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Optimize position search in error path
Translating index into a line/column pair takes considerable time. Notably, the JSON benchmark modified to run on malformed data spends around 50% of the CPU time generating the error object. While it is generally assumed that the cold path is quite slow, such a drastic pessimization may be unexpected, especially when a faster implementation exists. Using vectorized routines provided by the memchr crate increases performance of the failure path by 2x on average. Old implementation: DOM STRUCT data/canada.json 122 MB/s 168 MB/s data/citm_catalog.json 135 MB/s 195 MB/s data/twitter.json 142 MB/s 226 MB/s New implementation: DOM STRUCT data/canada.json 216 MB/s 376 MB/s data/citm_catalog.json 238 MB/s 736 MB/s data/twitter.json 210 MB/s 492 MB/s In comparison, the performance of the happy path is: DOM STRUCT data/canada.json 283 MB/s 416 MB/s data/citm_catalog.json 429 MB/s 864 MB/s data/twitter.json 275 MB/s 541 MB/s While this introduces a new dependency, memchr is much faster to compile than serde, so compile time does not increase significantly. Additionally, memchr provides a more efficient SWAR-based implementation of both the memchr and count routines even without std, providing benefits for embedded uses as well.
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@ -14,6 +14,7 @@ rust-version = "1.56"
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[dependencies]
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indexmap = { version = "2.2.3", optional = true }
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itoa = "1.0"
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memchr = { version = "2", default-features = false }
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ryu = "1.0"
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serde = { version = "1.0.194", default-features = false }
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@ -45,7 +46,7 @@ features = ["raw_value"]
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[features]
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default = ["std"]
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std = ["serde/std"]
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std = ["memchr/std", "serde/std"]
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# Provide integration for heap-allocated collections without depending on the
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# rest of the Rust standard library.
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19
src/read.rs
19
src/read.rs
@ -415,19 +415,14 @@ impl<'a> SliceRead<'a> {
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}
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fn position_of_index(&self, i: usize) -> Position {
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let mut position = Position { line: 1, column: 0 };
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for ch in &self.slice[..i] {
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match *ch {
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b'\n' => {
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position.line += 1;
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position.column = 0;
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}
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_ => {
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position.column += 1;
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}
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}
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let start_of_line = match memchr::memrchr(b'\n', &self.slice[..i]) {
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Some(position) => position + 1,
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None => 0,
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};
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Position {
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line: 1 + memchr::memchr_iter(b'\n', &self.slice[..start_of_line]).count(),
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column: i - start_of_line,
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}
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position
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}
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/// The big optimization here over IoRead is that if the string contains no
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