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// Copyright (c) The Diem Core Contributors
// SPDX-License-Identifier: Apache-2.0
#![forbid(unsafe_code)]
//! This module provides algorithms for accessing and updating a Merkle Accumulator structure
//! persisted in a key-value store. Note that this doesn't write to the storage directly, rather,
//! it reads from it via the `HashReader` trait and yields writes via an in memory `HashMap`.
//!
//! # Merkle Accumulator
//! Given an ever growing (append only) series of "leaf" hashes, we construct an evolving Merkle
//! Tree for which proofs of inclusion/exclusion of a leaf hash at a leaf index in a snapshot
//! of the tree (represented by root hash) can be given.
//!
//! # Leaf Nodes
//! Leaf nodes carry hash values to be stored and proved. They are only appended to the tree but
//! never deleted or updated.
//!
//! # Internal Nodes
//! A non-leaf node carries the hash value derived from both its left and right children.
//!
//! # Placeholder Nodes
//! To make sure each Leaf node has a Merkle Proof towards the root, placeholder nodes are added so
//! that along the route from a leaf to the root, each node has a sibling. Placeholder nodes have
//! the hash value `ACCUMULATOR_PLACEHOLDER_HASH`
//!
//! A placeholder node can appear as either a Leaf node or a non-Leaf node, but there is at most one
//! placeholder leaf at any time.
//!
//! # Frozen Nodes & Non-frozen Nodes
//! As leaves are added to the tree, placeholder nodes get replaced by non-placeholder nodes, and
//! when a node has all its descendants being non-placeholder, it becomes "Frozen" -- its hash value
//! won't change again in the event of new leaves being added. All leaves appended (not counting the
//! one possible placeholder leaf) are by definition Frozen.
//!
//! Other nodes, which have one or more placeholder descendants are Non-Frozen. As new elements are
//! appended to the accumulator the hash value of these nodes will change.
//!
//! # Leaf Count
//! Given a count of the number of leaves in a Merkle Accumulator it is possible to determine the
//! shape of the accumulator -- which nodes are filled and which nodes are placeholder nodes.
//!
//! Example:
//! Logical view of a Merkle Accumulator with 5 leaves:
//! ```text
//! Non-fzn
//! / \
//! / \
//! / \
//! Fzn2 Non-fzn
//! / \ / \
//! / \ / \
//! Fzn1 Fzn3 Non-fzn [Placeholder]
//! / \ / \ / \
//! L0 L1 L2 L3 L4 [Placeholder]
//! ```
//!
//! # Position and Physical Representation
//! As a Merkle Accumulator tree expands to the right and upwards, we number newly frozen nodes
//! monotonically. One way to do it is simply to use in-order index of nodes, and this is what
//! we do for the in-memory representation. We call the stated numbers identifying nodes below
//! simply "Position", and unless otherwise stated, this is the in-order position.
//!
//! For writing to disk however, we write all the children of a node before the parent.
//! Thus for disk write order, it is more convenient to use the post-order position as an index.
//! And with that we can map a Merkle Accumulator into a key-value storage: key is the post-order
//! position of a node, and the value is hash value it carries.
//!
//! We store only Frozen nodes, and generate non-Frozen nodes on the fly when accessing the tree.
//! This way, the physical representation of the tree is append-only, i.e. once written to physical
//! storage, nodes won't be either modified or deleted.
//!
//! Here is what we persist for the logical tree in the above example:
//!
//! ```text
//! Fzn2(6)
//! / \
//! / \
//! Fzn1(2) Fzn3(5)
//! / \ / \
//! L0(0) L1(1) L2(3) L3(4) L4(7)
//! ```
//!
//! When the next leaf node is persisted, the physical representation will be:
//!
//! ```text
//! Fzn2(6)
//! / \
//! / \
//! Fzn1(2) Fzn3(5) Fzn4(9)
//! / \ / \ / \
//! L0(0) L1(1) L2(3) L3(4) L4(7) L5(8)
//! ```
//!
//! The numbering corresponds to the post-order traversal of the tree.
//!
