Struct sharded_queue::ShardedQueue
source · pub struct ShardedQueue<Item> { /* private fields */ }Implementations§
source§impl<Item> ShardedQueue<Item>
impl<Item> ShardedQueue<Item>
ShardedQueue
Why you should use ShardedQueue
ShardedQueue is currently the fastest collection which can be used
under highest concurrency and load
(among most popular solutions, like concurrent-queue,
see benchmarks in directory benches and run them with
cargo bench
)
Simple example
use std::thread::{available_parallelism};
use sharded_queue::ShardedQueue;
let max_concurrent_thread_count = available_parallelism().unwrap().get();
let sharded_queue = ShardedQueue::new(max_concurrent_thread_count);
sharded_queue.push_back(1);
let item = sharded_queue.pop_front_or_spin();Why you may want to not use ShardedQueue
-
Unlike in other concurrent queues, FIFO order is not guaranteed. While it may seem that FIFO order is guaranteed, it is not, because there can be a situation, when multiple consumers or producers triggered long resize of very large shards, all but last, then passed enough time for resize to finish, then 1 consumer or producer triggers long resize of last shard, and all other threads start to consume or produce, and eventually start spinning on last shard, without guarantee which will acquire spin lock first, so we can’t even guarantee that ShardedQueue::pop_front_or_spin will acquire lock before ShardedQueue::push_back on first attempt
-
ShardedQueue doesn’t track length, since length’s increment/decrement logic may change depending on use case, as well as logic when it goes from 1 to 0 or reverse (in some cases, like [non_blocking_mutex::NonBlockingMutex], we don’t even add action to queue when count reaches 1, but run it immediately in same thread), or even negative (to optimize some hot paths, like in some schedulers, since it is cheaper to restore count to correct state than to enforce that it can not go negative in some schedulers)
-
ShardedQueue doesn’t have many features, only necessary methods ShardedQueue::pop_front_or_spin and ShardedQueue::push_back are implemented
Design explanation
ShardedQueue is designed to be used in some schedulers and [NonBlockingMutex]
as the most efficient collection under highest
concurrently and load
(concurrent stack can’t outperform it, because, unlike queue, which
spreads pop and push contention between front and back,
stack pop-s from back and push-es to back,
which has double the contention over queue, while number of atomic increments
per pop or push is same as in queue)
ShardedQueue uses array of protected by separate Mutex-es queues-shards,
and atomically increments head_index or tail_index when pop or push happens,
and computes shard index for current operation by applying modulo operation to
head_index or tail_index
Modulo operation is optimized, knowing that
x % 2^n == x & (2^n - 1), so, as long as queue-shard count is a power of two, we can compute modulo very efficiently using formula
queue_index % queue_count == queue_index & (queue_count - 1)As long as queue-shard count is a power of two and
is greater than number of concurrent threads,
and push/pop is fast enough to not overlap multiple laps,
we have the highest possible performance.
Synchronizing underlying non-concurrent queue costs only
- 1 additional atomic increment per
pushorpop(incrementinghead_indexortail_index) - 2 additional
compare_and_swap-s(uncontended Mutex acquire and release) - 1 cheap bit operation(to get modulo)
- 1 get from queue-shard list by index
Complex example
use sharded_queue::ShardedQueue;
use std::cell::UnsafeCell;
use std::fmt::{Debug, Display, Formatter};
use std::marker::PhantomData;
use std::ops::{Deref, DerefMut};
use std::sync::atomic::{AtomicUsize, Ordering};
pub struct NonBlockingMutex<'captured_variables, State: ?Sized> {
task_count: AtomicUsize,
task_queue: ShardedQueue<Box<dyn FnOnce(MutexGuard<State>) + Send + 'captured_variables>>,
unsafe_state: UnsafeCell<State>,
}
/// [NonBlockingMutex] is needed to run actions atomically without thread blocking, or context
/// switch, or spin lock contention, or rescheduling on some scheduler
///
/// Notice that it uses [ShardedQueue] which doesn't guarantee order of retrieval, hence
/// [NonBlockingMutex] doesn't guarantee order of execution too, even of already added
/// items
impl<'captured_variables, State> NonBlockingMutex<'captured_variables, State> {
#[inline]
pub fn new(max_concurrent_thread_count: usize, state: State) -> Self {
Self {
task_count: AtomicUsize::new(0),
task_queue: ShardedQueue::new(max_concurrent_thread_count),
unsafe_state: UnsafeCell::new(state),
}
}
/// Please don't forget that order of execution is not guaranteed. Atomicity of operations is guaranteed,
/// but order can be random
#[inline]
pub fn run_if_first_or_schedule_on_first(
&self,
run_with_state: impl FnOnce(MutexGuard<State>) + Send + 'captured_variables,
) {
if self.task_count.fetch_add(1, Ordering::Acquire) != 0 {
self.task_queue.push_back(Box::new(run_with_state));
} else {
// If we acquired first lock, run should be executed immediately and run loop started
run_with_state(unsafe { MutexGuard::new(self) });
/// Note that if [`fetch_sub`] != 1
/// => some thread entered first if block in method
/// => [ShardedQueue::push_back] is guaranteed to be called
/// => [ShardedQueue::pop_front_or_spin] will not deadlock while spins until it gets item
///
/// Notice that we run action first, and only then decrement count
/// with releasing(pushing) memory changes, even if it looks otherwise
while self.task_count.fetch_sub(1, Ordering::Release) != 1 {
self.task_queue.pop_front_or_spin()(unsafe { MutexGuard::new(self) });
}
}
}
}
/// [Send], [Sync], and [MutexGuard] logic was taken from [std::sync::Mutex]
/// and [std::sync::MutexGuard]
///
/// these are the only places where `T: Send` matters; all other
/// functionality works fine on a single thread.
