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complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
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// Copyright 2014 The Rust Project Developers. See the COPYRIGHT
// file at the top-level directory of this distribution and at
// http://rust-lang.org/COPYRIGHT.
//
// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
// http://www.apache.org/licenses/LICENSE-2.0> or the MIT license
// <LICENSE-MIT or http://opensource.org/licenses/MIT>, at your
// option. This file may not be copied, modified, or distributed
// except according to those terms.
// This implementation is largely based on the high-level description and analysis of B-Trees
// found in *Open Data Structures* (ODS). Although our implementation does not use any of
// the source found in ODS, if one wishes to review the high-level design of this structure, it
// can be freely downloaded at http://opendatastructures.org/. Its contents are as of this
// writing (August 2014) freely licensed under the following Creative Commons Attribution
// License: [CC BY 2.5 CA](http://creativecommons.org/licenses/by/2.5/ca/).
pub use self::Entry::*;
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
use core::prelude::*;
use self::StackOp::*;
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
use super::node::*;
use core::borrow::BorrowFrom;
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
use std::hash::{Writer, Hash};
use core::default::Default;
use core::{iter, fmt, mem};
use core::fmt::Show;
use ring_buf::RingBuf;
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
// FIXME(conventions): implement bounded iterators
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
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/// A map based on a B-Tree.
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///
/// B-Trees represent a fundamental compromise between cache-efficiency and actually minimizing
/// the amount of work performed in a search. In theory, a binary search tree (BST) is the optimal
/// choice for a sorted map, as a perfectly balanced BST performs the theoretical minimum amount of
/// comparisons necessary to find an element (log<sub>2</sub>n). However, in practice the way this
/// is done is *very* inefficient for modern computer architectures. In particular, every element
/// is stored in its own individually heap-allocated node. This means that every single insertion
/// triggers a heap-allocation, and every single comparison should be a cache-miss. Since these
/// are both notably expensive things to do in practice, we are forced to at very least reconsider
/// the BST strategy.
///
/// A B-Tree instead makes each node contain B-1 to 2B-1 elements in a contiguous array. By doing
2014-10-25 23:10:16 -04:00
/// this, we reduce the number of allocations by a factor of B, and improve cache efficiency in
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/// searches. However, this does mean that searches will have to do *more* comparisons on average.
/// The precise number of comparisons depends on the node search strategy used. For optimal cache
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/// efficiency, one could search the nodes linearly. For optimal comparisons, one could search
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/// the node using binary search. As a compromise, one could also perform a linear search
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/// that initially only checks every i<sup>th</sup> element for some choice of i.
///
/// Currently, our implementation simply performs naive linear search. This provides excellent
/// performance on *small* nodes of elements which are cheap to compare. However in the future we
/// would like to further explore choosing the optimal search strategy based on the choice of B,
/// and possibly other factors. Using linear search, searching for a random element is expected
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/// to take O(B log<sub>B</sub>n) comparisons, which is generally worse than a BST. In practice,
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/// however, performance is excellent. `BTreeMap` is able to readily outperform `TreeMap` under
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/// many workloads, and is competitive where it doesn't. BTreeMap also generally *scales* better
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/// than TreeMap, making it more appropriate for large datasets.
///
/// However, `TreeMap` may still be more appropriate to use in many contexts. If elements are very
/// large or expensive to compare, `TreeMap` may be more appropriate. It won't allocate any
/// more space than is needed, and will perform the minimal number of comparisons necessary.
/// `TreeMap` also provides much better performance stability guarantees. Generally, very few
/// changes need to be made to update a BST, and two updates are expected to take about the same
/// amount of time on roughly equal sized BSTs. However a B-Tree's performance is much more
/// amortized. If a node is overfull, it must be split into two nodes. If a node is underfull, it
/// may be merged with another. Both of these operations are relatively expensive to perform, and
/// it's possible to force one to occur at every single level of the tree in a single insertion or
/// deletion. In fact, a malicious or otherwise unlucky sequence of insertions and deletions can
/// force this degenerate behaviour to occur on every operation. While the total amount of work
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/// done on each operation isn't *catastrophic*, and *is* still bounded by O(B log<sub>B</sub>n),
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/// it is certainly much slower when it does.
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
#[deriving(Clone)]
pub struct BTreeMap<K, V> {
root: Node<K, V>,
length: uint,
depth: uint,
b: uint,
}
/// An abstract base over-which all other BTree iterators are built.
struct AbsEntries<T> {
lca: T,
left: RingBuf<T>,
right: RingBuf<T>,
size: uint,
}
/// An iterator over a BTreeMap's entries.
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pub struct Entries<'a, K: 'a, V: 'a> {
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
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inner: AbsEntries<Traversal<'a, K, V>>
}
/// A mutable iterator over a BTreeMap's entries.
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pub struct MutEntries<'a, K: 'a, V: 'a> {
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
inner: AbsEntries<MutTraversal<'a, K, V>>
}
/// An owning iterator over a BTreeMap's entries.
pub struct MoveEntries<K, V> {
inner: AbsEntries<MoveTraversal<K, V>>
}
/// An iterator over a BTreeMap's keys.
pub type Keys<'a, K, V> = iter::Map<'static, (&'a K, &'a V), &'a K, Entries<'a, K, V>>;
/// An iterator over a BTreeMap's values.
pub type Values<'a, K, V> = iter::Map<'static, (&'a K, &'a V), &'a V, Entries<'a, K, V>>;
/// A view into a single entry in a map, which may either be vacant or occupied.
pub enum Entry<'a, K:'a, V:'a> {
/// A vacant Entry
Vacant(VacantEntry<'a, K, V>),
/// An occupied Entry
Occupied(OccupiedEntry<'a, K, V>),
}
/// A vacant Entry.
pub struct VacantEntry<'a, K:'a, V:'a> {
key: K,
stack: stack::SearchStack<'a, K, V>,
}
/// An occupied Entry.
pub struct OccupiedEntry<'a, K:'a, V:'a> {
stack: stack::SearchStack<'a, K, V>,
}
impl<K: Ord, V> BTreeMap<K, V> {
/// Makes a new empty BTreeMap with a reasonable choice for B.
#[unstable = "matches collection reform specification, waiting for dust to settle"]
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
pub fn new() -> BTreeMap<K, V> {
//FIXME(Gankro): Tune this as a function of size_of<K/V>?
