Auto merge of #78317 - est31:linear_in_impl_count, r=matthewjasper
Turn quadratic time on number of impl blocks into linear time Previously, if you had a lot of inherent impl blocks on a type like: ```Rust struct Foo; impl Foo { fn foo_1() {} } // ... impl Foo { fn foo_100_000() {} } ``` The compiler would be very slow at processing it, because an internal algorithm would run in O(n^2), where n is the number of impl blocks. Now, we add a new algorithm that allocates but is faster asymptotically. Comparing rustc nightly with a local build of rustc as of this PR (results in seconds): | N | real time before | real time after | | - | - | - | | 4_000 | 0.57 | 0.46 | | 8_000 | 1.31 | 0.84 | | 16_000 | 3.56 | 1.69 | | 32_000 | 10.60 | 3.73 | I've tuned up the numbers to make the effect larger than the startup noise of rustc, but the asymptotic difference should hold for smaller n as well. Note: current state of the PR omits error messages if there are other errors present already. For now, I'm mainly interested in a perf run to study whether this issue is present at all. Please queue one for this PR. Thanks!
This commit is contained in:
commit
c609b2eaf3
5 changed files with 365 additions and 16 deletions
|
@ -1,10 +1,13 @@
|
|||
use rustc_data_structures::fx::{FxHashMap, FxHashSet};
|
||||
use rustc_errors::struct_span_err;
|
||||
use rustc_hir as hir;
|
||||
use rustc_hir::def_id::{CrateNum, DefId, LOCAL_CRATE};
|
||||
use rustc_hir::itemlikevisit::ItemLikeVisitor;
|
||||
use rustc_middle::ty::{self, TyCtxt};
|
||||
use rustc_span::Symbol;
|
||||
use rustc_trait_selection::traits::{self, SkipLeakCheck};
|
||||
use smallvec::SmallVec;
|
||||
use std::collections::hash_map::Entry;
|
||||
|
||||
pub fn crate_inherent_impls_overlap_check(tcx: TyCtxt<'_>, crate_num: CrateNum) {
|
||||
assert_eq!(crate_num, LOCAL_CRATE);
|
||||
|
@ -33,12 +36,9 @@ impl InherentOverlapChecker<'tcx> {
|
|||
}
|
||||
|
||||
for item1 in impl_items1.in_definition_order() {
|
||||
let collision = impl_items2.filter_by_name_unhygienic(item1.ident.name).any(|item2| {
|
||||
// Symbols and namespace match, compare hygienically.
|
||||
item1.kind.namespace() == item2.kind.namespace()
|
||||
&& item1.ident.normalize_to_macros_2_0()
|
||||
== item2.ident.normalize_to_macros_2_0()
|
||||
});
|
||||
let collision = impl_items2
|
||||
.filter_by_name_unhygienic(item1.ident.name)
|
||||
.any(|item2| self.compare_hygienically(item1, item2));
|
||||
|
||||
if collision {
|
||||
return true;
|
||||
|
@ -48,6 +48,12 @@ impl InherentOverlapChecker<'tcx> {
|
|||
false
|
||||
}
|
||||
|
||||
fn compare_hygienically(&self, item1: &ty::AssocItem, item2: &ty::AssocItem) -> bool {
|
||||
// Symbols and namespace match, compare hygienically.
|
||||
item1.kind.namespace() == item2.kind.namespace()
|
||||
&& item1.ident.normalize_to_macros_2_0() == item2.ident.normalize_to_macros_2_0()
|
||||
}
|
||||
|
||||
fn check_for_common_items_in_impls(
|
||||
&self,
|
||||
impl1: DefId,
|
||||
|
@ -58,12 +64,9 @@ impl InherentOverlapChecker<'tcx> {
|
|||
let impl_items2 = self.tcx.associated_items(impl2);
|
||||
|
||||
for item1 in impl_items1.in_definition_order() {
|
||||
let collision = impl_items2.filter_by_name_unhygienic(item1.ident.name).find(|item2| {
|
||||
// Symbols and namespace match, compare hygienically.
