Merge pull request 'Table+Model doc' (#22) from doc/model into master

Reviewed-on: https://git.deuxfleurs.fr/Deuxfleurs/garage/pulls/22

src/model/bucket_table.rs

@@ -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)]

src/table/crdt.rs

@@ -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 {
+	/// Returns a map that contains a single mapping from the specified key to the specified value.
-		let vals = std::mem::replace(&mut self.vals, vec![]);
+	/// This map is a mutator, or a delta-CRDT, such that when it is merged with the original map,
-		Self { vals }
+	/// 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
-	pub fn clear(&mut self) {
+	/// and 1 + the previous value's timestamp (if there is one), so that the new value will always
-		self.vals.clear();
+	/// 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[..]
 	}