BTreeMap::with_b(6)
}
/// Makes a new empty BTreeMap with the given B.
2014-10-05 09:48:38 -04:00
///
/// B cannot be less than 2.
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
pub fn with_b(b: uint) -> BTreeMap<K, V> {
assert!(b > 1, "B must be greater than 1");
BTreeMap {
length: 0,
depth: 1,
root: Node::make_leaf_root(b),
b: b,
}
}
/// Clears the map, removing all values.
///
/// # Example
///
/// ```
/// use std::collections::BTreeMap;
///
/// let mut a = BTreeMap::new();
/// a.insert(1u, "a");
/// a.clear();
/// assert!(a.is_empty());
/// ```
#[unstable = "matches collection reform specification, waiting for dust to settle"]
pub fn clear(&mut self) {
let b = self.b;
// avoid recursive destructors by manually traversing the tree
for _ in mem::replace(self, BTreeMap::with_b(b)).into_iter() {};
}
/// Deprecated: renamed to `get`.
#[deprecated = "renamed to `get`"]
pub fn find(&self, key: &K) -> Option<&V> {
self.get(key)
}
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
// Searching in a B-Tree is pretty straightforward.
//
// Start at the root. Try to find the key in the current node. If we find it, return it.
// If it's not in there, follow the edge *before* the smallest key larger than
// the search key. If no such key exists (they're *all* smaller), then just take the last
// edge in the node. If we're in a leaf and we don't find our key, then it's not
// in the tree.
/// Returns a reference to the value corresponding to the key.
///
/// The key may be any borrowed form of the map's key type, but the ordering
/// on the borrowed form *must* match the ordering on the key type.
///
/// # Example
///
/// ```
/// use std::collections::BTreeMap;
///
/// let mut map = BTreeMap::new();
/// map.insert(1u, "a");
/// assert_eq!(map.get(&1), Some(&"a"));
/// assert_eq!(map.get(&2), None);
/// ```
#[unstable = "matches collection reform specification, waiting for dust to settle"]
pub fn get<Sized? Q>(&self, key: &Q) -> Option<&V> where Q: BorrowFrom<K> + Ord {
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
let mut cur_node = &self.root;
loop {
match cur_node.search(key) {
Found(i) => return cur_node.val(i),
GoDown(i) => match cur_node.edge(i) {
None => return None,
Some(next_node) => {
cur_node = next_node;
continue;
}
}
}
}
}
/// Returns true if the map contains a value for the specified key.
///
/// The key may be any borrowed form of the map's key type, but the ordering
/// on the borrowed form *must* match the ordering on the key type.
///
/// # Example
///
/// ```
/// use std::collections::BTreeMap;
///
/// let mut map = BTreeMap::new();
/// map.insert(1u, "a");
/// assert_eq!(map.contains_key(&1), true);
/// assert_eq!(map.contains_key(&2), false);
/// ```
#[unstable = "matches collection reform specification, waiting for dust to settle"]
pub fn contains_key<Sized? Q>(&self, key: &Q) -> bool where Q: BorrowFrom<K> + Ord {
self.get(key).is_some()
}
/// Deprecated: renamed to `get_mut`.
#[deprecated = "renamed to `get_mut`"]
pub fn find_mut(&mut self, key: &K) -> Option<&mut V> {
self.get_mut(key)
}
/// Returns a mutable reference to the value corresponding to the key.
///
/// The key may be any borrowed form of the map's key type, but the ordering
/// on the borrowed form *must* match the ordering on the key type.
///
/// # Example
///
/// ```
/// use std::collections::BTreeMap;
///
/// let mut map = BTreeMap::new();
/// map.insert(1u, "a");
/// match map.get_mut(&1) {
/// Some(x) => *x = "b",
/// None => (),
/// }
/// assert_eq!(map[1], "b");
/// ```
// See `get` for implementation notes, this is basically a copy-paste with mut's added
#[unstable = "matches collection reform specification, waiting for dust to settle"]
pub fn get_mut<Sized? Q>(&mut self, key: &Q) -> Option<&mut V> where Q: BorrowFrom<K> + Ord {
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
// temp_node is a Borrowck hack for having a mutable value outlive a loop iteration
let mut temp_node = &mut self.root;
loop {
let cur_node = temp_node;
match cur_node.search(key) {
Found(i) => return cur_node.val_mut(i),
GoDown(i) => match cur_node.edge_mut(i) {
None => return None,
Some(next_node) => {
temp_node = next_node;
continue;
}
}
}
}
}
/// Deprecated: renamed to `insert`.
#[deprecated = "renamed to `insert`"]
pub fn swap(&mut self, key: K, value: V) -> Option<V> {
self.insert(key, value)
}
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
// Insertion in a B-Tree is a bit complicated.
//
// First we do the same kind of search described in `find`. But we need to maintain a stack of
// all the nodes/edges in our search path. If we find a match for the key we're trying to
// insert, just swap the vals and return the old ones. However, when we bottom out in a leaf,
// we attempt to insert our key-value pair at the same location we would want to follow another
// edge.
//
// If the node has room, then this is done in the obvious way by shifting elements. However,
// if the node itself is full, we split node into two, and give its median key-value
// pair to its parent to insert the new node with. Of course, the parent may also be
// full, and insertion can propagate until we reach the root. If we reach the root, and
// it is *also* full, then we split the root and place the two nodes under a newly made root.
//
// Note that we subtly deviate from Open Data Structures in our implementation of split.
// ODS describes inserting into the node *regardless* of its capacity, and then
// splitting *afterwards* if it happens to be overfull. However, this is inefficient.
// Instead, we split beforehand, and then insert the key-value pair into the appropriate
// result node. This has two consequences:
//
// 1) While ODS produces a left node of size B-1, and a right node of size B,
// we may potentially reverse this. However, this shouldn't effect the analysis.
//
// 2) While ODS may potentially return the pair we *just* inserted after
// the split, we will never do this. Again, this shouldn't effect the analysis.
/// Inserts a key-value pair from the map. If the key already had a value
/// present in the map, that value is returned. Otherwise, `None` is returned.
