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Table+Model doc #22

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lx merged 4 commits from doc/model into master 2020-12-12 16:08:33 +00:00
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2 changed files with 179 additions and 11 deletions
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3
src/model/bucket_table.rs
View file

@ -8,6 +8,9 @@ use garage_util::error::Error;
use crate::key_table::PermissionSet;
// We import the same file but in its version 0.1.0.
// We can then access v0.1.0 data structures.
// We use them to perform migrations.
use model010::bucket_table as prev;
#[derive(PartialEq, Clone, Debug, Serialize, Deserialize)]

187
src/table/crdt.rs
View file

@ -1,11 +1,48 @@
//! This package provides a simple implementation of conflict-free replicated data types (CRDTs)
//!
//! CRDTs are a type of data structures that do not require coordination. In other words, we can
//! edit them in parallel, we will always find a way to merge it.
//!
//! A general example is a counter. Its initial value is 0. Alice and Bob get a copy of the
//! counter. Alice does +1 on her copy, she reads 1. Bob does +3 on his copy, he reads 3. Now,
//! it is easy to merge their counters, order does not count: we always get 4.
//!
//! Learn more about CRDT [on Wikipedia](https://en.wikipedia.org/wiki/Conflict-free_replicated_data_type)
use serde::{Deserialize, Serialize};
use garage_util::data::*;
/// Definition of a CRDT - all CRDT Rust types implement this.
///
/// A CRDT is defined as a merge operator that respects a certain set of axioms.
///
/// In particular, the merge operator must be commutative, associative,
/// idempotent, and monotonic.
/// In other words, if `a`, `b` and `c` are CRDTs, and `⊔` denotes the merge operator,
/// the following axioms must apply:
///
/// ```text
/// a ⊔ b = b ⊔ a (commutativity)
/// (a ⊔ b) ⊔ c = a ⊔ (b ⊔ c) (associativity)
/// (a ⊔ b) ⊔ b = a ⊔ b (idempotence)
/// ```
///
/// Moreover, the relationship `≥` defined by `a ≥ b ⇔ ∃c. a = b ⊔ c` must be a partial order.
/// This implies a few properties such as: if `a ⊔ b ≠ a`, then there is no `c` such that `(a ⊔ b) ⊔ c = a`,
/// as this would imply a cycle in the partial order.
pub trait CRDT {
/// Merge the two datastructures according to the CRDT rules.
/// `self` is modified to contain the merged CRDT value. `other` is not modified.
///
/// # Arguments
///
/// * `other` - the other CRDT we wish to merge with
fn merge(&mut self, other: &Self);
}
/// All types that implement `Ord` (a total order) also implement a trivial CRDT
/// defined by the merge rule: `a ⊔ b = max(a, b)`.
impl<T> CRDT for T
where
T: Ord + Clone,
@ -19,6 +56,37 @@ where
// ---- LWW Register ----
/// Last Write Win (LWW)
///
/// An LWW CRDT associates a timestamp with a value, in order to implement a
/// time-based reconciliation rule: the most recent write wins.
/// For completeness, the LWW reconciliation rule must also be defined for two LWW CRDTs
/// with the same timestamp but different values.
///
/// In our case, we add the constraint that the value that is wrapped inside the LWW CRDT must
/// itself be a CRDT: in the case when the timestamp does not allow us to decide on which value to
/// keep, the merge rule of the inner CRDT is applied on the wrapped values. (Note that all types
/// that implement the `Ord` trait get a default CRDT implemetnation that keeps the maximum value.
/// This enables us to use LWW directly with primitive data types such as numbers or strings. It is
/// generally desirable in this case to never explicitly produce LWW values with the same timestamp
/// but different inner values, as the rule to keep the maximum value isn't generally the desired
/// semantics.)
///
/// As multiple computers clocks are always desynchronized,
/// when operations are close enough, it is equivalent to
/// take one copy and drop the other one.
