1 //! Parallel iterator types for [slices][std::slice] 2 //! 3 //! You will rarely need to interact with this module directly unless you need 4 //! to name one of the iterator types. 5 //! 6 //! [std::slice]: https://doc.rust-lang.org/stable/std/slice/ 7 8 mod mergesort; 9 mod quicksort; 10 11 mod test; 12 13 use self::mergesort::par_mergesort; 14 use self::quicksort::par_quicksort; 15 use crate::iter::plumbing::*; 16 use crate::iter::*; 17 use crate::split_producer::*; 18 use std::cmp; 19 use std::cmp::Ordering; 20 use std::fmt::{self, Debug}; 21 22 use super::math::div_round_up; 23 24 /// Parallel extensions for slices. 25 pub trait ParallelSlice<T: Sync> { 26 /// Returns a plain slice, which is used to implement the rest of the 27 /// parallel methods. as_parallel_slice(&self) -> &[T]28 fn as_parallel_slice(&self) -> &[T]; 29 30 /// Returns a parallel iterator over subslices separated by elements that 31 /// match the separator. 32 /// 33 /// # Examples 34 /// 35 /// ``` 36 /// use rayon::prelude::*; 37 /// let smallest = [1, 2, 3, 0, 2, 4, 8, 0, 3, 6, 9] 38 /// .par_split(|i| *i == 0) 39 /// .map(|numbers| numbers.iter().min().unwrap()) 40 /// .min(); 41 /// assert_eq!(Some(&1), smallest); 42 /// ``` par_split<P>(&self, separator: P) -> Split<'_, T, P> where P: Fn(&T) -> bool + Sync + Send,43 fn par_split<P>(&self, separator: P) -> Split<'_, T, P> 44 where 45 P: Fn(&T) -> bool + Sync + Send, 46 { 47 Split { 48 slice: self.as_parallel_slice(), 49 separator, 50 } 51 } 52 53 /// Returns a parallel iterator over all contiguous windows of length 54 /// `window_size`. The windows overlap. 55 /// 56 /// # Examples 57 /// 58 /// ``` 59 /// use rayon::prelude::*; 60 /// let windows: Vec<_> = [1, 2, 3].par_windows(2).collect(); 61 /// assert_eq!(vec![[1, 2], [2, 3]], windows); 62 /// ``` par_windows(&self, window_size: usize) -> Windows<'_, T>63 fn par_windows(&self, window_size: usize) -> Windows<'_, T> { 64 Windows { 65 window_size, 66 slice: self.as_parallel_slice(), 67 } 68 } 69 70 /// Returns a parallel iterator over at most `chunk_size` elements of 71 /// `self` at a time. The chunks do not overlap. 72 /// 73 /// If the number of elements in the iterator is not divisible by 74 /// `chunk_size`, the last chunk may be shorter than `chunk_size`. All 75 /// other chunks will have that exact length. 76 /// 77 /// # Examples 78 /// 79 /// ``` 80 /// use rayon::prelude::*; 81 /// let chunks: Vec<_> = [1, 2, 3, 4, 5].par_chunks(2).collect(); 82 /// assert_eq!(chunks, vec![&[1, 2][..], &[3, 4], &[5]]); 83 /// ``` par_chunks(&self, chunk_size: usize) -> Chunks<'_, T>84 fn par_chunks(&self, chunk_size: usize) -> Chunks<'_, T> { 85 assert!(chunk_size != 0, "chunk_size must not be zero"); 86 Chunks { 87 chunk_size, 88 slice: self.as_parallel_slice(), 89 } 90 } 91 92 /// Returns a parallel iterator over `chunk_size` elements of 93 /// `self` at a time. The chunks do not overlap. 94 /// 95 /// If `chunk_size` does not divide the length of the slice, then the 96 /// last up to `chunk_size-1` elements will be omitted and can be 97 /// retrieved from the remainder function of the iterator. 98 /// 99 /// # Examples 100 /// 101 /// ``` 102 /// use rayon::prelude::*; 103 /// let chunks: Vec<_> = [1, 2, 3, 4, 5].par_chunks_exact(2).collect(); 104 /// assert_eq!(chunks, vec![&[1, 2][..], &[3, 4]]); 105 /// ``` par_chunks_exact(&self, chunk_size: usize) -> ChunksExact<'_, T>106 fn par_chunks_exact(&self, chunk_size: usize) -> ChunksExact<'_, T> { 107 assert!(chunk_size != 0, "chunk_size must not be zero"); 108 let slice = self.as_parallel_slice(); 109 let rem = slice.len() % chunk_size; 110 let len = slice.len() - rem; 111 let (fst, snd) = slice.split_at(len); 112 ChunksExact { 113 chunk_size, 114 slice: fst, 115 rem: snd, 116 } 117 } 118 } 119 120 impl<T: Sync> ParallelSlice<T> for [T] { 121 #[inline] as_parallel_slice(&self) -> &[T]122 fn as_parallel_slice(&self) -> &[T] { 123 self 124 } 125 } 126 127 /// Parallel extensions for mutable slices. 128 pub trait ParallelSliceMut<T: Send> { 129 /// Returns a plain mutable slice, which is used to implement the rest of 130 /// the parallel methods. as_parallel_slice_mut(&mut self) -> &mut [T]131 fn as_parallel_slice_mut(&mut self) -> &mut [T]; 132 133 /// Returns a parallel iterator over mutable subslices separated by 134 /// elements that match the separator. 135 /// 136 /// # Examples 137 /// 138 /// ``` 139 /// use rayon::prelude::*; 140 /// let mut array = [1, 2, 3, 0, 2, 4, 8, 0, 3, 6, 9]; 141 /// array.par_split_mut(|i| *i == 0) 142 /// .for_each(|slice| slice.reverse()); 143 /// assert_eq!(array, [3, 2, 1, 0, 8, 4, 2, 0, 9, 6, 3]); 144 /// ``` par_split_mut<P>(&mut self, separator: P) -> SplitMut<'_, T, P> where P: Fn(&T) -> bool + Sync + Send,145 fn par_split_mut<P>(&mut self, separator: P) -> SplitMut<'_, T, P> 146 where 147 P: Fn(&T) -> bool + Sync + Send, 148 { 149 SplitMut { 150 slice: self.as_parallel_slice_mut(), 151 separator, 152 } 153 } 154 155 /// Returns a parallel iterator over at most `chunk_size` elements of 156 /// `self` at a time. The chunks are mutable and do not overlap. 