///
/// # Example
///
/// ```
/// use std::collections::BTreeMap;
///
/// let mut map = BTreeMap::new();
/// assert_eq!(map.insert(37u, "a"), None);
/// assert_eq!(map.is_empty(), false);
///
/// map.insert(37, "b");
/// assert_eq!(map.insert(37, "c"), Some("b"));
/// assert_eq!(map[37], "c");
/// ```
#[unstable = "matches collection reform specification, waiting for dust to settle"]
pub fn insert(&mut self, key: K, mut value: V) -> Option<V> {
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
// This is a stack of rawptrs to nodes paired with indices, respectively
// representing the nodes and edges of our search path. We have to store rawptrs
// because as far as Rust is concerned, we can mutate aliased data with such a
// stack. It is of course correct, but what it doesn't know is that we will only
// be popping and using these ptrs one at a time in child-to-parent order. The alternative
// to doing this is to take the Nodes from their parents. This actually makes
// borrowck *really* happy and everything is pretty smooth. However, this creates
// *tons* of pointless writes, and requires us to always walk all the way back to
// the root after an insertion, even if we only needed to change a leaf. Therefore,
// we accept this potential unsafety and complexity in the name of performance.
//
// Regardless, the actual dangerous logic is completely abstracted away from BTreeMap
// by the stack module. All it can do is immutably read nodes, and ask the search stack
// to proceed down some edge by index. This makes the search logic we'll be reusing in a
// few different methods much neater, and of course drastically improves safety.
let mut stack = stack::PartialSearchStack::new(self);
loop {
// Same basic logic as found in `find`, but with PartialSearchStack mediating the
// actual nodes for us
match stack.next().search(&key) {
Found(i) => unsafe {
// Perfect match, swap the values and return the old one
let next = stack.into_next();
mem::swap(next.unsafe_val_mut(i), &mut value);
return Some(value);
},
GoDown(i) => {
// We need to keep searching, try to get the search stack
// to go down further
stack = match stack.push(i) {
stack::Done(new_stack) => {
// We've reached a leaf, perform the insertion here
new_stack.insert(key, value);
return None;
}
stack::Grew(new_stack) => {
// We've found the subtree to insert this key/value pair in,
// keep searching
new_stack
}
};
}
}
}
}
// Deletion is the most complicated operation for a B-Tree.
//
// First we do the same kind of search described in
// `find`. But we need to maintain a stack of all the nodes/edges in our search path.
// If we don't find the key, then we just return `None` and do nothing. If we do find the
// key, we perform two operations: remove the item, and then possibly handle underflow.
//
// # removing the item
// If the node is a leaf, we just remove the item, and shift
// any items after it back to fill the hole.
//
// If the node is an internal node, we *swap* the item with the smallest item in
// in its right subtree (which must reside in a leaf), and then revert to the leaf
// case
//
// # handling underflow
// After removing an item, there may be too few items in the node. We want nodes
// to be mostly full for efficiency, although we make an exception for the root, which
// may have as few as one item. If this is the case, we may first try to steal
// an item from our left or right neighbour.
//
// To steal from the left (right) neighbour,
// we take the largest (smallest) item and child from it. We then swap the taken item
// with the item in their mutual parent that separates them, and then insert the
// parent's item and the taken child into the first (last) index of the underflowed node.
//
// However, stealing has the possibility of underflowing our neighbour. If this is the
// case, we instead *merge* with our neighbour. This of course reduces the number of
// children in the parent. Therefore, we also steal the item that separates the now
// merged nodes, and insert it into the merged node.
//
// Merging may cause the parent to underflow. If this is the case, then we must repeat
// the underflow handling process on the parent. If merging merges the last two children
// of the root, then we replace the root with the merged node.
/// Deprecated: renamed to `remove`.
#[deprecated = "renamed to `remove`"]
pub fn pop(&mut self, key: &K) -> Option<V> {
self.remove(key)
}
/// Removes a key from the map, returning the value at the key if the key
/// was previously in the map.
///
/// The key may be any borrowed form of the map's key type, but the ordering
/// on the borrowed form *must* match the ordering on the key type.
///
/// # Example
///
/// ```
/// use std::collections::BTreeMap;
///
/// let mut map = BTreeMap::new();
/// map.insert(1u, "a");
/// assert_eq!(map.remove(&1), Some("a"));
/// assert_eq!(map.remove(&1), None);
/// ```
#[unstable = "matches collection reform specification, waiting for dust to settle"]
pub fn remove<Sized? Q>(&mut self, key: &Q) -> Option<V> where Q: BorrowFrom<K> + Ord {
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
// See `swap` for a more thorough description of the stuff going on in here
let mut stack = stack::PartialSearchStack::new(self);
loop {
match stack.next().search(key) {
Found(i) => {
// Perfect match. Terminate the stack here, and remove the entry
return Some(stack.seal(i).remove());
},
GoDown(i) => {
// We need to keep searching, try to go down the next edge
stack = match stack.push(i) {
stack::Done(_) => return None, // We're at a leaf; the key isn't in here
stack::Grew(new_stack) => {
new_stack
}
};
}
}
}
}
}
/// The stack module provides a safe interface for constructing and manipulating a stack of ptrs
/// to nodes. By using this module much better safety guarantees can be made, and more search
/// boilerplate gets cut out.
mod stack {
pub use self::PushResult::*;
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
use core::prelude::*;
use super::BTreeMap;
use super::super::node::*;
use vec::Vec;
type StackItem<K, V> = (*mut Node<K, V>, uint);
type Stack<K, V> = Vec<StackItem<K, V>>;
/// A PartialSearchStack handles the construction of a search stack.
pub struct PartialSearchStack<'a, K:'a, V:'a> {
map: &'a mut BTreeMap<K, V>,
stack: Stack<K, V>,
next: *mut Node<K, V>,
}
/// A SearchStack represents a full path to an element of interest. It provides methods
/// for manipulating the element at the top of its stack.
pub struct SearchStack<'a, K:'a, V:'a> {
map: &'a mut BTreeMap<K, V>,
stack: Stack<K, V>,
top: StackItem<K, V>,
}
/// The result of asking a PartialSearchStack to push another node onto itself. Either it
/// Grew, in which case it's still Partial, or it found its last node was actually a leaf, in
/// which case it seals itself and yields a complete SearchStack.
pub enum PushResult<'a, K:'a, V:'a> {
Grew(PartialSearchStack<'a, K, V>),
Done(SearchStack<'a, K, V>),
}
impl<'a, K, V> PartialSearchStack<'a, K, V> {
/// Creates a new PartialSearchStack from a BTreeMap by initializing the stack with the
/// root of the tree.