///
/// Given that clocks are not too desynchronized, this assumption
/// is enough for most cases, as there is few chance that two humans
/// coordonate themself faster than the time difference between two NTP servers.
///
/// As a more concret example, let's suppose you want to upload a file
/// with the same key (path) in the same bucket at the very same time.
/// For each request, the file will be timestamped by the receiving server
/// and may differ from what you observed with your atomic clock!
///
/// This scheme is used by AWS S3 or Soundcloud and often without knowing
/// in entreprise when reconciliating databases with ad-hoc scripts.
#[derive(Clone, Debug, Serialize, Deserialize, PartialEq)]
pub struct LWW<T> {
ts: u64,
@ -29,22 +97,55 @@ impl<T> LWW<T>
where
T: CRDT,
{
/// Creates a new CRDT
///
/// CRDT's internal timestamp is set with current node's clock.
pub fn new(value: T) -> Self {
Self {
ts: now_msec(),
v: value,
}
}
/// Build a new CRDT from a previous non-compatible one
///
/// Compared to new, the CRDT's timestamp is not set to now
/// but must be set to the previous, non-compatible, CRDT's timestamp.
pub fn migrate_from_raw(ts: u64, value: T) -> Self {
Self { ts, v: value }
}
/// Update the LWW CRDT while keeping some causal ordering.
///
/// The timestamp of the LWW CRDT is updated to be the current node's clock
/// at time of update, or the previous timestamp + 1 if that's bigger,
/// so that the new timestamp is always strictly larger than the previous one.
/// This ensures that merging the update with the old value will result in keeping
/// the updated value.
pub fn update(&mut self, new_value: T) {
self.ts = std::cmp::max(self.ts + 1, now_msec());
self.v = new_value;
}
/// Get the CRDT value
pub fn get(&self) -> &T {
&self.v
}
/// Get a mutable reference to the CRDT's value
///
/// This is usefull to mutate the inside value without changing the LWW timestamp.
/// When such mutation is done, the merge between two LWW values is done using the inner
/// CRDT's merge operation. This is usefull in the case where the inner CRDT is a large
/// data type, such as a map, and we only want to change a single item in the map.
/// To do this, we can produce a "CRDT delta", i.e. a LWW that contains only the modification.
/// This delta consists in a LWW with the same timestamp, and the map
/// inside only contains the updated value.
/// The advantage of such a delta is that it is much smaller than the whole map.
///
/// Avoid using this if the inner data type is a primitive type such as a number or a string,
/// as you will then rely on the merge function defined on `Ord` types by keeping the maximum
/// of both values.
pub fn get_mut(&mut self) -> &mut T {
&mut self.v
}
@ -64,18 +165,20 @@ where
}
}
// ---- Boolean (true as absorbing state) ----
/// Boolean, where `true` is an absorbing state
#[derive(Clone, Copy, Debug, Serialize, Deserialize, PartialEq)]
pub struct Bool(bool);
impl Bool {
/// Create a new boolean with the specified value
pub fn new(b: bool) -> Self {
Self(b)
}
/// Set the boolean to true
pub fn set(&mut self) {
self.0 = true;
}
/// Get the boolean value
pub fn get(&self) -> bool {
self.0
}
@ -87,8 +190,23 @@ impl CRDT for Bool {
}
}
// ---- LWW Map ----
/// Last Write Win Map
///
/// This types defines a CRDT for a map from keys to values.
/// The values have an associated timestamp, such that the last written value
/// takes precedence over previous ones. As for the simpler `LWW` type, the value
/// type `V` is also required to implement the CRDT trait.
/// We do not encourage mutating the values associated with a given key
/// without updating the timestamp, in fact at the moment we do not provide a `.get_mut()`
/// method that would allow that.
///
/// Internally, the map is stored as a vector of keys and values, sorted by ascending key order.
