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Decrease deserialization complexity from quadratic to linear (#349) 

* Speed up array code

* Speed up map code too

Also add regression test

* Use more obvious closure notation

* Document the builder functions
master
est31 2019-10-28 16:05:13 +01:00 committed by Alex Crichton
parent ec21d604f8
commit c049b7aaec
2 changed files with 131 additions and 18 deletions
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112
src/de.rs
View File

@ -5,6 +5,7 @@
//! provided at the top of the crate.
use std::borrow::Cow;
use std::collections::HashMap;
use std::error;
use std::f64;
use std::fmt;
@ -215,6 +216,8 @@ impl<'de, 'b> de::Deserializer<'de> for &'b mut Deserializer<'de> {
V: de::Visitor<'de>,
{
let mut tables = self.tables()?;
let table_indices = build_table_indices(&tables);
let table_pindices = build_table_pindices(&tables);
let res = visitor.visit_map(MapVisitor {
values: Vec::new().into_iter().peekable(),
@ -223,6 +226,8 @@ impl<'de, 'b> de::Deserializer<'de> for &'b mut Deserializer<'de> {
cur: 0,
cur_parent: 0,
max: tables.len(),
table_indices: &table_indices,
table_pindices: &table_pindices,
tables: &mut tables,
array: false,
de: self,
@ -319,6 +324,53 @@ impl<'de, 'b> de::Deserializer<'de> for &'b mut Deserializer<'de> {
}
}
// Builds a datastructure that allows for efficient sublinear lookups.
// The returned HashMap contains a mapping from table header (like [a.b.c])
// to list of tables with that precise name. The tables are being identified
// by their index in the passed slice. We use a list as the implementation
// uses this data structure for arrays as well as tables,
// so if any top level [[name]] array contains multiple entries,
// there are multiple entires in the list.
// The lookup is performed in the `SeqAccess` implementation of `MapVisitor`.
// The lists are ordered, which we exploit in the search code by using
// bisection.
fn build_table_indices<'de>(tables: &[Table<'de>]) -> HashMap<Vec<Cow<'de, str>>, Vec<usize>> {
let mut res = HashMap::new();
for (i, table) in tables.iter().enumerate() {
let header = table.header.iter().map(|v| v.1.clone()).collect::<Vec<_>>();
res.entry(header).or_insert(Vec::new()).push(i);
}
res
}
// Builds a datastructure that allows for efficient sublinear lookups.
// The returned HashMap contains a mapping from table header (like [a.b.c])
// to list of tables whose name at least starts with the specified
// name. So searching for [a.b] would give both [a.b.c.d] as well as [a.b.e].
// The tables are being identified by their index in the passed slice.
//
// A list is used for two reasons: First, the implementation also
// stores arrays in the same data structure and any top level array
// of size 2 or greater creates multiple entries in the list with the
// same shared name. Second, there can be multiple tables sharing
// the same prefix.
//
// The lookup is performed in the `MapAccess` implementation of `MapVisitor`.
// The lists are ordered, which we exploit in the search code by using
// bisection.
fn build_table_pindices<'de>(tables: &[Table<'de>]) -> HashMap<Vec<Cow<'de, str>>, Vec<usize>> {
let mut res = HashMap::new();
for (i, table) in tables.iter().enumerate() {
let header = table.header.iter().map(|v| v.1.clone()).collect::<Vec<_>>();
for len in 0..=header.len() {
res.entry(header[..len].to_owned())
.or_insert(Vec::new())
.push(i);
}
}
res
}
fn headers_equal<'a, 'b>(hdr_a: &[(Span, Cow<'a, str>)], hdr_b: &[(Span, Cow<'b, str>)]) -> bool {
if hdr_a.len() != hdr_b.len() {
return false;
@ -340,6 +392,8 @@ struct MapVisitor<'de, 'b> {
cur: usize,
cur_parent: usize,
max: usize,
table_indices: &'b HashMap<Vec<Cow<'de, str>>, Vec<usize>>,
table_pindices: &'b HashMap<Vec<Cow<'de, str>>, Vec<usize>>,
tables: &'b mut [Table<'de>],
array: bool,
de: &'b mut Deserializer<'de>,
@ -365,20 +419,25 @@ impl<'de, 'b> de::MapAccess<'de> for MapVisitor<'de, 'b> {
}
let next_table = {
let prefix = &self.tables[self.cur_parent].header[..self.depth];
self.tables[self.cur..self.max]
let prefix_stripped = self.tables[self.cur_parent].header[..self.depth]
.iter()
.enumerate()
.find(|&(_, t)| {
if t.values.is_none() {
return false;
}
match t.header.get(..self.depth) {
Some(header) => headers_equal(&header, &prefix),
None => false,
.map(|v| v.1.clone())
.collect::<Vec<_>>();
self.table_pindices
.get(&prefix_stripped)
.and_then(|entries| {
let start = entries.binary_search(&self.cur).unwrap_or_else(|v| v);
if start == entries.len() || entries[start] < self.cur {
return None;
}
entries[start..]
.iter()
.copied()
.filter(|i| *i < self.max)
.map(|i| (i, &self.tables[i]))
.find(|(_, table)| table.values.is_some())
.map(|p| p.0)
})
.map(|(i, _)| i + self.cur)
};
let pos = match next_table {
@ -471,6 +530,8 @@ impl<'de, 'b> de::MapAccess<'de> for MapVisitor<'de, 'b> {
cur: 0,
max: self.max,
array,
table_indices: &*self.table_indices,
table_pindices: &*self.table_pindices,
tables: &mut *self.tables,
de: &mut *self.de,
});
@ -495,15 +556,28 @@ impl<'de, 'b> de::SeqAccess<'de> for MapVisitor<'de, 'b> {
return Ok(None);
}
let next = self.tables[..self.max]
let header_stripped = self.tables[self.cur_parent]
.header
.iter()
.enumerate()
.skip(self.cur_parent + 1)
.find(|&(_, table)| {
let tables_eq = headers_equal(&table.header, &self.tables[self.cur_parent].header);
table.array && tables_eq
.map(|v| v.1.clone())
.collect::<Vec<_>>();
let start_idx = self.cur_parent + 1;
let next = self
.table_indices
.get(&header_stripped)
.and_then(|entries| {
let start = entries.binary_search(&start_idx).unwrap_or_else(|v| v);
if start == entries.len() || entries[start] < start_idx {
return None;
}
entries[start..]
.iter()
.copied()
.filter(|i| *i < self.max)
.map(|i| (i, &self.tables[i]))
.find(|(_, table)| table.array)
.map(|p| p.0)
})
.map(|p| p.0)
.unwrap_or(self.max);
let ret = seed.deserialize(MapVisitor {
@ -519,6 +593,8 @@ impl<'de, 'b> de::SeqAccess<'de> for MapVisitor<'de, 'b> {
max: next,
cur: 0,
array: false,
table_indices: &*self.table_indices,
table_pindices: &*self.table_pindices,
tables: &mut self.tables,
de: &mut self.de,
})?;