pub fn new<'a>(map: &'a mut BTreeMap<K, V>) -> PartialSearchStack<'a, K, V> {
let depth = map.depth;
PartialSearchStack {
next: &mut map.root as *mut _,
map: map,
stack: Vec::with_capacity(depth),
}
}
/// Pushes the requested child of the stack's current top on top of the stack. If the child
/// exists, then a new PartialSearchStack is yielded. Otherwise, a full SearchStack is
/// yielded.
pub fn push(self, edge: uint) -> PushResult<'a, K, V> {
let map = self.map;
let mut stack = self.stack;
let next_ptr = self.next;
let next_node = unsafe {
&mut *next_ptr
};
let to_insert = (next_ptr, edge);
match next_node.edge_mut(edge) {
None => Done(SearchStack {
map: map,
stack: stack,
top: to_insert,
}),
Some(node) => {
stack.push(to_insert);
Grew(PartialSearchStack {
map: map,
stack: stack,
next: node as *mut _,
})
},
}
}
/// Converts the stack into a mutable reference to its top.
pub fn into_next(self) -> &'a mut Node<K, V> {
unsafe {
&mut *self.next
}
}
/// Gets the top of the stack.
pub fn next(&self) -> &Node<K, V> {
unsafe {
&*self.next
}
}
/// Converts the PartialSearchStack into a SearchStack.
pub fn seal(self, index: uint) -> SearchStack<'a, K, V> {
SearchStack {
map: self.map,
stack: self.stack,
top: (self.next as *mut _, index),
}
}
}
impl<'a, K, V> SearchStack<'a, K, V> {
/// Gets a reference to the value the stack points to.
pub fn peek(&self) -> &V {
let (node_ptr, index) = self.top;
unsafe {
(*node_ptr).val(index).unwrap()
}
}
/// Gets a mutable reference to the value the stack points to.
pub fn peek_mut(&mut self) -> &mut V {
let (node_ptr, index) = self.top;
unsafe {
(*node_ptr).val_mut(index).unwrap()
}
}
/// Converts the stack into a mutable reference to the value it points to, with a lifetime
/// tied to the original tree.
pub fn into_top(self) -> &'a mut V {
let (node_ptr, index) = self.top;
unsafe {
(*node_ptr).val_mut(index).unwrap()
}
}
/// Inserts the key and value into the top element in the stack, and if that node has to
/// split recursively inserts the split contents into the next element stack until
/// splits stop.
///
/// Assumes that the stack represents a search path from the root to a leaf.
///
/// An &mut V is returned to the inserted value, for callers that want a reference to this.
pub fn insert(self, key: K, val: V) -> &'a mut V {
unsafe {
let map = self.map;
map.length += 1;
let mut stack = self.stack;
// Insert the key and value into the leaf at the top of the stack
let (node, index) = self.top;
let (mut insertion, inserted_ptr) = {
(*node).insert_as_leaf(index, key, val)
};
loop {
match insertion {
Fit => {
// The last insertion went off without a hitch, no splits! We can stop
// inserting now.
return &mut *inserted_ptr;
}
Split(key, val, right) => match stack.pop() {
// The last insertion triggered a split, so get the next element on the
// stack to recursively insert the split node into.
None => {
// The stack was empty; we've split the root, and need to make a
// a new one. This is done in-place because we can't move the
// root out of a reference to the tree.
Node::make_internal_root(&mut map.root, map.b, key, val, right);
map.depth += 1;
return &mut *inserted_ptr;
}
Some((node, index)) => {
// The stack wasn't empty, do the insertion and recurse
insertion = (*node).insert_as_internal(index, key, val, right);
continue;
}
}
}
}
}
}
/// Removes the key and value in the top element of the stack, then handles underflows as
/// described in BTree's pop function.
pub fn remove(mut self) -> V {
// Ensure that the search stack goes to a leaf. This is necessary to perform deletion
// in a BTree. Note that this may put the tree in an inconsistent state (further
// described in leafify's comments), but this is immediately fixed by the
// removing the value we want to remove
self.leafify();
let map = self.map;
map.length -= 1;
let mut stack = self.stack;
// Remove the key-value pair from the leaf that this search stack points to.
// Then, note if the leaf is underfull, and promptly forget the leaf and its ptr
// to avoid ownership issues.
let (value, mut underflow) = unsafe {
let (leaf_ptr, index) = self.top;
let leaf = &mut *leaf_ptr;
let (_key, value) = leaf.remove_as_leaf(index);
let underflow = leaf.is_underfull();
(value, underflow)
};
loop {
match stack.pop() {
None => {
// We've reached the root, so no matter what, we're done. We manually
// access the root via the tree itself to avoid creating any dangling
// pointers.
if map.root.len() == 0 && !map.root.is_leaf() {
// We've emptied out the root, so make its only child the new root.
// If it's a leaf, we just let it become empty.
map.depth -= 1;
map.root = map.root.pop_edge().unwrap();
}
return value;
}
Some((parent_ptr, index)) => {
if underflow {
// Underflow! Handle it!
unsafe {
let parent = &mut *parent_ptr;
parent.handle_underflow(index);
underflow = parent.is_underfull();
}
} else {
// All done!
return value;
}
}
}
}
}
/// Subroutine for removal. Takes a search stack for a key that might terminate at an
/// internal node, and mutates the tree and search stack to *make* it a search stack
/// for that same key that *does* terminates at a leaf. If the mutation occurs, then this
/// leaves the tree in an inconsistent state that must be repaired by the caller by
/// removing the entry in question. Specifically the key-value pair and its successor will
/// become swapped.
fn leafify(&mut self) {
unsafe {
let (node_ptr, index) = self.top;
// First, get ptrs to the found key-value pair
let node = &mut *node_ptr;
let (key_ptr, val_ptr) = {
(node.unsafe_key_mut(index) as *mut _,
node.unsafe_val_mut(index) as *mut _)
};
// Try to go into the right subtree of the found key to find its successor
match node.edge_mut(index + 1) {
None => {
// We're a proper leaf stack, nothing to do
}
Some(mut temp_node) => {
//We're not a proper leaf stack, let's get to work.
