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Add Criterion benchmarks for parser (#7686)

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This PR sets up [Criterion](https://github.com/bheisler/criterion.rs)
for benchmarking in the main `nu` crate, and adds some simple parser
benchmarks.

To run the benchmarks, just do `cargo bench` or `cargo bench -- <regex
matching benchmark names>` in the repo root:

```bash
〉cargo bench -- parse
...
     Running benches/parser_benchmark.rs (target/release/deps/parser_benchmark-75d224bac82d5b0b)
parse_default_env_file  time:   [221.17 µs 222.34 µs 223.61 µs]
Found 8 outliers among 100 measurements (8.00%)
  5 (5.00%) high mild
  3 (3.00%) high severe

parse_default_config_file
                        time:   [1.4935 ms 1.4993 ms 1.5059 ms]
Found 11 outliers among 100 measurements (11.00%)
  7 (7.00%) high mild
  4 (4.00%) high severe
```

Existing benchmarks from `nu-plugin` have been moved into the main `nu`
crate to keep all our benchmarks in one place.
This commit is contained in:
Reilly Wood
2023-01-05 11:39:54 -08:00
committed by GitHub
parent 26d1307476
commit 771270d526
8 changed files with 119 additions and 44 deletions
Download Patch File Download Diff File Expand all files Collapse all files

7
crates/nu-plugin/Cargo.toml
View File

@ -15,10 +15,3 @@ serde = { version = "1.0.143" }
serde_json = { version = "1.0"}
rmp = "0.8.11"
rmp-serde = "1.1.0"
[dev-dependencies]
criterion = "0.3"
[[bench]]
name = "encoder_benchmark"
harness = false

6
crates/nu-plugin/README.md
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@ -1,6 +0,0 @@
# nu-plugin
## Benchmark
Here is a simple benchmark for different protocol for encoding/decoding nushell table, with different rows and columns. You can simply run `cargo bench` to run benchmark.
The relative html report is in `target/criterion/report/index.html`.

76
crates/nu-plugin/benches/encoder_benchmark.rs
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@ -1,76 +0,0 @@
use criterion::{criterion_group, criterion_main, Criterion};
use nu_plugin::{EncodingType, PluginResponse};
use nu_protocol::{Span, Value};
// generate a new table data with `row_cnt` rows, `col_cnt` columns.
fn new_test_data(row_cnt: usize, col_cnt: usize) -> Value {
let columns: Vec<String> = (0..col_cnt).map(|x| format!("col_{x}")).collect();
let vals: Vec<Value> = (0..col_cnt as i64).map(Value::test_int).collect();
Value::List {
vals: (0..row_cnt)
.map(|_| Value::test_record(columns.clone(), vals.clone()))
.collect(),
span: Span::test_data(),
}
}
fn bench_encoding(c: &mut Criterion) {
let mut group = c.benchmark_group("Encoding");
let test_cnt_pairs = [
(100, 5),
(100, 10),
(100, 15),
(1000, 5),
(1000, 10),
(1000, 15),
(10000, 5),
(10000, 10),
(10000, 15),
];
for (row_cnt, col_cnt) in test_cnt_pairs.into_iter() {
for fmt in ["json", "msgpack"] {
group.bench_function(&format!("{fmt} encode {row_cnt} * {col_cnt}"), |b| {
let mut res = vec![];
let test_data = PluginResponse::Value(Box::new(new_test_data(row_cnt, col_cnt)));
let encoder = EncodingType::try_from_bytes(fmt.as_bytes()).unwrap();
b.iter(|| encoder.encode_response(&test_data, &mut res))
});
}
}
group.finish();
}
fn bench_decoding(c: &mut Criterion) {
let mut group = c.benchmark_group("Decoding");
let test_cnt_pairs = [
(100, 5),
(100, 10),
(100, 15),
(1000, 5),
(1000, 10),
(1000, 15),
(10000, 5),
(10000, 10),
(10000, 15),
];
for (row_cnt, col_cnt) in test_cnt_pairs.into_iter() {
for fmt in ["json", "msgpack"] {
group.bench_function(&format!("{fmt} decode for {row_cnt} * {col_cnt}"), |b| {
let mut res = vec![];
let test_data = PluginResponse::Value(Box::new(new_test_data(row_cnt, col_cnt)));
let encoder = EncodingType::try_from_bytes(fmt.as_bytes()).unwrap();
encoder.encode_response(&test_data, &mut res).unwrap();
let mut binary_data = std::io::Cursor::new(res);
b.iter(|| {
binary_data.set_position(0);
encoder.decode_response(&mut binary_data)
})
});
}
}
group.finish();
}
criterion_group!(benches, bench_encoding, bench_decoding);
criterion_main!(benches);