157 /// 158 /// If the number of elements in the iterator is not divisible by 159 /// `chunk_size`, the last chunk may be shorter than `chunk_size`. All 160 /// other chunks will have that exact length. 161 /// 162 /// # Examples 163 /// 164 /// ``` 165 /// use rayon::prelude::*; 166 /// let mut array = [1, 2, 3, 4, 5]; 167 /// array.par_chunks_mut(2) 168 /// .for_each(|slice| slice.reverse()); 169 /// assert_eq!(array, [2, 1, 4, 3, 5]); 170 /// ``` par_chunks_mut(&mut self, chunk_size: usize) -> ChunksMut<'_, T>171 fn par_chunks_mut(&mut self, chunk_size: usize) -> ChunksMut<'_, T> { 172 assert!(chunk_size != 0, "chunk_size must not be zero"); 173 ChunksMut { 174 chunk_size, 175 slice: self.as_parallel_slice_mut(), 176 } 177 } 178 179 /// Returns a parallel iterator over `chunk_size` elements of 180 /// `self` at a time. The chunks are mutable and do not overlap. 181 /// 182 /// If `chunk_size` does not divide the length of the slice, then the 183 /// last up to `chunk_size-1` elements will be omitted and can be 184 /// retrieved from the remainder function of the iterator. 185 /// 186 /// # Examples 187 /// 188 /// ``` 189 /// use rayon::prelude::*; 190 /// let mut array = [1, 2, 3, 4, 5]; 191 /// array.par_chunks_exact_mut(3) 192 /// .for_each(|slice| slice.reverse()); 193 /// assert_eq!(array, [3, 2, 1, 4, 5]); 194 /// ``` par_chunks_exact_mut(&mut self, chunk_size: usize) -> ChunksExactMut<'_, T>195 fn par_chunks_exact_mut(&mut self, chunk_size: usize) -> ChunksExactMut<'_, T> { 196 assert!(chunk_size != 0, "chunk_size must not be zero"); 197 let slice = self.as_parallel_slice_mut(); 198 let rem = slice.len() % chunk_size; 199 let len = slice.len() - rem; 200 let (fst, snd) = slice.split_at_mut(len); 201 ChunksExactMut { 202 chunk_size, 203 slice: fst, 204 rem: snd, 205 } 206 } 207 208 /// Sorts the slice in parallel. 209 /// 210 /// This sort is stable (i.e. does not reorder equal elements) and `O(n log n)` worst-case. 211 /// 212 /// When applicable, unstable sorting is preferred because it is generally faster than stable 213 /// sorting and it doesn't allocate auxiliary memory. 214 /// See [`par_sort_unstable`](#method.par_sort_unstable). 215 /// 216 /// # Current implementation 217 /// 218 /// The current algorithm is an adaptive merge sort inspired by 219 /// [timsort](https://en.wikipedia.org/wiki/Timsort). 220 /// It is designed to be very fast in cases where the slice is nearly sorted, or consists of 221 /// two or more sorted sequences concatenated one after another. 222 /// 223 /// Also, it allocates temporary storage the same size as `self`, but for very short slices a 224 /// non-allocating insertion sort is used instead. 225 /// 226 /// In order to sort the slice in parallel, the slice is first divided into smaller chunks and 227 /// all chunks are sorted in parallel. Then, adjacent chunks that together form non-descending 228 /// or descending runs are concatenated. Finally, the remaining chunks are merged together using 229 /// parallel subdivision of chunks and parallel merge operation. 230 /// 231 /// # Examples 232 /// 233 /// ``` 234 /// use rayon::prelude::*; 235 /// 236 /// let mut v = [-5, 4, 1, -3, 2]; 237 /// 238 /// v.par_sort(); 239 /// assert_eq!(v, [-5, -3, 1, 2, 4]); 240 /// ``` par_sort(&mut self) where T: Ord,241 fn par_sort(&mut self) 242 where 243 T: Ord, 244 { 245 par_mergesort(self.as_parallel_slice_mut(), T::lt); 246 } 247 248 /// Sorts the slice in parallel with a comparator function. 249 /// 250 /// This sort is stable (i.e. does not reorder equal elements) and `O(n log n)` worst-case. 251 /// 252 /// When applicable, unstable sorting is preferred because it is generally faster than stable 253 /// sorting and it doesn't allocate auxiliary memory. 254 /// See [`par_sort_unstable_by`](#method.par_sort_unstable_by). 255 /// 256 /// # Current implementation 257 /// 258 /// The current algorithm is an adaptive merge sort inspired by 259 /// [timsort](https://en.wikipedia.org/wiki/Timsort). 260 /// It is designed to be very fast in cases where the slice is nearly sorted, or consists of 261 /// two or more sorted sequences concatenated one after another. 262 /// 263 /// Also, it allocates temporary storage the same size as `self`, but for very short slices a 264 /// non-allocating insertion sort is used instead. 265 /// 266 /// In order to sort the slice in parallel, the slice is first divided into smaller chunks and 267 /// all chunks are sorted in parallel. Then, adjacent chunks that together form non-descending 268 /// or descending runs are concatenated. Finally, the remaining chunks are merged together using 269 /// parallel subdivision of chunks and parallel merge operation. 270 /// 271 /// # Examples 272 /// 273 /// ``` 274 /// use rayon::prelude::*; 275 /// 276 /// let mut v = [5, 4, 1, 3, 2]; 277 /// v.par_sort_by(|a, b| a.cmp(b)); 278 /// assert_eq!