//! To think in key-value pairs:
//! ```text
//! |<-key->|<--value-->|
//! | 0 | hash_L0 |
//! | 1 | hash_L1 |
//! | 2 | hash_Fzn1 |
//! | ... | ... |
//! ```
#[cfg(any(test, feature = "fuzzing"))]
pub mod test_helpers;
use anyhow::{ensure, format_err, Result};
use diem_crypto::hash::{CryptoHash, CryptoHasher, HashValue, ACCUMULATOR_PLACEHOLDER_HASH};
use diem_types::proof::{
definition::{LeafCount, MAX_ACCUMULATOR_PROOF_DEPTH},
position::{FrozenSubTreeIterator, FrozenSubtreeSiblingIterator, Position},
AccumulatorConsistencyProof, AccumulatorProof, AccumulatorRangeProof, MerkleTreeInternalNode,
};
use mirai_annotations::*;
use std::marker::PhantomData;
/// Defines the interface between `MerkleAccumulator` and underlying storage.
pub trait HashReader {
/// Return `HashValue` carried by the node at `Position`.
fn get(&self, position: Position) -> Result<HashValue>;
}
/// A `Node` in a `MerkleAccumulator` tree is a `HashValue` at a `Position`
type Node = (Position, HashValue);
/// In this live Merkle Accumulator algorithms.
pub struct MerkleAccumulator<R, H> {
reader: PhantomData<R>,
hasher: PhantomData<H>,
}
impl<R, H> MerkleAccumulator<R, H>
where
R: HashReader,
H: CryptoHasher,
{
/// Given an existing Merkle Accumulator (represented by `num_existing_leaves` and a `reader`
/// that is able to fetch all existing frozen nodes), and a list of leaves to be appended,
/// returns the result root hash and new nodes to be frozen.
pub fn append(
reader: &R,
num_existing_leaves: LeafCount,
new_leaves: &[HashValue],
) -> Result<(HashValue, Vec<Node>)> {
MerkleAccumulatorView::<R, H>::new(reader, num_existing_leaves).append(new_leaves)
}
/// Get proof of inclusion of the leaf at `leaf_index` in this Merkle Accumulator of
/// `num_leaves` leaves in total. Siblings are read via `reader` (or generated dynamically
/// if they are non-frozen).
///
/// See [`diem_types::proof::AccumulatorProof`] for proof format.
pub fn get_proof(
reader: &R,
num_leaves: LeafCount,
leaf_index: u64,
) -> Result<AccumulatorProof<H>> {
MerkleAccumulatorView::<R, H>::new(reader, num_leaves).get_proof(leaf_index)
}
/// Gets a proof that shows the full accumulator is consistent with a smaller accumulator.
///
/// See [`diem_types::proof::AccumulatorConsistencyProof`] for proof format.
pub fn get_consistency_proof(
reader: &R,
full_acc_leaves: LeafCount,
sub_acc_leaves: LeafCount,
) -> Result<AccumulatorConsistencyProof> {
MerkleAccumulatorView::<R, H>::new(reader, full_acc_leaves)
.get_consistency_proof(sub_acc_leaves)
}
/// Gets a proof that shows a range of leaves are part of the accumulator.
///
/// See [`diem_types::proof::AccumulatorRangeProof`] for proof format.
pub fn get_range_proof(
reader: &R,
full_acc_leaves: LeafCount,
first_leaf_index: Option<u64>,
num_leaves: LeafCount,
) -> Result<AccumulatorRangeProof<H>> {
MerkleAccumulatorView::<R, H>::new(reader, full_acc_leaves)
.get_range_proof(first_leaf_index, num_leaves)
}
/// See `get_range_proof`. This is the version of it that returns `Position`s only.
pub fn get_range_proof_positions(
reader: &R,
full_acc_leaves: LeafCount,
first_leaf_index: Option<u64>,
num_leaves: LeafCount,
) -> Result<(Vec<Position>, Vec<Position>)> {
MerkleAccumulatorView::<R, H>::new(reader, full_acc_leaves)
.get_range_proof_positions(first_leaf_index, num_leaves)
}
/// From left to right, gets frozen subtree root hashes of the accumulator. For example, if the
/// accumulator has 5 leaves, `x` and `e` are returned.
/// ```text
/// root
/// / \
/// / \
/// / \
/// x o
/// / \ / \
/// / \ / \
/// o o o placeholder
/// / \ / \ / \
/// a b c d e placeholder
/// ```
pub fn get_frozen_subtree_hashes(reader: &R, num_leaves: LeafCount) -> Result<Vec<HashValue>> {
MerkleAccumulatorView::<R, H>::new(reader, num_leaves).get_frozen_subtree_hashes()
}
/// Get root hash at a specific version (hence num_leaves).