self.stack.push((node_ptr, index + 1));
loop {
// Walk into the smallest subtree of this node
let node = temp_node;
let node_ptr = node as *mut _;
if node.is_leaf() {
// This node is a leaf, do the swap and return
self.top = (node_ptr, 0);
node.unsafe_swap(0, &mut *key_ptr, &mut *val_ptr);
break;
} else {
// This node is internal, go deeper
self.stack.push((node_ptr, 0));
temp_node = node.unsafe_edge_mut(0);
}
}
}
}
}
}
}
}
impl<K: Ord, V> FromIterator<(K, V)> for BTreeMap<K, V> {
fn from_iter<T: Iterator<(K, V)>>(iter: T) -> BTreeMap<K, V> {
let mut map = BTreeMap::new();
map.extend(iter);
map
}
}
impl<K: Ord, V> Extend<(K, V)> for BTreeMap<K, V> {
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
#[inline]
fn extend<T: Iterator<(K, V)>>(&mut self, mut iter: T) {
for (k, v) in iter {
self.insert(k, v);
}
}
}
impl<S: Writer, K: Hash<S>, V: Hash<S>> Hash<S> for BTreeMap<K, V> {
fn hash(&self, state: &mut S) {
for elt in self.iter() {
elt.hash(state);
}
}
}
impl<K: Ord, V> Default for BTreeMap<K, V> {
fn default() -> BTreeMap<K, V> {
BTreeMap::new()
}
}
impl<K: PartialEq, V: PartialEq> PartialEq for BTreeMap<K, V> {
fn eq(&self, other: &BTreeMap<K, V>) -> bool {
self.len() == other.len() &&
self.iter().zip(other.iter()).all(|(a, b)| a == b)
}
}
impl<K: Eq, V: Eq> Eq for BTreeMap<K, V> {}
impl<K: PartialOrd, V: PartialOrd> PartialOrd for BTreeMap<K, V> {
#[inline]
fn partial_cmp(&self, other: &BTreeMap<K, V>) -> Option<Ordering> {
iter::order::partial_cmp(self.iter(), other.iter())
}
}
impl<K: Ord, V: Ord> Ord for BTreeMap<K, V> {
#[inline]
fn cmp(&self, other: &BTreeMap<K, V>) -> Ordering {
iter::order::cmp(self.iter(), other.iter())
}
}
impl<K: Show, V: Show> Show for BTreeMap<K, V> {
fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
try!(write!(f, "{{"));
for (i, (k, v)) in self.iter().enumerate() {
if i != 0 { try!(write!(f, ", ")); }
try!(write!(f, "{}: {}", *k, *v));
}
write!(f, "}}")
}
}
impl<K: Ord, Sized? Q, V> Index<Q, V> for BTreeMap<K, V>
where Q: BorrowFrom<K> + Ord
{
fn index(&self, key: &Q) -> &V {
self.get(key).expect("no entry found for key")
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
}
}
impl<K: Ord, Sized? Q, V> IndexMut<Q, V> for BTreeMap<K, V>
where Q: BorrowFrom<K> + Ord
{
fn index_mut(&mut self, key: &Q) -> &mut V {
self.get_mut(key).expect("no entry found for key")
}
}
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
/// Genericises over how to get the correct type of iterator from the correct type
/// of Node ownership.
trait Traverse<N> {
fn traverse(node: N) -> Self;
}
impl<'a, K, V> Traverse<&'a Node<K, V>> for Traversal<'a, K, V> {
fn traverse(node: &'a Node<K, V>) -> Traversal<'a, K, V> {
node.iter()
}
}
impl<'a, K, V> Traverse<&'a mut Node<K, V>> for MutTraversal<'a, K, V> {
fn traverse(node: &'a mut Node<K, V>) -> MutTraversal<'a, K, V> {
node.iter_mut()
}
}
impl<K, V> Traverse<Node<K, V>> for MoveTraversal<K, V> {
fn traverse(node: Node<K, V>) -> MoveTraversal<K, V> {
node.into_iter()
}
}
/// Represents an operation to perform inside the following iterator methods.
/// This is necessary to use in `next` because we want to modify self.left inside
/// a match that borrows it. Similarly, in `next_back` for self.right. Instead, we use this
/// enum to note what we want to do, and do it after the match.
enum StackOp<T> {
Push(T),
Pop,
}
impl<K, V, E, T: Traverse<E> + DoubleEndedIterator<TraversalItem<K, V, E>>>
Iterator<(K, V)> for AbsEntries<T> {
// This function is pretty long, but only because there's a lot of cases to consider.
// Our iterator represents two search paths, left and right, to the smallest and largest
// elements we have yet to yield. lca represents the least common ancestor of these two paths,
// above-which we never walk, since everything outside it has already been consumed (or was
// never in the range to iterate).
//
// Note that the design of these iterators permits an *arbitrary* initial pair of min and max,
// making these arbitrary sub-range iterators. However the logic to construct these paths
// efficiently is fairly involved, so this is a FIXME. The sub-range iterators also wouldn't be
2014-11-06 09:32:37 -08:00
// able to accurately predict size, so those iterators can't implement ExactSizeIterator.
