Files
neon/libs/neonart/src/lib.rs
2025-06-30 11:10:02 +02:00

584 lines
19 KiB
Rust

//! Adaptive Radix Tree (ART) implementation, with Optimistic Lock Coupling.
//!
//! The data structure is described in these two papers:
//!
//! [1] Leis, V. & Kemper, Alfons & Neumann, Thomas. (2013).
//! The adaptive radix tree: ARTful indexing for main-memory databases.
//! Proceedings - International Conference on Data Engineering. 38-49. 10.1109/ICDE.2013.6544812.
//! https://db.in.tum.de/~leis/papers/ART.pdf
//!
//! [2] Leis, Viktor & Scheibner, Florian & Kemper, Alfons & Neumann, Thomas. (2016).
//! The ART of practical synchronization.
//! 1-8. 10.1145/2933349.2933352.
//! https://db.in.tum.de/~leis/papers/artsync.pdf
//!
//! [1] describes the base data structure, and [2] describes the Optimistic Lock Coupling that we
//! use.
//!
//! The papers mention a few different variants. We have made the following choices in this
//! implementation:
//!
//! - All keys have the same length
//!
//! - Single-value leaves.
//!
//! - For collapsing inner nodes, we use the Pessimistic approach, where each inner node stores a
//! variable length "prefix", which stores the keys of all the one-way nodes which have been
//! removed. However, similar to the "hybrid" approach described in the paper, each node only has
//! space for a constant-size prefix of 8 bytes. If a node would have a longer prefix, then we
//! create create one-way nodes to store them. (There was no particular reason for this choice,
//! the "hybrid" approach described in the paper might be better.)
//!
//! - For concurrency, we use Optimistic Lock Coupling. The paper [2] also describes another method,
//! ROWEX, which generally performs better when there is contention, but that is not important
//! for use and Optimisic Lock Coupling is simpler to implement.
//!
//! ## Requirements
//!
//! This data structure is currently used for the integrated LFC, relsize and last-written LSN cache
//! in the compute communicator, part of the 'neon' Postgres extension. We have some unique
//! requirements, which is why we had to write our own. Namely:
//!
//! - The data structure has to live in fixed-sized shared memory segment. That rules out any
//! built-in Rust collections and most crates. (Except possibly with the 'allocator_api' rust
//! feature, which still nightly-only experimental as of this writing).
//!
//! - The data structure is accessed from multiple processes. Only one process updates the data
//! structure, but other processes perform reads. That rules out using built-in Rust locking
//! primitives like Mutex and RwLock, and most crates too.
//!
//! - Within the one process with write-access, multiple threads can perform updates concurrently.
//! That rules out using PostgreSQL LWLocks for the locking.
//!
//! The implementation is generic, and doesn't depend on any PostgreSQL specifics, but it has been
//! written with that usage and the above constraints in mind. Some noteworthy assumptions:
//!
//! - Contention is assumed to be rare. In the integrated cache in PostgreSQL, there's higher level
//! locking in the PostgreSQL buffer manager, which ensures that two backends should not try to
//! read / write the same page at the same time. (Prefetching can conflict with actual reads,
//! however.)
//!
//! - The keys in the integrated cache are 17 bytes long.
//!
//! ## Usage
//!
//! Because this is designed to be used as a Postgres shared memory data structure, initialization
//! happens in three stages:
//!
//! 0. A fixed area of shared memory is allocated at postmaster startup.
//!
//! 1. TreeInitStruct::new() is called to initialize it, still in Postmaster process, before any
//! other process or thread is running. It returns a TreeInitStruct, which is inherited by all
//! the processes through fork().
//!
//! 2. One process may have write-access to the struct, by calling
//! [TreeInitStruct::attach_writer]. (That process is the communicator process.)
//!
//! 3. Other processes get read-access to the struct, by calling [TreeInitStruct::attach_reader]
//!
//! "Write access" means that you can insert / update / delete values in the tree.
//!
//! NOTE: The Values stored in the tree are sometimes moved, when a leaf node fills up and a new
//! larger node needs to be allocated. The versioning and epoch-based allocator ensure that the data
//! structure stays consistent, but if the Value has interior mutability, like atomic fields,
//! updates to such fields might be lost if the leaf node is concurrently moved! If that becomes a
//! problem, the version check could be passed up to the caller, so that the caller could detect the
//! lost updates and retry the operation.
//!
//! ## Implementation
//!
//! node_ptr: Provides low-level implementations of the four different node types (eight actually,
//! since there is an Internal and Leaf variant of each)
//!
//! lock_and_version.rs: Provides an abstraction for the combined lock and version counter on each
//! node.
//!
//! node_ref.rs: The code in node_ptr.rs deals with raw pointers. node_ref.rs provides more type-safe
//! abstractions on top.
//!
