jpds/garage
1
0
Fork 0
forked from Deuxfleurs/garage
Code Issues 40 Pull requests Projects Releases Packages Wiki Activity

Merge pull request 'Changed all instances of assignation to assignment' (#465) from jpds/garage:assignments-correction into next

Browse source 
Reviewed-on: Deuxfleurs/garage#465
This commit is contained in:
Alex 2023-01-11 16:05:27 +00:00
commit 4f409f73dc
5 changed files with 73 additions and 73 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

4
src/garage/cli/layout.rs
View file

@ -210,7 +210,7 @@ pub async fn cmd_show_layout(
v + 1)
}
Err(e) => {
println!("Error while trying to compute the assignation: {}", e);
println!("Error while trying to compute the assignment: {}", e);
println!("This new layout cannot yet be applied.");
println!(
"You can also revert all proposed changes with: garage layout revert --version {}",
@ -236,7 +236,7 @@ pub async fn cmd_apply_layout(
send_layout(rpc_cli, rpc_host, layout).await?;
println!("New cluster layout with updated role assignation has been applied in cluster.");
println!("New cluster layout with updated role assignment has been applied in cluster.");
println!("Data will now be moved around between nodes accordingly.");
Ok(())

2
src/garage/cli/structs.rs
View file

@ -17,7 +17,7 @@ pub enum Command {
#[structopt(name = "node", version = garage_version())]
Node(NodeOperation),
/// Operations on the assignation of node roles in the cluster layout
/// Operations on the assignment of node roles in the cluster layout
#[structopt(name = "layout", version = garage_version())]
Layout(LayoutOperation),

4
src/rpc/graph_algo.rs
View file

@ -1,5 +1,5 @@
//! This module deals with graph algorithms.
//! It is used in layout.rs to build the partition to node assignation.
//! It is used in layout.rs to build the partition to node assignment.
use rand::prelude::SliceRandom;
use std::cmp::{max, min};
@ -177,7 +177,7 @@ impl Graph<FlowEdge> {
let flow_upper_bound = self.flow_upper_bound()?;
// To ensure the dispersion of the associations generated by the
// assignation, we shuffle the neighbours of the nodes. Hence,
// assignment, we shuffle the neighbours of the nodes. Hence,
// the vertices do not consider their neighbours in the same order.
self.shuffle_edges();