/// This is why the key type `K` must implement `Ord` (and also to ensure a unique serialization,
/// such that two values can be compared for equality based on their hashes). As a consequence,
/// insertions take `O(n)` time. This means that LWWMap should be used for reasonably small maps.
/// However, note that even if we were using a more efficient data structure such as a `BTreeMap`,
/// the serialization cost `O(n)` would still have to be paid at each modification, so we are
/// actually not losing anything here.
#[derive(Clone, Debug, Serialize, Deserialize, PartialEq)]
pub struct LWWMap<K, V> {
vals: Vec<(K, u64, V)>,
@ -99,21 +217,35 @@ where
K: Ord,
V: CRDT,
{
/// Create a new empty map CRDT
pub fn new() -> Self {
Self { vals: vec![] }
}
/// Used to migrate from a map defined in an incompatible format. This produces
/// a map that contains a single item with the specified timestamp (copied from
/// the incompatible format). Do this as many times as you have items to migrate,
/// and put them all together using the CRDT merge operator.
pub fn migrate_from_raw_item(k: K, ts: u64, v: V) -> Self {
Self {
vals: vec![(k, ts, v)],
}
}
pub fn take_and_clear(&mut self) -> Self {
let vals = std::mem::replace(&mut self.vals, vec![]);
Self { vals }
}
pub fn clear(&mut self) {
self.vals.clear();
}
/// Returns a map that contains a single mapping from the specified key to the specified value.
/// This map is a mutator, or a delta-CRDT, such that when it is merged with the original map,
/// the previous value will be replaced with the one specified here.
/// The timestamp in the provided mutator is set to the maximum of the current system's clock
/// and 1 + the previous value's timestamp (if there is one), so that the new value will always
/// take precedence (LWW rule).
///
/// Typically, to update the value associated to a key in the map, you would do the following:
///
/// ```
/// let my_update = my_crdt.update_mutator(key_to_modify, new_value);
/// my_crdt.merge(&my_update);
/// ```
///
/// However extracting the mutator on its own and only sending that on the network is very
/// interesting as it is much smaller than the whole map.
pub fn update_mutator(&self, k: K, new_v: V) -> Self {
let new_vals = match self.vals.binary_search_by(|(k2, _, _)| k2.cmp(&k)) {
Ok(i) => {
@ -125,12 +257,45 @@ where
};
Self { vals: new_vals }
}
/// Takes all of the values of the map and returns them. The current map is reset to the
/// empty map. This is very usefull to produce in-place a new map that contains only a delta
/// that modifies a certain value:
///
/// ```
/// let mut a = get_my_crdt_value();
/// let old_a = a.take_and_clear();
/// a.merge(&old_a.update_mutator(key_to_modify, new_value));
/// put_my_crdt_value(a);
/// ```
///
/// Of course in this simple example we could have written simply
/// `pyt_my_crdt_value(a.update_mutator(key_to_modify, new_value))`,
/// but in the case where the map is a field in a struct for instance (as is always the case),
/// this becomes very handy:
///
/// ```
/// let mut a = get_my_crdt_value();
/// let old_a_map = a.map_field.take_and_clear();
/// a.map_field.merge(&old_a_map.update_mutator(key_to_modify, new_value));
/// put_my_crdt_value(a);
/// ```
pub fn take_and_clear(&mut self) -> Self {
let vals = std::mem::replace(&mut self.vals, vec![]);
Self { vals }
}
/// Removes all values from the map
pub fn clear(&mut self) {
self.vals.clear();
}
/// Get a reference to the value assigned to a key
pub fn get(&self, k: &K) -> Option<&V> {
match self.vals.binary_search_by(|(k2, _, _)| k2.cmp(&k)) {
Ok(i) => Some(&self.vals[i].2),
Err(_) => None,
}
}
/// Gets a reference to all of the items, as a slice. Usefull to iterate on all map values.
/// In most case you will want to ignore the timestamp (second item of the tuple).
pub fn items(&self) -> &[(K, u64, V)] {
&self.vals[..]
}