//! algorithm.rs: Contains the functions to implement lookups and updates in the tree
//!
//! allocator.rs: Provides a facility to allocate memory for the tree nodes. (We must provide our
//! own abstraction for that because we need the data structure to live in a pre-allocated shared
//! memory segment).
//!
//! epoch.rs: The data structure requires that when a node is removed from the tree, it is not
//! immediately deallocated, but stays around for as long as concurrent readers might still have
//! pointers to them. This is enforced by an epoch system. This is similar to
//! e.g. crossbeam_epoch, but we couldn't use that either because it has to work across processes
//! communicating over the shared memory segment.
//!
//! ## See also
//!
//! There are some existing Rust ART implementations out there, but none of them filled all
//! the requirements:
//!
//! - https://github.com/XiangpengHao/congee
//! - https://github.com/declanvk/blart
//!
//! ## TODO
//!
//! - Removing values has not been implemented
mod algorithm;
pub mod allocator;
mod epoch;
use algorithm::RootPtr;
use algorithm::node_ptr::NodePtr;
use std::collections::VecDeque;
use std::fmt::Debug;
use std::marker::PhantomData;
use std::ptr::NonNull;
use std::sync::atomic::{AtomicBool, Ordering};
use crate::epoch::EpochPin;
#[cfg(test)]
mod tests;
use allocator::ArtAllocator;
pub use allocator::ArtMultiSlabAllocator;
pub use allocator::OutOfMemoryError;
/// Fixed-length key type.
///
pub trait Key: Debug {
const KEY_LEN: usize;
fn as_bytes(&self) -> &[u8];
}
/// Values stored in the tree
///
/// Values need to be Cloneable, because when a node "grows", the value is copied to a new node and
/// the old sticks around until all readers that might see the old value are gone.
// fixme obsolete, no longer needs Clone
pub trait Value {}
const MAX_GARBAGE: usize = 1024;
/// The root of the tree, plus other tree-wide data. This is stored in the shared memory.
pub struct Tree<V: Value> {
/// For simplicity, so that we never need to grow or shrink the root, the root node is always an
/// Internal256 node. Also, it never has a prefix (that's actually a bit wasteful, incurring one
/// indirection to every lookup)
root: RootPtr<V>,
writer_attached: AtomicBool,
epoch: epoch::EpochShared,
}
unsafe impl<V: Value + Sync> Sync for Tree<V> {}
unsafe impl<V: Value + Send> Send for Tree<V> {}
struct GarbageQueue<V>(VecDeque<(NodePtr<V>, u64)>);
unsafe impl<V: Value + Sync> Sync for GarbageQueue<V> {}
unsafe impl<V: Value + Send> Send for GarbageQueue<V> {}
impl<V> GarbageQueue<V> {
fn new() -> GarbageQueue<V> {
GarbageQueue(VecDeque::with_capacity(MAX_GARBAGE))
}
fn remember_obsolete_node(&mut self, ptr: NodePtr<V>, epoch: u64) {
self.0.push_front((ptr, epoch));
}
fn next_obsolete(&mut self, cutoff_epoch: u64) -> Option<NodePtr<V>> {
if let Some(back) = self.0.back() {
if back.1 < cutoff_epoch {
return Some(self.0.pop_back().unwrap().0);
}
}
None
}
}
/// Struct created at postmaster startup
pub struct TreeInitStruct<'t, K: Key, V: Value, A: ArtAllocator<V>> {
tree: &'t Tree<V>,
allocator: &'t A,
phantom_key: PhantomData<K>,
}
/// The worker process has a reference to this. The write operations are only safe
/// from the worker process
pub struct TreeWriteAccess<'t, K: Key, V: Value, A: ArtAllocator<V>>
where
K: Key,
V: Value,
{
tree: &'t Tree<V>,
pub allocator: &'t A,
epoch_handle: epoch::LocalHandle<'t>,
phantom_key: PhantomData<K>,
/// Obsolete nodes that cannot be recycled until their epoch expires.