(v, [1, 2, 3, 4, 5]); 279 /// 280 /// // reverse sorting 281 /// v.par_sort_by(|a, b| b.cmp(a)); 282 /// assert_eq!(v, [5, 4, 3, 2, 1]); 283 /// ``` par_sort_by<F>(&mut self, compare: F) where F: Fn(&T, &T) -> Ordering + Sync,284 fn par_sort_by<F>(&mut self, compare: F) 285 where 286 F: Fn(&T, &T) -> Ordering + Sync, 287 { 288 par_mergesort(self.as_parallel_slice_mut(), |a, b| { 289 compare(a, b) == Ordering::Less 290 }); 291 } 292 293 /// Sorts the slice in parallel with a key extraction function. 294 /// 295 /// This sort is stable (i.e. does not reorder equal elements) and `O(n log n)` worst-case. 296 /// 297 /// When applicable, unstable sorting is preferred because it is generally faster than stable 298 /// sorting and it doesn't allocate auxiliary memory. 299 /// See [`par_sort_unstable_by_key`](#method.par_sort_unstable_by_key). 300 /// 301 /// # Current implementation 302 /// 303 /// The current algorithm is an adaptive merge sort inspired by 304 /// [timsort](https://en.wikipedia.org/wiki/Timsort). 305 /// It is designed to be very fast in cases where the slice is nearly sorted, or consists of 306 /// two or more sorted sequences concatenated one after another. 307 /// 308 /// Also, it allocates temporary storage the same size as `self`, but for very short slices a 309 /// non-allocating insertion sort is used instead. 310 /// 311 /// In order to sort the slice in parallel, the slice is first divided into smaller chunks and 312 /// all chunks are sorted in parallel. Then, adjacent chunks that together form non-descending 313 /// or descending runs are concatenated. Finally, the remaining chunks are merged together using 314 /// parallel subdivision of chunks and parallel merge operation. 315 /// 316 /// # Examples 317 /// 318 /// ``` 319 /// use rayon::prelude::*; 320 /// 321 /// let mut v = [-5i32, 4, 1, -3, 2]; 322 /// 323 /// v.par_sort_by_key(|k| k.abs()); 324 /// assert_eq!(v, [1, 2, -3, 4, -5]); 325 /// ``` par_sort_by_key<B, F>(&mut self, f: F) where B: Ord, F: Fn(&T) -> B + Sync,326 fn par_sort_by_key<B, F>(&mut self, f: F) 327 where 328 B: Ord, 329 F: Fn(&T) -> B + Sync, 330 { 331 par_mergesort(self.as_parallel_slice_mut(), |a, b| f(a).lt(&f(b))); 332 } 333 334 /// Sorts the slice in parallel, but may not preserve the order of equal elements. 335 /// 336 /// This sort is unstable (i.e. may reorder equal elements), in-place (i.e. does not allocate), 337 /// and `O(n log n)` worst-case. 338 /// 339 /// # Current implementation 340 /// 341 /// The current algorithm is based on Orson Peters' [pattern-defeating quicksort][pdqsort], 342 /// which is a quicksort variant designed to be very fast on certain kinds of patterns, 343 /// sometimes achieving linear time. It is randomized but deterministic, and falls back to 344 /// heapsort on degenerate inputs. 345 /// 346 /// It is generally faster than stable sorting, except in a few special cases, e.g. when the 347 /// slice consists of several concatenated sorted sequences. 348 /// 349 /// All quicksorts work in two stages: partitioning into two halves followed by recursive 350 /// calls. The partitioning phase is sequential, but the two recursive calls are performed in 351 /// parallel. 352 /// 353 /// [pdqsort]: https://github.com/orlp/pdqsort 354 /// 355 /// # Examples 356 /// 357 /// ``` 358 /// use rayon::prelude::*; 359 /// 360 /// let mut v = [-5, 4, 1, -3, 2]; 361 /// 362 /// v.par_sort_unstable(); 363 /// assert_eq!(v, [-5, -3, 1, 2, 4]); 364 /// ``` par_sort_unstable(&mut self) where T: Ord,365 fn par_sort_unstable(&mut self) 366 where 367 T: Ord, 368 { 369 par_quicksort(self.as_parallel_slice_mut(), T::lt); 370 } 371 372 /// Sorts the slice in parallel with a comparator function, but may not preserve the order of 373 /// equal elements. 374 /// 375 /// This sort is unstable (i.e. may reorder equal elements), in-place (i.e. does not allocate), 376 /// and `O(n log n)` worst-case. 377 /// 378 /// # Current implementation 379 /// 380 /// The current algorithm is based on Orson Peters' [pattern-defeating quicksort][pdqsort], 381 /// which is a quicksort variant designed to be very fast on certain kinds of patterns, 382 /// sometimes achieving linear time. It is randomized but deterministic, and falls back to 383 /// heapsort on degenerate inputs. 384 /// 385 /// It is generally faster than stable sorting, except in a few special cases, e.g. when the 386 /// slice consists of several concatenated sorted sequences. 387 /// 388 /// All quicksorts work in two stages: partitioning into two halves followed by recursive 389 /// calls. The partitioning phase is sequential, but the two recursive calls are performed in 390 /// parallel. 391 /// 392 /// [pdqsort]: https://github.com/orlp/pdqsort 393 /// 394 /// # Examples 395 /// 396 /// ``` 397 /// use rayon::prelude::*; 398 /// 399 /// let mut v = [5, 4, 1, 3, 2]; 400 /// v.par_sort_unstable_by(|a, b| a.cmp(b)); 401 /// assert_eq!(v, [1, 2, 3, 4, 5]); 402 /// 403 /// // reverse sorting 404 /// v.par_sort_unstable_by(|a, b| b.cmp(a)); 405 /// assert_eq!