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:

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.

If there is an overlap between multiple impl blocks in terms of
identifiers, we still run a O(m^2) algorithm on groups of impl
blocks that have overlaps, but that m refers to the size of the
connected component, which is hopefully smaller than the n
that refers to the sum of all connected components.

Author: est31

compiler/rustc_typeck/src/coherence/inherent_impls_overlap.rs

@@ -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);
@@ -45,7 +48,7 @@ impl InherentOverlapChecker<'tcx> {
         false
     }
 
-    fn compare_hygienically(&self, item1: &'tcx ty::AssocItem, item2: &'tcx ty::AssocItem) -> bool {
+    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()
@@ -134,10 +137,149 @@ 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.
+                if impls.len() < 30 {
+                    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,
+                                    );
+                                }
+                            }
                         }
                     }
                 }