garbage: spin::Mutex<GarbageQueue<V>>,
}
/// The backends have a reference to this. It cannot be used to modify the tree
pub struct TreeReadAccess<'t, K: Key, V: Value>
where
K: Key,
V: Value,
{
tree: &'t Tree<V>,
epoch_handle: epoch::LocalHandle<'t>,
phantom_key: PhantomData<K>,
}
impl<'t, K: Key, V: Value, A: ArtAllocator<V>> TreeInitStruct<'t, K, V, A> {
pub fn new(allocator: &'t A) -> TreeInitStruct<'t, K, V, A> {
let tree_ptr = allocator.alloc_tree();
let tree_ptr = NonNull::new(tree_ptr).expect("out of memory");
let init = Tree {
root: algorithm::new_root(allocator).expect("out of memory"),
writer_attached: AtomicBool::new(false),
epoch: epoch::EpochShared::new(),
};
unsafe { tree_ptr.write(init) };
TreeInitStruct {
tree: unsafe { tree_ptr.as_ref() },
allocator,
phantom_key: PhantomData,
}
}
pub fn attach_writer(self) -> TreeWriteAccess<'t, K, V, A> {
let previously_attached = self.tree.writer_attached.swap(true, Ordering::Relaxed);
if previously_attached {
panic!("writer already attached");
}
TreeWriteAccess {
tree: self.tree,
allocator: self.allocator,
phantom_key: PhantomData,
epoch_handle: self.tree.epoch.register(),
garbage: spin::Mutex::new(GarbageQueue::new()),
}
}
pub fn attach_reader(self) -> TreeReadAccess<'t, K, V> {
TreeReadAccess {
tree: self.tree,
phantom_key: PhantomData,
epoch_handle: self.tree.epoch.register(),
}
}
}
impl<'t, K: Key, V: Value, A: ArtAllocator<V>> TreeWriteAccess<'t, K, V, A> {
pub fn start_write<'g>(&'t self) -> TreeWriteGuard<'g, K, V, A>
where
't: 'g,
{
TreeWriteGuard {
tree_writer: self,
epoch_pin: self.epoch_handle.pin(),
phantom_key: PhantomData,
created_garbage: false,
}
}
pub fn start_read(&'t self) -> TreeReadGuard<'t, K, V> {
TreeReadGuard {
tree: self.tree,
epoch_pin: self.epoch_handle.pin(),
phantom_key: PhantomData,
}
}
}
impl<'t, K: Key, V: Value> TreeReadAccess<'t, K, V> {
pub fn start_read(&'t self) -> TreeReadGuard<'t, K, V> {
TreeReadGuard {
tree: self.tree,
epoch_pin: self.epoch_handle.pin(),
phantom_key: PhantomData,
}
}
}
pub struct TreeReadGuard<'e, K, V>
where
K: Key,
V: Value,
{
tree: &'e Tree<V>,
epoch_pin: EpochPin<'e>,
phantom_key: PhantomData<K>,
}
impl<'e, K: Key, V: Value> TreeReadGuard<'e, K, V> {
pub fn get(&'e self, key: &K) -> Option<&'e V> {
algorithm::search(key, self.tree.root, &self.epoch_pin)
}
}
pub struct TreeWriteGuard<'e, K, V, A>
where
K: Key,
V: Value,
A: ArtAllocator<V>,
{
tree_writer: &'e TreeWriteAccess<'e, K, V, A>,
epoch_pin: EpochPin<'e>,
phantom_key: PhantomData<K>,
created_garbage: bool,
}
pub enum UpdateAction<V> {
Nothing,
Insert(V),
Remove,
}
impl<'e, K: Key, V: Value, A: ArtAllocator<V>> TreeWriteGuard<'e, K, V, A> {
/// Get a value
pub fn get(&'e mut self, key: &K) -> Option<&'e V> {
algorithm::search(key, self.tree_writer.tree.root, &self.epoch_pin)
}
/// Insert a value
pub fn insert(self, key: &K, value: V) -> Result<bool, OutOfMemoryError> {
let mut success = None;
self.update_with_fn(key, |existing| {
if existing.is_some() {
success = Some(false);
UpdateAction::Nothing
} else {
success = Some(true);
UpdateAction::Insert(value)
}
})?;
Ok(success.expect("value_fn not called"))
}
/// Remove value. Returns true if it existed
pub fn remove(self, key: &K) -> bool {
let mut result = false;
// FIXME: It's not clear if OOM is expected while removing. It seems
// not nice, but shrinking a node can OOM. Then again, we could opt
// to not shrink a node if we cannot allocate, to live a little longer.
self.update_with_fn(key, |existing| match existing {
Some(_) => {
result = true;
UpdateAction::Remove
}
None => UpdateAction::Nothing,
})
.expect("out of memory while removing");
result
}
/// Try to remove value and return the old value.
pub fn remove_and_return(self, key: &K) -> Option<V>
where
V: Clone,
{
let mut old = None;
self.update_with_fn(key, |existing| {
old = existing.cloned();
UpdateAction::Remove
})
.expect("out of memory while removing");
old
}
/// Update key using the given function. All the other modifying operations are based on this.