(v, [5, 4, 3, 2, 1]); 406 /// ``` par_sort_unstable_by<F>(&mut self, compare: F) where F: Fn(&T, &T) -> Ordering + Sync,407 fn par_sort_unstable_by<F>(&mut self, compare: F) 408 where 409 F: Fn(&T, &T) -> Ordering + Sync, 410 { 411 par_quicksort(self.as_parallel_slice_mut(), |a, b| { 412 compare(a, b) == Ordering::Less 413 }); 414 } 415 416 /// Sorts the slice in parallel with a key extraction function, but may not preserve the order 417 /// of equal elements. 418 /// 419 /// This sort is unstable (i.e. may reorder equal elements), in-place (i.e. does not allocate), 420 /// and `O(n log n)` worst-case. 421 /// 422 /// # Current implementation 423 /// 424 /// The current algorithm is based on Orson Peters' [pattern-defeating quicksort][pdqsort], 425 /// which is a quicksort variant designed to be very fast on certain kinds of patterns, 426 /// sometimes achieving linear time. It is randomized but deterministic, and falls back to 427 /// heapsort on degenerate inputs. 428 /// 429 /// It is generally faster than stable sorting, except in a few special cases, e.g. when the 430 /// slice consists of several concatenated sorted sequences. 431 /// 432 /// All quicksorts work in two stages: partitioning into two halves followed by recursive 433 /// calls. The partitioning phase is sequential, but the two recursive calls are performed in 434 /// parallel. 435 /// 436 /// [pdqsort]: https://github.com/orlp/pdqsort 437 /// 438 /// # Examples 439 /// 440 /// ``` 441 /// use rayon::prelude::*; 442 /// 443 /// let mut v = [-5i32, 4, 1, -3, 2]; 444 /// 445 /// v.par_sort_unstable_by_key(|k| k.abs()); 446 /// assert_eq!(v, [1, 2, -3, 4, -5]); 447 /// ``` par_sort_unstable_by_key<B, F>(&mut self, f: F) where B: Ord, F: Fn(&T) -> B + Sync,448 fn par_sort_unstable_by_key<B, F>(&mut self, f: F) 449 where 450 B: Ord, 451 F: Fn(&T) -> B + Sync, 452 { 453 par_quicksort(self.as_parallel_slice_mut(), |a, b| f(a).lt(&f(b))); 454 } 455 } 456 457 impl<T: Send> ParallelSliceMut<T> for [T] { 458 #[inline] as_parallel_slice_mut(&mut self) -> &mut [T]459 fn as_parallel_slice_mut(&mut self) -> &mut [T] { 460 self 461 } 462 } 463 464 impl<'data, T: Sync + 'data> IntoParallelIterator for &'data [T] { 465 type Item = &'data T; 466 type Iter = Iter<'data, T>; 467 into_par_iter(self) -> Self::Iter468 fn into_par_iter(self) -> Self::Iter { 469 Iter { slice: self } 470 } 471 } 472 473 impl<'data, T: Sync + 'data> IntoParallelIterator for &'data Vec<T> { 474 type Item = &'data T; 475 type Iter = Iter<'data, T>; 476 into_par_iter(self) -> Self::Iter477 fn into_par_iter(self) -> Self::Iter { 478 Iter { slice: self } 479 } 480 } 481 482 impl<'data, T: Send + 'data> IntoParallelIterator for &'data mut [T] { 483 type Item = &'data mut T; 484 type Iter = IterMut<'data, T>; 485 into_par_iter(self) -> Self::Iter486 fn into_par_iter(self) -> Self::Iter { 487 IterMut { slice: self } 488 } 489 } 490 491 impl<'data, T: Send + 'data> IntoParallelIterator for &'data mut Vec<T> { 492 type Item = &'data mut T; 493 type Iter = IterMut<'data, T>; 494 into_par_iter(self) -> Self::Iter495 fn into_par_iter(self) -> Self::Iter { 496 IterMut { slice: self } 497 } 498 } 499 500 /// Parallel iterator over immutable items in a slice 501 #[derive(Debug)] 502 pub struct Iter<'data, T: Sync> { 503 slice: &'data [T], 504 } 505 506 impl<'data, T: Sync> Clone for Iter<'data, T> { clone(&self) -> Self507 fn clone(&self) -> Self { 508 Iter { ..*self } 509 } 510 } 511 512 impl<'data, T: Sync + 'data> ParallelIterator for Iter<'data, T> { 513 type Item = &'data T; 514 drive_unindexed<C>(self, consumer: C) -> C::Result where C: UnindexedConsumer<Self::Item>,515 fn drive_unindexed<C>(self, consumer: C) -> C::Result 516 where 517 C: UnindexedConsumer<Self::Item>, 518 { 519 bridge(self, consumer) 520 } 521 opt_len(&self) -> Option<usize>522 fn opt_len(&self) -> Option<usize> { 523 Some(self.len()) 524 } 525 } 526 527 impl<'data, T: Sync + 'data> IndexedParallelIterator for Iter<'data, T> { drive<C>(self, consumer: C) -> C::Result where C: Consumer<Self::Item>,528 fn drive<C>(self, consumer: C) -> C::Result 529 where 530 C: Consumer<Self::Item>, 531 { 532 bridge(self, consumer) 533 } 534 len(&self) -> usize535 fn len(&self) -> usize { 536 self.slice.len() 537 } 538 with_producer<CB>(self, callback: CB) -> CB::Output where CB: ProducerCallback<Self::Item>,539 fn with_producer<CB>(self, callback: CB) -> CB::Output 540 where 541 CB: ProducerCallback<Self::Item>, 542 { 543 callback.callback(IterProducer { slice: self.slice }) 544 } 545 } 546 547 struct IterProducer<'data, T: Sync> { 548 slice: &'data [T], 549 } 550 551 impl<'data, T: 'data + Sync> Producer for IterProducer<'data, T> { 552 type Item = &'data T; 553 type IntoIter = ::std::slice::Iter<'data, T>; 554 into_iter(self) -> Self::IntoIter555 fn into_iter(self) -> Self::IntoIter { 556 self.slice.iter() 557 } 558 split_at(self, index: usize) -> (Self, Self)559 fn split_at(self, index: usize) -> (Self, Self) { 560 let (left, right) = self.slice.split_at(index); 561 (IterProducer { slice: left }, IterProducer { slice: right }) 562 } 563 } 564 565 /// Parallel iterator over immutable non-overlapping chunks of a slice 566 #[derive(Debug)] 567 pub struct Chunks<'data, T: Sync> { 568 chunk_size: usize, 569 slice: &'data [T], 570 } 571 572 impl<'data, T: Sync> Clone for Chunks<'data, T> { clone(&self) -> Self573 fn clone(&self) -> Self { 574 Chunks { ..