|
||||
item1.kind.namespace() == item2.kind.namespace()
|
||||
&& item1.ident.normalize_to_macros_2_0()
|
||||
== item2.ident.normalize_to_macros_2_0()
|
||||
});
|
||||
let collision = impl_items2
|
||||
.filter_by_name_unhygienic(item1.ident.name)
|
||||
.find(|item2| self.compare_hygienically(item1, item2));
|
||||
|
||||
if let Some(item2) = collision {
|
||||
let name = item1.ident.normalize_to_macros_2_0();
|
||||
|
@ -134,10 +137,150 @@ impl ItemLikeVisitor<'v> for InherentOverlapChecker<'tcx> {
|
|||
.map(|impl_def_id| (impl_def_id, self.tcx.associated_items(*impl_def_id)))
|
||||
.collect::<SmallVec<[_; 8]>>();
|
||||
|
||||
for (i, &(&impl1_def_id, impl_items1)) in impls_items.iter().enumerate() {
|
||||
for &(&impl2_def_id, impl_items2) in &impls_items[(i + 1)..] {
|
||||
if self.impls_have_common_items(impl_items1, impl_items2) {
|
||||
self.check_for_overlapping_inherent_impls(impl1_def_id, impl2_def_id);
|
||||
// Perform a O(n^2) algorithm for small n,
|
||||
// otherwise switch to an allocating algorithm with
|
||||
// faster asymptotic runtime.
|
||||
const ALLOCATING_ALGO_THRESHOLD: usize = 500;
|
||||
if impls.len() < ALLOCATING_ALGO_THRESHOLD {
|
||||
for (i, &(&impl1_def_id, impl_items1)) in impls_items.iter().enumerate() {
|
||||
for &(&impl2_def_id, impl_items2) in &impls_items[(i + 1)..] {
|
||||
if self.impls_have_common_items(impl_items1, impl_items2) {
|
||||
self.check_for_overlapping_inherent_impls(
|
||||
impl1_def_id,
|
||||
impl2_def_id,
|
||||
);
|
||||
}
|
||||
}
|
||||
}
|
||||
} else {
|
||||
// Build a set of connected regions of impl blocks.
|
||||
// Two impl blocks are regarded as connected if they share
|
||||
// an item with the same unhygienic identifier.
|
||||
// After we have assembled the connected regions,
|
||||
// run the O(n^2) algorithm on each connected region.
|
||||
// This is advantageous to running the algorithm over the
|
||||
// entire graph when there are many connected regions.
|
||||
|
||||
struct ConnectedRegion {
|
||||
idents: SmallVec<[Symbol; 8]>,
|
||||
impl_blocks: FxHashSet<usize>,
|
||||
}
|
||||
// Highest connected region id
|
||||
let mut highest_region_id = 0;
|
||||
let mut connected_region_ids = FxHashMap::default();
|
||||
let mut connected_regions = FxHashMap::default();
|
||||
|
||||
for (i, &(&_impl_def_id, impl_items)) in impls_items.iter().enumerate() {
|
||||
if impl_items.len() == 0 {
|
||||
continue;
|
||||
}
|
||||
// First obtain a list of existing connected region ids
|
||||
let mut idents_to_add = SmallVec::<[Symbol; 8]>::new();
|
||||
let ids = impl_items
|
||||
.in_definition_order()
|
||||
.filter_map(|item| {
|
||||
let entry = connected_region_ids.entry(item.ident.name);
|
||||
if let Entry::Occupied(e) = &entry {
|
||||
Some(*e.get())
|
||||
} else {
|
||||
idents_to_add.push(item.ident.name);
|
||||
None
|
||||
}
|
||||
})
|
||||
.collect::<FxHashSet<usize>>();
|
||||
match ids.len() {
|
||||
0 | 1 => {
|
||||
let id_to_set = if ids.len() == 0 {
|
||||
// Create a new connected region
|
||||
let region = ConnectedRegion {
|
||||
idents: idents_to_add,
|
||||
impl_blocks: std::iter::once(i).collect(),
|
||||
};
|
||||
connected_regions.insert(highest_region_id, region);
|
||||
(highest_region_id, highest_region_id += 1).0
|
||||
} else {
|
||||
// Take the only id inside the list
|
||||
let id_to_set = *ids.iter().next().unwrap();
|
||||
let region = connected_regions.get_mut(&id_to_set).unwrap();
|
||||
region.impl_blocks.insert(i);
|
||||
region.idents.extend_from_slice(&idents_to_add);
|
||||
id_to_set
|
||||
};
|
||||
let (_id, region) = connected_regions.iter().next().unwrap();
|
||||
// Update the connected region ids
|
||||
for ident in region.idents.iter() {
|
||||
connected_region_ids.insert(*ident, id_to_set);
|
||||
}
|
||||
}
|
||||
_ => {
|
||||
// We have multiple connected regions to merge.