pub fn get_root_hash(reader: &R, num_leaves: LeafCount) -> Result<HashValue> {
MerkleAccumulatorView::<R, H>::new(reader, num_leaves).get_root_hash()
}
}
/// Actual implementation of Merkle Accumulator algorithms, which carries the `reader` and
/// `num_leaves` on an instance for convenience
struct MerkleAccumulatorView<'a, R, H> {
reader: &'a R,
num_leaves: LeafCount,
hasher: PhantomData<H>,
}
impl<'a, R, H> MerkleAccumulatorView<'a, R, H>
where
R: HashReader,
H: CryptoHasher,
{
fn new(reader: &'a R, num_leaves: LeafCount) -> Self {
Self {
reader,
num_leaves,
hasher: PhantomData,
}
}
/// implementation for pub interface `MerkleAccumulator::append`
fn append(&self, new_leaves: &[HashValue]) -> Result<(HashValue, Vec<Node>)> {
// Deal with the case where new_leaves is empty
if new_leaves.is_empty() {
if self.num_leaves == 0 {
return Ok((*ACCUMULATOR_PLACEHOLDER_HASH, Vec::new()));
} else {
let root_hash = self.get_hash(Position::root_from_leaf_count(self.num_leaves))?;
return Ok((root_hash, Vec::new()));
}
}
let num_new_leaves = new_leaves.len();
let last_new_leaf_count = self.num_leaves + num_new_leaves as LeafCount;
let root_level = Position::root_level_from_leaf_count(last_new_leaf_count);
let mut to_freeze = Vec::with_capacity(Self::max_to_freeze(num_new_leaves, root_level));
// Iterate over the new leaves, adding them to to_freeze and then adding any frozen parents
// when right children are encountered. This has the effect of creating frozen nodes in
// perfect post-order, which can be used as a strictly increasing append only index for
// the underlying storage.
//
// We will track newly created left siblings while iterating so we can pair them with their
// right sibling, if and when it becomes frozen. If the frozen left sibling is not created
// in this iteration, it must already exist in storage.
let mut left_siblings: Vec<(_, _)> = Vec::new();
for (leaf_offset, leaf) in new_leaves.iter().enumerate() {
let leaf_pos = Position::from_leaf_index(self.num_leaves + leaf_offset as LeafCount);
let mut hash = *leaf;
to_freeze.push((leaf_pos, hash));
let mut pos = leaf_pos;
while pos.is_right_child() {
let sibling = pos.sibling();
hash = match left_siblings.pop() {
Some((x, left_hash)) => {
assert_eq!(x, sibling);
Self::hash_internal_node(left_hash, hash)
}
None => Self::hash_internal_node(self.reader.get(sibling)?, hash),
};
pos = pos.parent();
to_freeze.push((pos, hash));
}
// The node remaining must be a left child, possibly the root of a complete binary tree.
left_siblings.push((pos, hash));
}
// Now reconstruct the final root hash by walking up to root level and adding
// placeholder hash nodes as needed on the right, and left siblings that have either
// been newly created or read from storage.
let (mut pos, mut hash) = left_siblings.pop().expect("Must have at least one node");
for _ in pos.level()..root_level as u32 {
hash = if pos.is_left_child() {
Self::hash_internal_node(hash, *ACCUMULATOR_PLACEHOLDER_HASH)
} else {
let sibling = pos.sibling();
match left_siblings.pop() {
Some((x, left_hash)) => {
assert_eq!(x, sibling);
Self::hash_internal_node(left_hash, hash)
}
None => Self::hash_internal_node(self.reader.get(sibling)?, hash),
}
};
pos = pos.parent();
}
assert!(left_siblings.is_empty());
Ok((hash, to_freeze))
}
/// upper bound of num of frozen nodes:
/// new leaves and resulting frozen internal nodes forming a complete binary subtree
/// num_new_leaves * 2 - 1 < num_new_leaves * 2
/// and the full route from root of that subtree to the accumulator root turns frozen
/// height - (log2(num_new_leaves) + 1) < height - 1 = root_level
fn max_to_freeze(num_new_leaves: usize, root_level: u32) -> usize {
precondition!(root_level as usize <= MAX_ACCUMULATOR_PROOF_DEPTH);
precondition!(num_new_leaves < (usize::max_value() / 2));
precondition!(num_new_leaves * 2 <= usize::max_value() - root_level as usize);
num_new_leaves * 2 + root_level as usize
}
fn hash_internal_node(left: HashValue, right: HashValue) -> HashValue {
MerkleTreeInternalNode::<H>::new(left, right).hash()
}
fn rightmost_leaf_index(&self) -> u64 {
(self.num_leaves - 1) as u64
}
fn get_hash(&self, position: Position) -> Result<HashValue> {
let idx = self.rightmost_leaf_index();
if position.is_placeholder(idx) {
Ok(*ACCUMULATOR_PLACEHOLDER_HASH)
} else if position.is_freezable(idx) {
self.reader.get(position)
} else {
// non-frozen non-placeholder node
Ok(Self::hash_internal_node(
self.get_hash(position.left_child())?,
self.get_hash(position.right_child())?,
))
}
}
fn get_hashes(&self, positions: &[Position]) -> Result<Vec<HashValue>> {
positions.iter().map(|p| self.get_hash(*p)).collect()
}
fn get_root_hash(&self) -> Result<HashValue> {
self.get_hash(Position::root_from_leaf_count(self.num_leaves))
}
/// implementation for pub interface `MerkleAccumulator::get_proof`
fn get_proof(&self, leaf_index: u64) -> Result<AccumulatorProof<H>> {
ensure!(
leaf_index < self.num_leaves as u64,
"invalid leaf_index {}, num_leaves {}",
leaf_index,
self.num_leaves
);
let siblings = self.get_siblings(leaf_index, |_p| true)?;
Ok(AccumulatorProof::new(siblings))
}
/// Implementation for public interface `MerkleAccumulator::get_consistency_proof`.