*self } 575 } 576 } 577 578 impl<'data, T: Sync + 'data> ParallelIterator for Chunks<'data, T> { 579 type Item = &'data [T]; 580 drive_unindexed<C>(self, consumer: C) -> C::Result where C: UnindexedConsumer<Self::Item>,581 fn drive_unindexed<C>(self, consumer: C) -> C::Result 582 where 583 C: UnindexedConsumer<Self::Item>, 584 { 585 bridge(self, consumer) 586 } 587 opt_len(&self) -> Option<usize>588 fn opt_len(&self) -> Option<usize> { 589 Some(self.len()) 590 } 591 } 592 593 impl<'data, T: Sync + 'data> IndexedParallelIterator for Chunks<'data, T> { drive<C>(self, consumer: C) -> C::Result where C: Consumer<Self::Item>,594 fn drive<C>(self, consumer: C) -> C::Result 595 where 596 C: Consumer<Self::Item>, 597 { 598 bridge(self, consumer) 599 } 600 len(&self) -> usize601 fn len(&self) -> usize { 602 div_round_up(self.slice.len(), self.chunk_size) 603 } 604 with_producer<CB>(self, callback: CB) -> CB::Output where CB: ProducerCallback<Self::Item>,605 fn with_producer<CB>(self, callback: CB) -> CB::Output 606 where 607 CB: ProducerCallback<Self::Item>, 608 { 609 callback.callback(ChunksProducer { 610 chunk_size: self.chunk_size, 611 slice: self.slice, 612 }) 613 } 614 } 615 616 struct ChunksProducer<'data, T: Sync> { 617 chunk_size: usize, 618 slice: &'data [T], 619 } 620 621 impl<'data, T: 'data + Sync> Producer for ChunksProducer<'data, T> { 622 type Item = &'data [T]; 623 type IntoIter = ::std::slice::Chunks<'data, T>; 624 into_iter(self) -> Self::IntoIter625 fn into_iter(self) -> Self::IntoIter { 626 self.slice.chunks(self.chunk_size) 627 } 628 split_at(self, index: usize) -> (Self, Self)629 fn split_at(self, index: usize) -> (Self, Self) { 630 let elem_index = cmp::min(index * self.chunk_size, self.slice.len()); 631 let (left, right) = self.slice.split_at(elem_index); 632 ( 633 ChunksProducer { 634 chunk_size: self.chunk_size, 635 slice: left, 636 }, 637 ChunksProducer { 638 chunk_size: self.chunk_size, 639 slice: right, 640 }, 641 ) 642 } 643 } 644 645 /// Parallel iterator over immutable non-overlapping chunks of a slice 646 #[derive(Debug)] 647 pub struct ChunksExact<'data, T: Sync> { 648 chunk_size: usize, 649 slice: &'data [T], 650 rem: &'data [T], 651 } 652 653 impl<'data, T: Sync> ChunksExact<'data, T> { 654 /// Return the remainder of the original slice that is not going to be 655 /// returned by the iterator. The returned slice has at most `chunk_size-1` 656 /// elements. remainder(&self) -> &'data [T]657 pub fn remainder(&self) -> &'data [T] { 658 self.rem 659 } 660 } 661 662 impl<'data, T: Sync> Clone for ChunksExact<'data, T> { clone(&self) -> Self663 fn clone(&self) -> Self { 664 ChunksExact { ..*self } 665 } 666 } 667 668 impl<'data, T: Sync + 'data> ParallelIterator for ChunksExact<'data, T> { 669 type Item = &'data [T]; 670 drive_unindexed<C>(self, consumer: C) -> C::Result where C: UnindexedConsumer<Self::Item>,671 fn drive_unindexed<C>(self, consumer: C) -> C::Result 672 where 673 C: UnindexedConsumer<Self::Item>, 674 { 675 bridge(self, consumer) 676 } 677 opt_len(&self) -> Option<usize>678 fn opt_len(&self) -> Option<usize> { 679 Some(self.len()) 680 } 681 } 682 683 impl<'data, T: Sync + 'data> IndexedParallelIterator for ChunksExact<'data, T> { drive<C>(self, consumer: C) -> C::Result where C: Consumer<Self::Item>,684 fn drive<C>(self, consumer: C) -> C::Result 685 where 686 C: Consumer<Self::Item>, 687 { 688 bridge(self, consumer) 689 } 690 len(&self) -> usize691 fn len(&self) -> usize { 692 self.slice.len() / self.chunk_size 693 } 694 with_producer<CB>(self, callback: CB) -> CB::Output where CB: ProducerCallback<Self::Item>,695 fn with_producer<CB>(self, callback: CB) -> CB::Output 696 where 697 CB: ProducerCallback<Self::Item>, 698 { 699 callback.callback(ChunksExactProducer { 700 chunk_size: self.chunk_size, 701 slice: self.slice, 702 }) 703 } 704 } 705 706 struct ChunksExactProducer<'data, T: Sync> { 707 chunk_size: usize, 708 slice: &'data [T], 709 } 710 711 impl<'data, T: 'data + Sync> Producer for ChunksExactProducer<'data, T> { 712 type Item = &'data [T]; 713 type IntoIter = ::std::slice::ChunksExact<'data, T>; 714 into_iter(self) -> Self::IntoIter715 fn into_iter(self) -> Self::IntoIter { 716 self.slice.chunks_exact(self.chunk_size) 717 } 718 split_at(self, index: usize) -> (Self, Self)719 fn split_at(self, index: usize) -> (Self, Self) { 720 let elem_index = index * self.chunk_size; 721 let (left, right) = self.slice.split_at(elem_index); 722 ( 723 ChunksExactProducer { 724 chunk_size: self.chunk_size, 725 slice: left, 726 }, 727 ChunksExactProducer { 728 chunk_size: self.chunk_size, 729 slice: right, 730 }, 731 ) 732 } 733 } 734 735 /// Parallel iterator over immutable overlapping windows of a slice 736 #[derive(Debug)] 737 pub struct Windows<'data, T: Sync> { 738 window_size: usize, 739 slice: &'data [T], 740 } 741 742 impl<'data, T: Sync> Clone for Windows<'data, T> { clone(&self) -> Self743 fn clone(&self) -> Self { 744 Windows { ..