|
||||
// In the worst case this might add impl blocks
|
||||
// one by one and can thus be O(n^2) in the size
|
||||
// of the resulting final connected region, but
|
||||
// this is no issue as the final step to check
|
||||
// for overlaps runs in O(n^2) as well.
|
||||
|
||||
// Take the smallest id from the list
|
||||
let id_to_set = *ids.iter().min().unwrap();
|
||||
|
||||
// Sort the id list so that the algorithm is deterministic
|
||||
let mut ids = ids.into_iter().collect::<SmallVec<[_; 8]>>();
|
||||
ids.sort();
|
||||
|
||||
let mut region = connected_regions.remove(&id_to_set).unwrap();
|
||||
region.idents.extend_from_slice(&idents_to_add);
|
||||
region.impl_blocks.insert(i);
|
||||
|
||||
for &id in ids.iter() {
|
||||
if id == id_to_set {
|
||||
continue;
|
||||
}
|
||||
let r = connected_regions.remove(&id).unwrap();
|
||||
// Update the connected region ids
|
||||
for ident in r.idents.iter() {
|
||||
connected_region_ids.insert(*ident, id_to_set);
|
||||
}
|
||||
region.idents.extend_from_slice(&r.idents);
|
||||
region.impl_blocks.extend(r.impl_blocks);
|
||||
}
|
||||
connected_regions.insert(id_to_set, region);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
debug!(
|
||||
"churning through {} components (sum={}, avg={}, var={}, max={})",
|
||||
connected_regions.len(),
|
||||
impls.len(),
|
||||
impls.len() / connected_regions.len(),
|
||||
{
|
||||
let avg = impls.len() / connected_regions.len();
|
||||
let s = connected_regions
|
||||
.iter()
|
||||
.map(|r| r.1.impl_blocks.len() as isize - avg as isize)
|
||||
.map(|v| v.abs() as usize)
|
||||
.sum::<usize>();
|
||||
s / connected_regions.len()
|
||||
},
|
||||
connected_regions.iter().map(|r| r.1.impl_blocks.len()).max().unwrap()
|
||||
);
|
||||
// List of connected regions is built. Now, run the overlap check
|
||||
// for each pair of impl blocks in the same connected region.
|
||||
for (_id, region) in connected_regions.into_iter() {
|
||||
let mut impl_blocks =
|
||||
region.impl_blocks.into_iter().collect::<SmallVec<[_; 8]>>();
|
||||
impl_blocks.sort();
|
||||
for (i, &impl1_items_idx) in impl_blocks.iter().enumerate() {
|
||||
let &(&impl1_def_id, impl_items1) = &impls_items[impl1_items_idx];
|
||||
for &impl2_items_idx in impl_blocks[(i + 1)..].iter() {
|
||||
let &(&impl2_def_id, impl_items2) = &impls_items[impl2_items_idx];
|
||||
if self.impls_have_common_items(impl_items1, impl_items2) {
|
||||
self.check_for_overlapping_inherent_impls(
|
||||
impl1_def_id,
|
||||
impl2_def_id,
|
||||
);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
|
Loading…
Add table
Add a link
Reference in a new issue