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
fn next(&mut self) -> Option<(K, V)> {
loop {
// We want the smallest element, so try to get the top of the left stack
let op = match self.left.back_mut() {
// The left stack is empty, so try to get the next element of the two paths
// LCAs (the left search path is currently a subpath of the right one)
None => match self.lca.next() {
// The lca has been exhausted, walk further down the right path
None => match self.right.pop_front() {
// The right path is exhausted, so we're done
None => return None,
// The right path had something, make that the new LCA
// and restart the whole process
Some(right) => {
self.lca = right;
continue;
}
},
// The lca yielded an edge, make that the new head of the left path
Some(Edge(next)) => Push(Traverse::traverse(next)),
// The lca yielded an entry, so yield that
Some(Elem(k, v)) => {
self.size -= 1;
return Some((k, v))
}
},
// The left stack wasn't empty, so continue along the node in its head
Some(iter) => match iter.next() {
// The head of the left path is empty, so Pop it off and restart the process
None => Pop,
// The head of the left path yielded an edge, so make that the new head
// of the left path
Some(Edge(next)) => Push(Traverse::traverse(next)),
// The head of the left path yielded entry, so yield that
Some(Elem(k, v)) => {
self.size -= 1;
return Some((k, v))
}
}
};
// Handle any operation on the left stack as necessary
match op {
Push(item) => { self.left.push_back(item); },
Pop => { self.left.pop_back(); },
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
}
}
}
fn size_hint(&self) -> (uint, Option<uint>) {
(self.size, Some(self.size))
}
}
impl<K, V, E, T: Traverse<E> + DoubleEndedIterator<TraversalItem<K, V, E>>>
DoubleEndedIterator<(K, V)> for AbsEntries<T> {
// next_back is totally symmetric to next
fn next_back(&mut self) -> Option<(K, V)> {
loop {
let op = match self.right.back_mut() {
None => match self.lca.next_back() {
None => match self.left.pop_front() {
None => return None,
Some(left) => {
self.lca = left;
continue;
}
},
Some(Edge(next)) => Push(Traverse::traverse(next)),
Some(Elem(k, v)) => {
self.size -= 1;
return Some((k, v))
}
},
Some(iter) => match iter.next_back() {
None => Pop,
Some(Edge(next)) => Push(Traverse::traverse(next)),
Some(Elem(k, v)) => {
self.size -= 1;
return Some((k, v))
}
}
};
match op {
Push(item) => { self.right.push_back(item); },
Pop => { self.right.pop_back(); }
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
}
}
}
}
impl<'a, K, V> Iterator<(&'a K, &'a V)> for Entries<'a, K, V> {
fn next(&mut self) -> Option<(&'a K, &'a V)> { self.inner.next() }
fn size_hint(&self) -> (uint, Option<uint>) { self.inner.size_hint() }
}
impl<'a, K, V> DoubleEndedIterator<(&'a K, &'a V)> for Entries<'a, K, V> {
fn next_back(&mut self) -> Option<(&'a K, &'a V)> { self.inner.next_back() }
}
2014-11-06 09:32:37 -08:00
impl<'a, K, V> ExactSizeIterator<(&'a K, &'a V)> for Entries<'a, K, V> {}
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
impl<'a, K, V> Iterator<(&'a K, &'a mut V)> for MutEntries<'a, K, V> {
fn next(&mut self) -> Option<(&'a K, &'a mut V)> { self.inner.next() }
fn size_hint(&self) -> (uint, Option<uint>) { self.inner.size_hint() }
}
impl<'a, K, V> DoubleEndedIterator<(&'a K, &'a mut V)> for MutEntries<'a, K, V> {
fn next_back(&mut self) -> Option<(&'a K, &'a mut V)> { self.inner.next_back() }
}
2014-11-06 09:32:37 -08:00
impl<'a, K, V> ExactSizeIterator<(&'a K, &'a mut V)> for MutEntries<'a, K, V> {}
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
impl<K, V> Iterator<(K, V)> for MoveEntries<K, V> {
fn next(&mut self) -> Option<(K, V)> { self.inner.next() }
fn size_hint(&self) -> (uint, Option<uint>) { self.inner.size_hint() }
}
impl<K, V> DoubleEndedIterator<(K, V)> for MoveEntries<K, V> {
fn next_back(&mut self) -> Option<(K, V)> { self.inner.next_back() }
}
2014-11-06 09:32:37 -08:00
impl<K, V> ExactSizeIterator<(K, V)> for MoveEntries<K, V> {}
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
impl<'a, K: Ord, V> VacantEntry<'a, K, V> {
/// Sets the value of the entry with the VacantEntry's key,
/// and returns a mutable reference to it.
pub fn set(self, value: V) -> &'a mut V {
self.stack.insert(self.key, value)
}
}
impl<'a, K: Ord, V> OccupiedEntry<'a, K, V> {
/// Gets a reference to the value in the entry.
pub fn get(&self) -> &V {
self.stack.peek()
}
/// Gets a mutable reference to the value in the entry.
pub fn get_mut(&mut self) -> &mut V {
self.stack.peek_mut()
}
/// Converts the entry into a mutable reference to its value.
pub fn into_mut(self) -> &'a mut V {
self.stack.into_top()
}
/// Sets the value of the entry with the OccupiedEntry's key,
/// and returns the entry's old value.
pub fn set(&mut self, mut value: V) -> V {
mem::swap(self.stack.peek_mut(), &mut value);
value
}
/// Takes the value of the entry out of the map, and returns it.
pub fn take(self) -> V {
self.stack.remove()
}
}
impl<K, V> BTreeMap<K, V> {
/// Gets an iterator over the entries of the map.
#[unstable = "matches collection reform specification, waiting for dust to settle"]
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
pub fn iter<'a>(&'a self) -> Entries<'a, K, V> {
let len = self.len();
Entries {
inner: AbsEntries {
lca: Traverse::traverse(&self.root),
left: RingBuf::new(),
right: RingBuf::new(),
size: len,
}
}
}
/// Gets a mutable iterator over the entries of the map.
#[unstable = "matches collection reform specification, waiting for dust to settle"]
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
pub fn iter_mut<'a>(&'a mut self) -> MutEntries<'a, K, V> {
let len = self.len();
MutEntries {
inner: AbsEntries {
lca: Traverse::traverse(&mut self.root),
left: RingBuf::new(),
right: RingBuf::new(),
size: len,
}
}
}
/// Gets an owning iterator over the entries of the map.
#[unstable = "matches collection reform specification, waiting for dust to settle"]
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
pub fn into_iter(self) -> MoveEntries<K, V> {
let len = self.len();
MoveEntries {
inner: AbsEntries {
lca: Traverse::traverse(self.root),
left: RingBuf::new(),
right: RingBuf::new(),
size: len,
}
}
}
/// Gets an iterator over the keys of the map.
#[unstable = "matches collection reform specification, waiting for dust to settle"]
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
pub fn keys<'a>(&'a self) -> Keys<'a, K, V> {
self.iter().map(|(k, _)| k)
}
/// Gets an iterator over the values of the map.
#[unstable = "matches collection reform specification, waiting for dust to settle"]
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
pub fn values<'a>(&'a self) -> Values<'a, K, V> {
self.iter().map(|(_, v)| v)
}
/// Return the number of elements in the map.