*self } 745 } 746 } 747 748 impl<'data, T: Sync + 'data> ParallelIterator for Windows<'data, T> { 749 type Item = &'data [T]; 750 drive_unindexed<C>(self, consumer: C) -> C::Result where C: UnindexedConsumer<Self::Item>,751 fn drive_unindexed<C>(self, consumer: C) -> C::Result 752 where 753 C: UnindexedConsumer<Self::Item>, 754 { 755 bridge(self, consumer) 756 } 757 opt_len(&self) -> Option<usize>758 fn opt_len(&self) -> Option<usize> { 759 Some(self.len()) 760 } 761 } 762 763 impl<'data, T: Sync + 'data> IndexedParallelIterator for Windows<'data, T> { drive<C>(self, consumer: C) -> C::Result where C: Consumer<Self::Item>,764 fn drive<C>(self, consumer: C) -> C::Result 765 where 766 C: Consumer<Self::Item>, 767 { 768 bridge(self, consumer) 769 } 770 len(&self) -> usize771 fn len(&self) -> usize { 772 assert!(self.window_size >= 1); 773 self.slice.len().saturating_sub(self.window_size - 1) 774 } 775 with_producer<CB>(self, callback: CB) -> CB::Output where CB: ProducerCallback<Self::Item>,776 fn with_producer<CB>(self, callback: CB) -> CB::Output 777 where 778 CB: ProducerCallback<Self::Item>, 779 { 780 callback.callback(WindowsProducer { 781 window_size: self.window_size, 782 slice: self.slice, 783 }) 784 } 785 } 786 787 struct WindowsProducer<'data, T: Sync> { 788 window_size: usize, 789 slice: &'data [T], 790 } 791 792 impl<'data, T: 'data + Sync> Producer for WindowsProducer<'data, T> { 793 type Item = &'data [T]; 794 type IntoIter = ::std::slice::Windows<'data, T>; 795 into_iter(self) -> Self::IntoIter796 fn into_iter(self) -> Self::IntoIter { 797 self.slice.windows(self.window_size) 798 } 799 split_at(self, index: usize) -> (Self, Self)800 fn split_at(self, index: usize) -> (Self, Self) { 801 let left_index = cmp::min(self.slice.len(), index + (self.window_size - 1)); 802 let left = &self.slice[..left_index]; 803 let right = &self.slice[index..]; 804 ( 805 WindowsProducer { 806 window_size: self.window_size, 807 slice: left, 808 }, 809 WindowsProducer { 810 window_size: self.window_size, 811 slice: right, 812 }, 813 ) 814 } 815 } 816 817 /// Parallel iterator over mutable items in a slice 818 #[derive(Debug)] 819 pub struct IterMut<'data, T: Send> { 820 slice: &'data mut [T], 821 } 822 823 impl<'data, T: Send + 'data> ParallelIterator for IterMut<'data, T> { 824 type Item = &'data mut T; 825 drive_unindexed<C>(self, consumer: C) -> C::Result where C: UnindexedConsumer<Self::Item>,826 fn drive_unindexed<C>(self, consumer: C) -> C::Result 827 where 828 C: UnindexedConsumer<Self::Item>, 829 { 830 bridge(self, consumer) 831 } 832 opt_len(&self) -> Option<usize>833 fn opt_len(&self) -> Option<usize> { 834 Some(self.len()) 835 } 836 } 837 838 impl<'data, T: Send + 'data> IndexedParallelIterator for IterMut<'data, T> { drive<C>(self, consumer: C) -> C::Result where C: Consumer<Self::Item>,839 fn drive<C>(self, consumer: C) -> C::Result 840 where 841 C: Consumer<Self::Item>, 842 { 843 bridge(self, consumer) 844 } 845 len(&self) -> usize846 fn len(&self) -> usize { 847 self.slice.len() 848 } 849 with_producer<CB>(self, callback: CB) -> CB::Output where CB: ProducerCallback<Self::Item>,850 fn with_producer<CB>(self, callback: CB) -> CB::Output 851 where 852 CB: ProducerCallback<Self::Item>, 853 { 854 callback.callback(IterMutProducer { slice: self.slice }) 855 } 856 } 857 858 struct IterMutProducer<'data, T: Send> { 859 slice: &'data mut [T], 860 } 861 862 impl<'data, T: 'data + Send> Producer for IterMutProducer<'data, T> { 863 type Item = &'data mut T; 864 type IntoIter = ::std::slice::IterMut<'data, T>; 865 into_iter(self) -> Self::IntoIter866 fn into_iter(self) -> Self::IntoIter { 867 self.slice.iter_mut() 868 } 869 split_at(self, index: usize) -> (Self, Self)870 fn split_at(self, index: usize) -> (Self, Self) { 871 let (left, right) = self.slice.split_at_mut(index); 872 ( 873 IterMutProducer { slice: left }, 874 IterMutProducer { slice: right }, 875 ) 876 } 877 } 878 879 /// Parallel iterator over mutable non-overlapping chunks of a slice 880 #[derive(Debug)] 881 pub struct ChunksMut<'data, T: Send> { 882 chunk_size: usize, 883 slice: &'data mut [T], 884 } 885 886 impl<'data, T: Send + 'data> ParallelIterator for ChunksMut<'data, T> { 887 type Item = &'data mut [T]; 888 drive_unindexed<C>(self, consumer: C) -> C::Result where C: UnindexedConsumer<Self::Item>,889 fn drive_unindexed<C>(self, consumer: C) -> C::Result 890 where 891 C: UnindexedConsumer<Self::Item>, 892 { 893 bridge(self, consumer) 894 } 895 opt_len(&self) -> Option<usize>896 fn opt_len(&self) -> Option<usize> { 897 Some(self.len()) 898 } 899 } 900 901 impl<'data, T: Send + 'data> IndexedParallelIterator for