37
test-suite/tests/linear.rs Normal file
View File

@ -0,0 +1,37 @@
use std::time::{Duration, Instant};
use toml::Value;
const TOLERANCE: f64 = 2.0;
fn measure_time(entries: usize, f: impl Fn(usize) -> String) -> Duration {
let start = Instant::now();
let mut s = String::new();
for i in 0..entries {
s += &f(i);
s += "entry = 42\n"
}
s.parse::<Value>().unwrap();
Instant::now() - start
}
#[test]
fn linear_increase_map() {
let time_1 = measure_time(100, |i| format!("[header_no_{}]\n", i));
let time_4 = measure_time(400, |i| format!("[header_no_{}]\n", i));
dbg!(time_1, time_4);
// Now ensure that the deserialization time has increased linearly
// (within a tolerance interval) instead of, say, quadratically
assert!(time_4 > time_1.mul_f64(4.0 - TOLERANCE));
assert!(time_4 < time_1.mul_f64(4.0 + TOLERANCE));
}
#[test]
fn linear_increase_array() {
let time_1 = measure_time(100, |i| format!("[[header_no_{}]]\n", i));
let time_4 = measure_time(400, |i| format!("[[header_no_{}]]\n", i));
dbg!(time_1, time_4);
// Now ensure that the deserialization time has increased linearly
// (within a tolerance interval) instead of, say, quadratically
assert!(time_4 > time_1.mul_f64(4.0 - TOLERANCE));
assert!(time_4 < time_1.mul_f64(4.0 + TOLERANCE));
}