unsafe impl<'captured_variables, State: ?Sized + Send> Send
for NonBlockingMutex<'captured_variables, State>
{
}
unsafe impl<'captured_variables, State: ?Sized + Send> Sync
for NonBlockingMutex<'captured_variables, State>
{
}
/// Code was mostly taken from [std::sync::MutexGuard], it is expected to protect [State]
/// from moving out of synchronized loop
pub struct MutexGuard<
'captured_variables,
'non_blocking_mutex_ref,
State: ?Sized + 'non_blocking_mutex_ref,
> {
non_blocking_mutex: &'non_blocking_mutex_ref NonBlockingMutex<'captured_variables, State>,
/// Adding it to ensure that [MutexGuard] implements [Send] and [Sync] in same cases
/// as [std::sync::MutexGuard] and protects [State] from going out of synchronized
/// execution loop
///
/// todo remove when this error is no longer actual
/// negative trait bounds are not yet fully implemented; use marker types for now [E0658]
_phantom_unsend: PhantomData<std::sync::MutexGuard<'non_blocking_mutex_ref, State>>,
}
// todo uncomment when this error is no longer actual
// negative trait bounds are not yet fully implemented; use marker types for now [E0658]
// impl<'captured_variables, 'non_blocking_mutex_ref, State: ?Sized> !Send
// for MutexGuard<'captured_variables, 'non_blocking_mutex_ref, State>
// {
// }
unsafe impl<'captured_variables, 'non_blocking_mutex_ref, State: ?Sized + Sync> Sync
for MutexGuard<'captured_variables, 'non_blocking_mutex_ref, State>
{
}
impl<'captured_variables, 'non_blocking_mutex_ref, State: ?Sized>
MutexGuard<'captured_variables, 'non_blocking_mutex_ref, State>
{
unsafe fn new(
non_blocking_mutex: &'non_blocking_mutex_ref NonBlockingMutex<'captured_variables, State>,
) -> Self {
Self {
non_blocking_mutex,
_phantom_unsend: PhantomData,
}
}
}
impl<'captured_variables, 'non_blocking_mutex_ref, State: ?Sized> Deref
for MutexGuard<'captured_variables, 'non_blocking_mutex_ref, State>
{
type Target = State;
#[inline]
fn deref(&self) -> &State {
unsafe { &*self.non_blocking_mutex.unsafe_state.get() }
}
}
impl<'captured_variables, 'non_blocking_mutex_ref, State: ?Sized> DerefMut
for MutexGuard<'captured_variables, 'non_blocking_mutex_ref, State>
{
#[inline]
fn deref_mut(&mut self) -> &mut State {
unsafe { &mut *self.non_blocking_mutex.unsafe_state.get() }
}
}
impl<'captured_variables, 'non_blocking_mutex_ref, State: ?Sized + Debug> Debug
for MutexGuard<'captured_variables, 'non_blocking_mutex_ref, State>
{
#[inline]
fn fmt(&self, f: &mut Formatter<'_>) -> std::fmt::Result {
Debug::fmt(&**self, f)
}
}
impl<'captured_variables, 'non_blocking_mutex_ref, State: ?Sized + Display> Display
for MutexGuard<'captured_variables, 'non_blocking_mutex_ref, State>
{
#[inline]
fn fmt(&self, f: &mut Formatter<'_>) -> std::fmt::Result {
(**self).fmt(f)
}
}use sharded_queue::ShardedQueue;
fn is_send<T: Send>(t: T) {}
let shardedQueue: ShardedQueue<usize> = ShardedQueue::new(1);
is_send(shardedQueue);use sharded_queue::ShardedQueue;
fn is_sync<T: Sync>(t: T) {}
let shardedQueue: ShardedQueue<usize> = ShardedQueue::new(1);
is_sync(shardedQueue);use std::rc::Rc;
use sharded_queue::ShardedQueue;
fn is_send<T: Send>(t: T) {}
let shardedQueue: ShardedQueue<Rc<usize>> = ShardedQueue::new(1);
is_send(shardedQueue);use std::rc::Rc;
use sharded_queue::ShardedQueue;
fn is_sync<T: Sync>(t: T) {}
let shardedQueue: ShardedQueue<Rc<usize>> = ShardedQueue::new(1);
is_sync(shardedQueue);use std::collections::VecDeque;
fn is_send<T: Send>(t: T) {}
let vecDeque: VecDeque<usize> = VecDeque::new();
is_send(vecDeque);use std::collections::VecDeque;
fn is_sync<T: Sync>(t: T) {}
let vecDeque: VecDeque<usize> = VecDeque::new();
is_sync(vecDeque);use std::collections::VecDeque;
use std::rc::Rc;
fn is_send<T: Send>(t: T) {}
let vecDeque: VecDeque<Rc<usize>> = VecDeque::new();
is_send(vecDeque);use std::collections::VecDeque;
use std::rc::Rc;
fn is_sync<T: Sync>(t: T) {}
let vecDeque: VecDeque<Rc<usize>> = VecDeque::new();
is_sync(vecDeque);pub fn new(max_concurrent_thread_count: usize) -> Self
sourcepub fn pop_front_or_spin(&self) -> Item
pub fn pop_front_or_spin(&self) -> Item
Note that it will spin until item is added => it can spin very long if ShardedQueue::pop_front_or_spin is called without guarantee that ShardedQueue::push_back will be called