ChunksMut<'data, T> { drive<C>(self, consumer: C) -> C::Result where C: Consumer<Self::Item>,902 fn drive<C>(self, consumer: C) -> C::Result 903 where 904 C: Consumer<Self::Item>, 905 { 906 bridge(self, consumer) 907 } 908 len(&self) -> usize909 fn len(&self) -> usize { 910 div_round_up(self.slice.len(), self.chunk_size) 911 } 912 with_producer<CB>(self, callback: CB) -> CB::Output where CB: ProducerCallback<Self::Item>,913 fn with_producer<CB>(self, callback: CB) -> CB::Output 914 where 915 CB: ProducerCallback<Self::Item>, 916 { 917 callback.callback(ChunksMutProducer { 918 chunk_size: self.chunk_size, 919 slice: self.slice, 920 }) 921 } 922 } 923 924 struct ChunksMutProducer<'data, T: Send> { 925 chunk_size: usize, 926 slice: &'data mut [T], 927 } 928 929 impl<'data, T: 'data + Send> Producer for ChunksMutProducer<'data, T> { 930 type Item = &'data mut [T]; 931 type IntoIter = ::std::slice::ChunksMut<'data, T>; 932 into_iter(self) -> Self::IntoIter933 fn into_iter(self) -> Self::IntoIter { 934 self.slice.chunks_mut(self.chunk_size) 935 } 936 split_at(self, index: usize) -> (Self, Self)937 fn split_at(self, index: usize) -> (Self, Self) { 938 let elem_index = cmp::min(index * self.chunk_size, self.slice.len()); 939 let (left, right) = self.slice.split_at_mut(elem_index); 940 ( 941 ChunksMutProducer { 942 chunk_size: self.chunk_size, 943 slice: left, 944 }, 945 ChunksMutProducer { 946 chunk_size: self.chunk_size, 947 slice: right, 948 }, 949 ) 950 } 951 } 952 953 /// Parallel iterator over mutable non-overlapping chunks of a slice 954 #[derive(Debug)] 955 pub struct ChunksExactMut<'data, T: Send> { 956 chunk_size: usize, 957 slice: &'data mut [T], 958 rem: &'data mut [T], 959 } 960 961 impl<'data, T: Send> ChunksExactMut<'data, T> { 962 /// Return the remainder of the original slice that is not going to be 963 /// returned by the iterator. The returned slice has at most `chunk_size-1` 964 /// elements. 965 /// 966 /// Note that this has to consume `self` to return the original lifetime of 967 /// the data, which prevents this from actually being used as a parallel 968 /// iterator since that also consumes. This method is provided for parity 969 /// with `std::iter::ChunksExactMut`, but consider calling `remainder()` or 970 /// `take_remainder()` as alternatives. into_remainder(self) -> &'data mut [T]971 pub fn into_remainder(self) -> &'data mut [T] { 972 self.rem 973 } 974 975 /// Return the remainder of the original slice that is not going to be 976 /// returned by the iterator. The returned slice has at most `chunk_size-1` 977 /// elements. 978 /// 979 /// Consider `take_remainder()` if you need access to the data with its 980 /// original lifetime, rather than borrowing through `&mut self` here. remainder(&mut self) -> &mut [T]981 pub fn remainder(&mut self) -> &mut [T] { 982 self.rem 983 } 984 985 /// Return the remainder of the original slice that is not going to be 986 /// returned by the iterator. The returned slice has at most `chunk_size-1` 987 /// elements. Subsequent calls will return an empty slice. take_remainder(&mut self) -> &'data mut [T]988 pub fn take_remainder(&mut self) -> &'data mut [T] { 989 std::mem::replace(&mut self.rem, &mut []) 990 } 991 } 992 993 impl<'data, T: Send + 'data> ParallelIterator for ChunksExactMut<'data, T> { 994 type Item = &'data mut [T]; 995 drive_unindexed<C>(self, consumer: C) -> C::Result where C: UnindexedConsumer<Self::Item>,996 fn drive_unindexed<C>(self, consumer: C) -> C::Result 997 where 998 C: UnindexedConsumer<Self::Item>, 999 { 1000 bridge(self, consumer) 1001 } 1002 opt_len(&self) -> Option<usize>1003 fn opt_len(&self) -> Option<usize> { 1004 Some(self.len()) 1005 } 1006 } 1007 1008 impl<'data, T: Send + 'data> IndexedParallelIterator for ChunksExactMut<'data, T> { drive<C>(self, consumer: C) -> C::Result where C: Consumer<Self::Item>,1009 fn drive<C>(self, consumer: C) -> C::Result 1010 where 1011 C: Consumer<Self::Item>, 1012 { 1013 bridge(self, consumer) 1014 } 1015 len(&self) -> usize1016 fn len(&self) -> usize { 1017 self.slice.len() / self.chunk_size 1018 } 1019 with_producer<CB>(self, callback: CB) -> CB::Output where CB: ProducerCallback<Self::Item>,1020 fn with_producer<CB>(self, callback: CB) -> CB::Output 1021 where 1022 CB: ProducerCallback<Self::Item>, 1023 { 1024 callback.callback(ChunksExactMutProducer { 1025 chunk_size: self.chunk_size, 1026 slice: self.slice, 1027 }) 1028 } 1029 } 1030 1031 struct ChunksExactMutProducer<'data, T: Send> { 1032 chunk_size: usize, 1033 slice: &'data mut [T], 1034 } 1035 1036 impl<'data, T: 'data + Send> Producer for ChunksExactMutProducer<'data, T> { 1037 type Item = &'data mut [T]; 1038 type IntoIter = ::std::slice::ChunksExactMut<'data, T>; 1039 into_iter(self) -> Self::IntoIter1040 fn into_iter(self) -> Self::IntoIter { 1041 self.slice.chunks_exact_mut(self.chunk_size) 1042 } 1043 split_at(self, index: usize) -> (Self, Self)1044 fn split_at(self, index: usize) -> (Self, Self) { 1045 let elem_index = index * self.chunk_size; 1046 let (left, right) = self.slice.split_at_mut(elem_index); 1047 ( 1048 ChunksExactMutProducer { 1049 chunk_size: self.chunk_size, 1050 slice: left, 1051 }, 1052 ChunksExactMutProducer { 1053 chunk_size: self.chunk_size, 1054 slice: right, 1055 }, 1056 ) 1057 } 1058 } 1059 1060 /// Parallel iterator over slices separated by a predicate 1061 pub struct Split<'data, T, P> { 1062 slice: &'data [T], 1063 separator: P, 1064 } 1065 1066 impl<'data, T, P: Clone> Clone for Split<'data, T, P> { clone(&self) -> Self1067 fn clone(&self) -> Self { 1068 Split { 1069 separator: self.separator.clone(), 1070 ..