///
/// The function is passed a reference to the existing value, if any. If the function
/// returns None, the value is removed from the tree (or if there was no existing value,
/// does nothing). If the function returns Some, the existing value is replaced, of if there
/// was no existing value, it is inserted. FIXME: update comment
pub fn update_with_fn<F>(mut self, key: &K, value_fn: F) -> Result<(), OutOfMemoryError>
where
F: FnOnce(Option<&V>) -> UpdateAction<V>,
{
algorithm::update_fn(key, value_fn, self.tree_writer.tree.root, &mut self)?;
if self.created_garbage {
let _ = self.collect_garbage();
}
Ok(())
}
fn remember_obsolete_node(&mut self, ptr: NodePtr<V>) {
self.tree_writer
.garbage
.lock()
.remember_obsolete_node(ptr, self.epoch_pin.epoch);
self.created_garbage = true;
}
// returns number of nodes recycled
fn collect_garbage(&self) -> usize {
self.tree_writer.tree.epoch.advance();
self.tree_writer.tree.epoch.broadcast();
let cutoff_epoch = self.tree_writer.tree.epoch.get_oldest();
let mut result = 0;
let mut garbage_queue = self.tree_writer.garbage.lock();
while let Some(ptr) = garbage_queue.next_obsolete(cutoff_epoch) {
ptr.deallocate(self.tree_writer.allocator);
result += 1;
}
result
}
}
pub struct TreeIterator<K>
where
K: Key + for<'a> From<&'a [u8]>,
{
done: bool,
pub next_key: Vec<u8>,
max_key: Option<Vec<u8>>,
phantom_key: PhantomData<K>,
}
impl<K> TreeIterator<K>
where
K: Key + for<'a> From<&'a [u8]>,
{
pub fn new_wrapping() -> TreeIterator<K> {
TreeIterator {
done: false,
next_key: vec![0; K::KEY_LEN],
max_key: None,
phantom_key: PhantomData,
}
}
pub fn new(range: &std::ops::Range<K>) -> TreeIterator<K> {
let result = TreeIterator {
done: false,
next_key: Vec::from(range.start.as_bytes()),
max_key: Some(Vec::from(range.end.as_bytes())),
phantom_key: PhantomData,
};
assert_eq!(result.next_key.len(), K::KEY_LEN);
assert_eq!(result.max_key.as_ref().unwrap().len(), K::KEY_LEN);
result
}
pub fn next<'g, V>(&mut self, read_guard: &'g TreeReadGuard<'g, K, V>) -> Option<(K, &'g V)>
where
V: Value,
{
if self.done {
return None;
}
let mut wrapped_around = false;
loop {
assert_eq!(self.next_key.len(), K::KEY_LEN);
if let Some((k, v)) =
algorithm::iter_next(&self.next_key, read_guard.tree.root, &read_guard.epoch_pin)
{
assert_eq!(k.len(), K::KEY_LEN);
assert_eq!(self.next_key.len(), K::KEY_LEN);
// Check if we reached the end of the range
if let Some(max_key) = &self.max_key {
if k.as_slice() >= max_key.as_slice() {
self.done = true;
break None;
}
}
// increment the key
self.next_key = k.clone();
increment_key(self.next_key.as_mut_slice());
let k = k.as_slice().into();
break Some((k, v));
} else {
if self.max_key.is_some() {
self.done = true;
} else {
// Start from beginning
if !wrapped_around {
for i in 0..K::KEY_LEN {
self.next_key[i] = 0;
}
wrapped_around = true;
continue;
} else {
// The tree is completely empty
// FIXME: perhaps we should remember the starting point instead.
// Currently this will scan some ranges twice.
break None;
}
}
break None;
}
}
}
}
fn increment_key(key: &mut [u8]) -> bool {
for i in (0..key.len()).rev() {
let (byte, overflow) = key[i].overflowing_add(1);
key[i] = byte;
if !overflow {
return false;
}
}
true
}
// Debugging functions
impl<'e, K: Key, V: Value + Debug, A: ArtAllocator<V>> TreeWriteGuard<'e, K, V, A> {
pub fn dump(&mut self, dst: &mut dyn std::io::Write) {
algorithm::dump_tree(self.tree_writer.tree.root, &self.epoch_pin, dst)
}
}
impl<'e, K: Key, V: Value + Debug> TreeReadGuard<'e, K, V> {
pub fn dump(&mut self, dst: &mut dyn std::io::Write) {
algorithm::dump_tree(self.tree.root, &self.epoch_pin, dst)
}
}
impl<'e, K: Key, V: Value> TreeWriteAccess<'e, K, V, ArtMultiSlabAllocator<'e, V>> {
pub fn get_statistics(&self) -> ArtTreeStatistics {
self.allocator.get_statistics();
ArtTreeStatistics {
blocks: self.allocator.inner.block_allocator.get_statistics(),
slabs: self.allocator.get_statistics(),
epoch: self.tree.epoch.get_current(),
oldest_epoch: self.tree.epoch.get_oldest(),
num_garbage: self.garbage.lock().0.len() as u64,
}
}
}
#[derive(Clone, Debug)]
pub struct ArtTreeStatistics {
pub blocks: allocator::block::BlockAllocatorStats,
pub slabs: allocator::ArtMultiSlabStats,
pub epoch: u64,
pub oldest_epoch: u64,
pub num_garbage: u64,
}