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