*self 1071 } 1072 } 1073 } 1074 1075 impl<'data, T: Debug, P> Debug for Split<'data, T, P> { fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result1076 fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result { 1077 f.debug_struct("Split").field("slice", &self.slice).finish() 1078 } 1079 } 1080 1081 impl<'data, T, P> ParallelIterator for Split<'data, T, P> 1082 where 1083 P: Fn(&T) -> bool + Sync + Send, 1084 T: Sync, 1085 { 1086 type Item = &'data [T]; 1087 drive_unindexed<C>(self, consumer: C) -> C::Result where C: UnindexedConsumer<Self::Item>,1088 fn drive_unindexed<C>(self, consumer: C) -> C::Result 1089 where 1090 C: UnindexedConsumer<Self::Item>, 1091 { 1092 let producer = SplitProducer::new(self.slice, &self.separator); 1093 bridge_unindexed(producer, consumer) 1094 } 1095 } 1096 1097 /// Implement support for `SplitProducer`. 1098 impl<'data, T, P> Fissile<P> for &'data [T] 1099 where 1100 P: Fn(&T) -> bool, 1101 { length(&self) -> usize1102 fn length(&self) -> usize { 1103 self.len() 1104 } 1105 midpoint(&self, end: usize) -> usize1106 fn midpoint(&self, end: usize) -> usize { 1107 end / 2 1108 } 1109 find(&self, separator: &P, start: usize, end: usize) -> Option<usize>1110 fn find(&self, separator: &P, start: usize, end: usize) -> Option<usize> { 1111 self[start..end].iter().position(separator) 1112 } 1113 rfind(&self, separator: &P, end: usize) -> Option<usize>1114 fn rfind(&self, separator: &P, end: usize) -> Option<usize> { 1115 self[..end].iter().rposition(separator) 1116 } 1117 split_once(self, index: usize) -> (Self, Self)1118 fn split_once(self, index: usize) -> (Self, Self) { 1119 let (left, right) = self.split_at(index); 1120 (left, &right[1..]) // skip the separator 1121 } 1122 fold_splits<F>(self, separator: &P, folder: F, skip_last: bool) -> F where F: Folder<Self>, Self: Send,1123 fn fold_splits<F>(self, separator: &P, folder: F, skip_last: bool) -> F 1124 where 1125 F: Folder<Self>, 1126 Self: Send, 1127 { 1128 let mut split = self.split(separator); 1129 if skip_last { 1130 split.next_back(); 1131 } 1132 folder.consume_iter(split) 1133 } 1134 } 1135 1136 /// Parallel iterator over mutable slices separated by a predicate 1137 pub struct SplitMut<'data, T, P> { 1138 slice: &'data mut [T], 1139 separator: P, 1140 } 1141 1142 impl<'data, T: Debug, P> Debug for SplitMut<'data, T, P> { fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result1143 fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result { 1144 f.debug_struct("SplitMut") 1145 .field("slice", &self.slice) 1146 .finish() 1147 } 1148 } 1149 1150 impl<'data, T, P> ParallelIterator for SplitMut<'data, T, P> 1151 where 1152 P: Fn(&T) -> bool + Sync + Send, 1153 T: Send, 1154 { 1155 type Item = &'data mut [T]; 1156 drive_unindexed<C>(self, consumer: C) -> C::Result where C: UnindexedConsumer<Self::Item>,1157 fn drive_unindexed<C>(self, consumer: C) -> C::Result 1158 where 1159 C: UnindexedConsumer<Self::Item>, 1160 { 1161 let producer = SplitProducer::new(self.slice, &self.separator); 1162 bridge_unindexed(producer, consumer) 1163 } 1164 } 1165 1166 /// Implement support for `SplitProducer`. 1167 impl<'data, T, P> Fissile<P> for &'data mut [T] 1168 where 1169 P: Fn(&T) -> bool, 1170 { length(&self) -> usize1171 fn length(&self) -> usize { 1172 self.len() 1173 } 1174 midpoint(&self, end: usize) -> usize1175 fn midpoint(&self, end: usize) -> usize { 1176 end / 2 1177 } 1178 find(&self, separator: &P, start: usize, end: usize) -> Option<usize>1179 fn find(&self, separator: &P, start: usize, end: usize) -> Option<usize> { 1180 self[start..end].iter().position(separator) 1181 } 1182 rfind(&self, separator: &P, end: usize) -> Option<usize>1183 fn rfind(&self, separator: &P, end: usize) -> Option<usize> { 1184 self[..end].iter().rposition(separator) 1185 } 1186 split_once(self, index: usize) -> (Self, Self)1187 fn split_once(self, index: usize) -> (Self, Self) { 1188 let (left, right) = self.split_at_mut(index); 1189 (left, &mut right[1..]) // skip the separator 1190 } 1191 fold_splits<F>(self, separator: &P, folder: F, skip_last: bool) -> F where F: Folder<Self>, Self: Send,1192 fn fold_splits<F>(self, separator: &P, folder: F, skip_last: bool) -> F 1193 where 1194 F: Folder<Self>, 1195 Self: Send, 1196 { 1197 let mut split = self.split_mut(separator); 1198 if skip_last { 1199 split.next_back(); 1200 } 1201 folder.consume_iter(split) 1202 } 1203 } 1204