serializer(); | |
let mut stream = s.serialize_csv(&col, &FormatSettings::default()).unwrap(); | |
while let Some(field) = stream.next() { | |
buf.extend_from_slice(field); | |
buf.push(b','); | |
} | |
} | |
fn write_vec(col: &ColumnRef) { | |
let mut buf = Vec::with_capacity(1000*1000); | |
let s = col.data_type().create_serializer(); | |
let v = s.serialize_column(&col, &FormatSettings::default()).unwrap(); | |
for field in v { | |
buf.extend_from_slice(&field.as_bytes()); | |
buf.push(b','); | |
} | |
} |
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Gnuplot not found, using plotters backend | |
Benchmarking csv write i32 2^10 not null | |
Benchmarking csv write i32 2^10 not null: Warming up for 3.0000 s | |
Benchmarking csv write i32 2^10 not null: Collecting 100 samples in estimated 5.0493 s (495k iterations) | |
Benchmarking csv write i32 2^10 not null: Analyzing | |
csv write i32 2^10 not null | |
time: [10.140 us 10.153 us 10.166 us] | |
Found 6 outliers among 100 measurements (6.00%) | |
2 (2.00%) low mild | |
3 (3.00%) high mild | |
1 (1.00%) high severe | |
Benchmarking csv write i32 2^12 not null | |
Benchmarking csv write i32 2^12 not null: Warming up for 3.0000 s | |
Benchmarking csv write i32 2^12 not null: Collecting 100 samples in estimated 5.1627 s (106k iterations) | |
Benchmarking csv write i32 2^12 not null: Analyzing | |
csv write i32 2^12 not null | |
time: [47.459 us 47.629 us 47.831 us] | |
Benchmarking csv write i32 2^14 not null | |
Benchmarking csv write i32 2^14 not null: Warming up for 3.0000 s | |
Benchmarking csv write i32 2^14 not null: Collecting 100 samples in estimated 5.4855 s (25k iterations) | |
Benchmarking csv write i32 2^14 not null: Analyzing | |
csv write i32 2^14 not null | |
time: [216.46 us 217.00 us 217.62 us] | |
Found 2 outliers among 100 measurements (2.00%) | |
1 (1.00%) high mild | |
1 (1.00%) high severe | |
Benchmarking csv write i32 2^16 not null | |
Benchmarking csv write i32 2^16 not null: Warming up for 3.0000 s | |
Benchmarking csv write i32 2^16 not null: Collecting 100 samples in estimated 9.1455 s (10k iterations) | |
Benchmarking csv write i32 2^16 not null: Analyzing | |
csv write i32 2^16 not null | |
time: [904.87 us 905.99 us 907.16 us] | |
Benchmarking csv write i32 2^18 not null | |
Benchmarking csv write i32 2^18 not null: Warming up for 3.0000 s | |
Benchmarking csv write i32 2^18 not null: Collecting 100 samples in estimated 5.1667 s (1400 iterations) | |
Benchmarking csv write i32 2^18 not null: Analyzing | |
csv write i32 2^18 not null | |
time: [3.6859 ms 3.6916 ms 3.6973 ms] |
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Gnuplot not found, using plotters backend | |
Benchmarking csv write i32 2^10 not null | |
Benchmarking csv write i32 2^10 not null: Warming up for 3.0000 s | |
Benchmarking csv write i32 2^10 not null: Collecting 100 samples in estimated 5.1116 s (86k iterations) | |
Benchmarking csv write i32 2^10 not null: Analyzing | |
csv write i32 2^10 not null | |
time: [59.350 us 59.406 us 59.464 us] | |
change: [+483.90% +484.94% +486.03%] (p = 0.00 < 0.05) | |
Performance has regressed. | |
Found 5 outliers among 100 measurements (5.00%) | |
3 (3.00%) low mild | |
2 (2.00%) high mild | |
Benchmarking csv write i32 2^12 not null | |
Benchmarking csv write i32 2^12 not null: Warming up for 3.0000 s | |
Benchmarking csv write i32 2^12 not null: Collecting 100 samples in estimated 5.0646 s (20k iterations) | |
Benchmarking csv write i32 2^12 not null: Analyzing | |
csv write i32 2^12 not null | |
time: [248.51 us 248.81 us 249.10 us] | |
change: [+412.43% +414.91% +417.36%] (p = 0.00 < 0.05) | |
Performance has regressed. | |
Found 6 outliers among 100 measurements (6.00%) | |
1 (1.00%) low severe | |
3 (3.00%) low mild | |
2 (2.00%) high mild | |
Benchmarking csv write i32 2^14 not null | |
Benchmarking csv write i32 2^14 not null: Warming up for 3.0000 s | |
Warning: Unable to complete 100 samples in 5.0s. You may wish to increase target time to 5.1s, enable flat sampling, or reduce sample count to 70. | |
Benchmarking csv write i32 2^14 not null: Collecting 100 samples in estimated 5.0731 s (5050 iterations) | |
Benchmarking csv write i32 2^14 not null: Analyzing | |
csv write i32 2^14 not null | |
time: [999.72 us 1.0007 ms 1.0018 ms] | |
change: [+360.17% +361.29% +362.38%] (p = 0.00 < 0.05) | |
Performance has regressed. | |
Found 3 outliers among 100 measurements (3.00%) | |
1 (1.00%) low severe | |
1 (1.00%) low mild | |
1 (1.00%) high mild | |
Benchmarking csv write i32 2^16 not null | |
Benchmarking csv write i32 2^16 not null: Warming up for 3.0000 s | |
Benchmarking csv write i32 2^16 not null: Collecting 100 samples in estimated 5.2801 s (1300 iterations) | |
Benchmarking csv write i32 2^16 not null: Analyzing | |
csv write i32 2^16 not null | |
time: [4.0588 ms 4.0632 ms 4.0675 ms] | |
change: [+347.26% +347.99% +348.75%] (p = 0.00 < 0.05) | |
Performance has regressed. | |
Found 4 outliers among 100 measurements (4.00%) | |
4 (4.00%) low mild | |
Benchmarking csv write i32 2^18 not null | |
Benchmarking csv write i32 2^18 not null: Warming up for 3.0000 s | |
Benchmarking csv write i32 2^18 not null: Collecting 100 samples in estimated 6.5120 s (400 iterations) | |
Benchmarking csv write i32 2^18 not null: Analyzing | |
csv write i32 2^18 not null | |
time: [16.267 ms 16.281 ms 16.295 ms] | |
change: [+340.23% +341.02% +341.80%] (p = 0.00 < 0.05) | |
Performance has regressed. | |
Found 2 outliers among 100 measurements (2.00%) | |
1 (1.00%) high mild | |
1 (1.00%) high severe |
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