fn get_consistency_proof(
&self,
sub_acc_leaves: LeafCount,
) -> Result<AccumulatorConsistencyProof> {
ensure!(
sub_acc_leaves <= self.num_leaves,
"Can't get accumulator consistency proof for a version newer than the local version. \
Local next version: {}, asked next version: {}",
self.num_leaves,
sub_acc_leaves,
);
let subtrees = FrozenSubtreeSiblingIterator::new(sub_acc_leaves, self.num_leaves)
.map(|p| self.reader.get(p))
.collect::<Result<Vec<_>>>()?;
Ok(AccumulatorConsistencyProof::new(subtrees))
}
/// Implementation for public interface `MerkleAccumulator::get_range_proof`.
fn get_range_proof(
&self,
first_leaf_index: Option<u64>,
num_leaves: LeafCount,
) -> Result<AccumulatorRangeProof<H>> {
let (left_siblings, right_siblings) =
self.get_range_proof_positions(first_leaf_index, num_leaves)?;
Ok(AccumulatorRangeProof::new(
self.get_hashes(&left_siblings)?,
self.get_hashes(&right_siblings)?,
))
}
fn get_range_proof_positions(
&self,
first_leaf_index: Option<u64>,
num_leaves: LeafCount,
) -> Result<(Vec<Position>, Vec<Position>)> {
if first_leaf_index.is_none() {
ensure!(
num_leaves == 0,
"num_leaves is not zero while first_leaf_index is None.",
);
return Ok((Vec::new(), Vec::new()));
}
let first_leaf_index = first_leaf_index.expect("first_leaf_index should not be None.");
ensure!(
num_leaves > 0,
"num_leaves is zero while first_leaf_index is not None.",
);
let last_leaf_index = first_leaf_index
.checked_add(num_leaves - 1)
.ok_or_else(|| format_err!("Requesting too many leaves."))?;
ensure!(
last_leaf_index < self.num_leaves as u64,
"Invalid last_leaf_index: {}, num_leaves: {}",
last_leaf_index,
self.num_leaves,
);
let left_siblings = self.get_sibling_positions(first_leaf_index, |p| p.is_left_child());
let right_siblings = self.get_sibling_positions(last_leaf_index, |p| p.is_right_child());
Ok((left_siblings, right_siblings))
}
fn get_siblings(
&self,
leaf_index: u64,
filter: impl Fn(Position) -> bool,
) -> Result<Vec<HashValue>> {
self.get_hashes(&self.get_sibling_positions(leaf_index, filter))
}
/// Helper function to get siblings on the path from the given leaf to the root. An additional
/// filter function can be applied to filter out certain siblings.
fn get_sibling_positions(
&self,
leaf_index: u64,
filter: impl Fn(Position) -> bool,
) -> Vec<Position> {
let root_pos = Position::root_from_leaf_count(self.num_leaves);
Position::from_leaf_index(leaf_index)
.iter_ancestor_sibling()
.take(root_pos.level() as usize)
.filter(|p| filter(*p))
.collect()
}
/// Implementation for public interface `MerkleAccumulator::get_frozen_subtree_hashes`.
fn get_frozen_subtree_hashes(&self) -> Result<Vec<HashValue>> {
FrozenSubTreeIterator::new(self.num_leaves)
.map(|p| self.reader.get(p))
.collect::<Result<Vec<_>>>()
}
}
#[cfg(test)]
mod tests;