///
/// # Example
///
/// ```
/// use std::collections::BTreeMap;
///
/// let mut a = BTreeMap::new();
/// assert_eq!(a.len(), 0);
/// a.insert(1u, "a");
/// assert_eq!(a.len(), 1);
/// ```
#[unstable = "matches collection reform specification, waiting for dust to settle"]
pub fn len(&self) -> uint { self.length }
/// Return true if the map contains no elements.
///
/// # Example
///
/// ```
/// use std::collections::BTreeMap;
///
/// let mut a = BTreeMap::new();
/// assert!(a.is_empty());
/// a.insert(1u, "a");
/// assert!(!a.is_empty());
/// ```
#[unstable = "matches collection reform specification, waiting for dust to settle"]
pub fn is_empty(&self) -> bool { self.len() == 0 }
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
}
impl<K: Ord, V> BTreeMap<K, V> {
/// Gets the given key's corresponding entry in the map for in-place manipulation.
pub fn entry<'a>(&'a mut self, key: K) -> Entry<'a, K, V> {
// same basic logic of `swap` and `pop`, blended together
let mut stack = stack::PartialSearchStack::new(self);
loop {
match stack.next().search(&key) {
Found(i) => {
// Perfect match
return Occupied(OccupiedEntry {
stack: stack.seal(i)
});
},
GoDown(i) => {
stack = match stack.push(i) {
stack::Done(new_stack) => {
// Not in the tree, but we've found where it goes
return Vacant(VacantEntry {
stack: new_stack,
key: key,
});
}
stack::Grew(new_stack) => {
// We've found the subtree this key must go in
new_stack
}
};
}
}
}
}
}
#[cfg(test)]
mod test {
use std::prelude::*;
use super::{BTreeMap, Occupied, Vacant};
#[test]
fn test_basic_large() {
let mut map = BTreeMap::new();
let size = 10000u;
assert_eq!(map.len(), 0);
for i in range(0, size) {
assert_eq!(map.insert(i, 10*i), None);
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
assert_eq!(map.len(), i + 1);
}
for i in range(0, size) {
assert_eq!(map.get(&i).unwrap(), &(i*10));
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
}
for i in range(size, size*2) {
assert_eq!(map.get(&i), None);
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
}
for i in range(0, size) {
assert_eq!(map.insert(i, 100*i), Some(10*i));
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
assert_eq!(map.len(), size);
}
for i in range(0, size) {
assert_eq!(map.get(&i).unwrap(), &(i*100));
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
}
for i in range(0, size/2) {
assert_eq!(map.remove(&(i*2)), Some(i*200));
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
assert_eq!(map.len(), size - i - 1);
}
for i in range(0, size/2) {
assert_eq!(map.get(&(2*i)), None);
assert_eq!(map.get(&(2*i+1)).unwrap(), &(i*200 + 100));
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
}
for i in range(0, size/2) {
assert_eq!(map.remove(&(2*i)), None);
assert_eq!(map.remove(&(2*i+1)), Some(i*200 + 100));
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
assert_eq!(map.len(), size/2 - i - 1);
}
}
#[test]
fn test_basic_small() {
let mut map = BTreeMap::new();
assert_eq!(map.remove(&1), None);
assert_eq!(map.get(&1), None);
assert_eq!(map.insert(1u, 1u), None);
assert_eq!(map.get(&1), Some(&1));
assert_eq!(map.insert(1, 2), Some(1));
assert_eq!(map.get(&1), Some(&2));
assert_eq!(map.insert(2, 4), None);
assert_eq!(map.get(&2), Some(&4));
assert_eq!(map.remove(&1), Some(2));
assert_eq!(map.remove(&2), Some(4));
assert_eq!(map.remove(&1), None);
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
}
#[test]
fn test_iter() {
let size = 10000u;
// Forwards
let mut map: BTreeMap<uint, uint> = Vec::from_fn(size, |i| (i, i)).into_iter().collect();
{
let mut iter = map.iter();
for i in range(0, size) {
assert_eq!(iter.size_hint(), (size - i, Some(size - i)));
assert_eq!(iter.next().unwrap(), (&i, &i));
}
assert_eq!(iter.size_hint(), (0, Some(0)));
assert_eq!(iter.next(), None);
}
{
let mut iter = map.iter_mut();
for i in range(0, size) {
assert_eq!(iter.size_hint(), (size - i, Some(size - i)));
assert_eq!(iter.next().unwrap(), (&i, &mut (i + 0)));
}
assert_eq!(iter.size_hint(), (0, Some(0)));
assert_eq!(iter.next(), None);
}
{
let mut iter = map.into_iter();
for i in range(0, size) {
assert_eq!(iter.size_hint(), (size - i, Some(size - i)));
assert_eq!(iter.next().unwrap(), (i, i));
}
assert_eq!(iter.size_hint(), (0, Some(0)));
assert_eq!(iter.next(), None);
}
}
#[test]
fn test_iter_rev() {
let size = 10000u;
// Forwards
let mut map: BTreeMap<uint, uint> = Vec::from_fn(size, |i| (i, i)).into_iter().collect();
{
let mut iter = map.iter().rev();
for i in range(0, size) {
assert_eq!(iter.size_hint(), (size - i, Some(size - i)));
assert_eq!(iter.next().unwrap(), (&(size - i - 1), &(size - i - 1)));
}
assert_eq!(iter.size_hint(), (0, Some(0)));
assert_eq!(iter.next(), None);
}
{
let mut iter = map.iter_mut().rev();
for i in range(0, size) {
assert_eq!(iter.size_hint(), (size - i, Some(size - i)));
assert_eq!(iter.next().unwrap(), (&(size - i - 1), &mut(size - i - 1)));
}
assert_eq!(iter.size_hint(), (0, Some(0)));
assert_eq!(iter.next(), None);
}
{
let mut iter = map.into_iter().rev();
for i in range(0, size) {
assert_eq!(iter.size_hint(), (size - i, Some(size - i)));
assert_eq!(iter.next().unwrap(), (size - i - 1, size - i - 1));
}
assert_eq!(iter.size_hint(), (0, Some(0)));
assert_eq!(iter.next(), None);
}
}
#[test]
fn test_entry(){
let xs = [(1i, 10i), (2, 20), (3, 30), (4, 40), (5, 50), (6, 60)];
let mut map: BTreeMap<int, int> = xs.iter().map(|&x| x).collect();
// Existing key (insert)
match map.entry(1) {
Vacant(_) => unreachable!(),
Occupied(mut view) => {
assert_eq!(view.get(), &10);
assert_eq!(view.set(100), 10);
}
}
assert_eq!(map.get(&1).unwrap(), &100);
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
assert_eq!(map.len(), 6);
// Existing key (update)
match map.entry(2) {
Vacant(_) => unreachable!(),
Occupied(mut view) => {
let v = view.get_mut();
*v *= 10;
}
}
assert_eq!(map.get(&2).unwrap(), &200);
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
assert_eq!(map.len(), 6);
// Existing key (take)
match map.entry(3) {
Vacant(_) => unreachable!(),
Occupied(view) => {
assert_eq!(view.take(), 30);
}
}
assert_eq!(map.get(&3), None);
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
assert_eq!(map.len(), 5);
// Inexistent key (insert)
match map.entry(10) {
Occupied(_) => unreachable!(),
Vacant(view) => {
assert_eq!(*view.set(1000), 1000);
}
}
assert_eq!(map.get(&10).unwrap(), &1000);
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
assert_eq!(map.len(), 6);
}
}
#[cfg(test)]
mod bench {
use std::prelude::*;
use std::rand::{weak_rng, Rng};
use test::{Bencher, black_box};
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
use super::BTreeMap;
use bench::{insert_rand_n, insert_seq_n, find_rand_n, find_seq_n};
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
#[bench]
pub fn insert_rand_100(b: &mut Bencher) {
let mut m : BTreeMap<uint,uint> = BTreeMap::new();
insert_rand_n(100, &mut m, b,
|m, i| { m.insert(i, 1); },
|m, i| { m.remove(&i); });
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
}
#[bench]
pub fn insert_rand_10_000(b: &mut Bencher) {
let mut m : BTreeMap<uint,uint> = BTreeMap::new();
insert_rand_n(10_000, &mut m, b,
|m, i| { m.insert(i, 1); },
|m, i| { m.remove(&i); });
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
}
// Insert seq
#[bench]
pub fn insert_seq_100(b: &mut Bencher) {
let mut m : BTreeMap<uint,uint> = BTreeMap::new();
insert_seq_n(100, &mut m, b,
|m, i| { m.insert(i, 1); },
|m, i| { m.remove(&i); });
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
}
#[bench]
pub fn insert_seq_10_000(b: &mut Bencher) {
let mut m : BTreeMap<uint,uint> = BTreeMap::new();
insert_seq_n(10_000, &mut m, b,
|m, i| { m.insert(i, 1); },
|m, i| { m.remove(&i); });
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
}
// Find rand
#[bench]
pub fn find_rand_100(b: &mut Bencher) {
let mut m : BTreeMap<uint,uint> = BTreeMap::new();
find_rand_n(100, &mut m, b,
|m, i| { m.insert(i, 1); },
|m, i| { m.get(&i); });
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
}
#[bench]
pub fn find_rand_10_000(b: &mut Bencher) {
let mut m : BTreeMap<uint,uint> = BTreeMap::new();
find_rand_n(10_000, &mut m, b,
|m, i| { m.insert(i, 1); },
|m, i| { m.get(&i); });
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
}
// Find seq
#[bench]
pub fn find_seq_100(b: &mut Bencher) {
let mut m : BTreeMap<uint,uint> = BTreeMap::new();
find_seq_n(100, &mut m, b,
|m, i| { m.insert(i, 1); },
|m, i| { m.get(&i); });
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
}
#[bench]
pub fn find_seq_10_000(b: &mut Bencher) {
let mut m : BTreeMap<uint,uint> = BTreeMap::new();
find_seq_n(10_000, &mut m, b,
|m, i| { m.insert(i, 1); },
|m, i| { m.get(&i); });
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
}
fn bench_iter(b: &mut Bencher, size: uint) {
let mut map = BTreeMap::<uint, uint>::new();
let mut rng = weak_rng();
for _ in range(0, size) {
map.insert(rng.gen(), rng.gen());
}
b.iter(|| {
for entry in map.iter() {
black_box(entry);
}
});
}
#[bench]
pub fn iter_20(b: &mut Bencher) {
bench_iter(b, 20);
}
#[bench]
pub fn iter_1000(b: &mut Bencher) {
bench_iter(b, 1000);
}
#[bench]
pub fn iter_100000(b: &mut Bencher) {
bench_iter(b, 100000);
}
complete btree rewrite Replaces BTree with BTreeMap and BTreeSet, which are completely new implementations. BTreeMap's internal Node representation is particularly inefficient at the moment to make this first implementation easy to reason about and fairly safe. Both collections are also currently missing some of the tooling specific to sorted collections, which is planned as future work pending reform of these APIs. General implementation issues are discussed with TODOs internally Perf results on x86_64 Linux: test treemap::bench::find_rand_100 ... bench: 76 ns/iter (+/- 4) test treemap::bench::find_rand_10_000 ... bench: 163 ns/iter (+/- 6) test treemap::bench::find_seq_100 ... bench: 77 ns/iter (+/- 3) test treemap::bench::find_seq_10_000 ... bench: 115 ns/iter (+/- 1) test treemap::bench::insert_rand_100 ... bench: 111 ns/iter (+/- 1) test treemap::bench::insert_rand_10_000 ... bench: 996 ns/iter (+/- 18) test treemap::bench::insert_seq_100 ... bench: 486 ns/iter (+/- 20) test treemap::bench::insert_seq_10_000 ... bench: 800 ns/iter (+/- 15) test btree::map::bench::find_rand_100 ... bench: 74 ns/iter (+/- 4) test btree::map::bench::find_rand_10_000 ... bench: 153 ns/iter (+/- 5) test btree::map::bench::find_seq_100 ... bench: 82 ns/iter (+/- 1) test btree::map::bench::find_seq_10_000 ... bench: 108 ns/iter (+/- 0) test btree::map::bench::insert_rand_100 ... bench: 220 ns/iter (+/- 1) test btree::map::bench::insert_rand_10_000 ... bench: 620 ns/iter (+/- 16) test btree::map::bench::insert_seq_100 ... bench: 411 ns/iter (+/- 12) test btree::map::bench::insert_seq_10_000 ... bench: 534 ns/iter (+/- 14) BTreeMap still has a lot of room for optimization, but it's already beating out TreeMap on most access patterns. [breaking-change]
2014-09-16 10:49:26 -04:00
}