128
src/rpc/layout.rs
View file

@ -34,8 +34,8 @@ pub struct ClusterLayout {
/// This attribute is only used to retain the previously computed partition size,
/// to know to what extent does it change with the layout update.
pub partition_size: u64,
/// Parameters used to compute the assignation currently given by
/// ring_assignation_data
/// Parameters used to compute the assignment currently given by
/// ring_assignment_data
pub parameters: LayoutParameters,
pub roles: LwwMap<Uuid, NodeRoleV>,
@ -48,12 +48,12 @@ pub struct ClusterLayout {
/// 2. nodes that don't have a role are excluded (but they need to
/// stay in the CRDT as tombstones)
pub node_id_vec: Vec<Uuid>,
/// the assignation of data partitions to node, the values
/// the assignment of data partitions to node, the values
/// are indices in node_id_vec
#[serde(with = "serde_bytes")]
pub ring_assignation_data: Vec<CompactNodeType>,
pub ring_assignment_data: Vec<CompactNodeType>,
/// Parameters to be used in the next partition assignation computation.
/// Parameters to be used in the next partition assignment computation.
pub staging_parameters: Lww<LayoutParameters>,
/// Role changes which are staged for the next version of the layout
pub staging_roles: LwwMap<Uuid, NodeRoleV>,
@ -61,7 +61,7 @@ pub struct ClusterLayout {
}
impl garage_util::migrate::InitialFormat for ClusterLayout {}
/// This struct is used to set the parameters to be used in the assignation computation
/// This struct is used to set the parameters to be used in the assignment computation
/// algorithm. It is stored as a Crdt.
#[derive(PartialEq, Eq, PartialOrd, Ord, Clone, Debug, Serialize, Deserialize)]
pub struct LayoutParameters {
@ -106,7 +106,7 @@ impl NodeRole {
}
}
// Implementation of the ClusterLayout methods unrelated to the assignation algorithm.
// Implementation of the ClusterLayout methods unrelated to the assignment algorithm.
impl ClusterLayout {
pub fn new(replication_factor: usize) -> Self {
// We set the default zone redundancy to be equal to the replication factor,
@ -124,7 +124,7 @@ impl ClusterLayout {
partition_size: 0,
roles: LwwMap::new(),
node_id_vec: Vec::new(),
ring_assignation_data: Vec::new(),
ring_assignment_data: Vec::new(),
parameters,
staging_parameters,
staging_roles: empty_lwwmap,
@ -183,7 +183,7 @@ To know the correct value of the new layout version, invoke `garage layout show`
self.staging_roles.clear();
self.staging_hash = self.calculate_staging_hash();
let msg = self.calculate_partition_assignation()?;
let msg = self.calculate_partition_assignment()?;
self.version += 1;
@ -276,7 +276,7 @@ To know the correct value of the new layout version, invoke `garage layout show`
for (i, id) in self.node_id_vec.iter().enumerate() {
if id == uuid {
let mut count = 0;
for nod in self.ring_assignation_data.iter() {
for nod in self.ring_assignment_data.iter() {
if i as u8 == *nod {
count += 1
}
@ -301,7 +301,7 @@ To know the correct value of the new layout version, invoke `garage layout show`
}
/// Check a cluster layout for internal consistency
/// (assignation, roles, parameters, partition size)
/// (assignment, roles, parameters, partition size)
/// returns true if consistent, false if error
pub fn check(&self) -> Result<(), String> {
// Check that the hash of the staging data is correct
@ -325,37 +325,37 @@ To know the correct value of the new layout version, invoke `garage layout show`
return Err(format!("node_id_vec does not contain the correct set of nodes\nnode_id_vec: {:?}\nexpected: {:?}", node_id_vec, expected_nodes));
}
// Check that the assignation data has the correct length
let expected_assignation_data_len = (1 << PARTITION_BITS) * self.replication_factor;
if self.ring_assignation_data.len() != expected_assignation_data_len {
// Check that the assignment data has the correct length
let expected_assignment_data_len = (1 << PARTITION_BITS) * self.replication_factor;
if self.ring_assignment_data.len() != expected_assignment_data_len {
return Err(format!(
"ring_assignation_data has incorrect length {} instead of {}",
self.ring_assignation_data.len(),
expected_assignation_data_len
"ring_assignment_data has incorrect length {} instead of {}",
self.ring_assignment_data.len(),
expected_assignment_data_len
));
}
// Check that the assigned nodes are correct identifiers
// of nodes that are assigned a role
// and that role is not the role of a gateway nodes
for x in self.ring_assignation_data.iter() {
for x in self.ring_assignment_data.iter() {
if *x as usize >= self.node_id_vec.len() {
return Err(format!(
"ring_assignation_data contains invalid node id {}",
"ring_assignment_data contains invalid node id {}",
*x
));
}
let node = self.node_id_vec[*x as usize];
match self.roles.get(&node) {
Some(NodeRoleV(Some(x))) if x.capacity.is_some() => (),
_ => return Err("ring_assignation_data contains id of a gateway node".into()),
_ => return Err("ring_assignment_data contains id of a gateway node".into()),
}
}
// Check that every partition is associated to distinct nodes
let rf = self.replication_factor;
for p in 0..(1 << PARTITION_BITS) {
let nodes_of_p = self.ring_assignation_data[rf * p..rf * (p + 1)].to_vec();
let nodes_of_p = self.ring_assignment_data[rf * p..rf * (p + 1)].to_vec();
if nodes_of_p.iter().unique().count() != rf {
return Err(format!("partition does not contain {} unique node ids", rf));
}
@ -378,7 +378,7 @@ To know the correct value of the new layout version, invoke `garage layout show`
// Check that the nodes capacities is consistent with the stored partitions
let mut node_usage = vec![0; MAX_NODE_NUMBER];
for n in self.ring_assignation_data.iter() {
for n in self.ring_assignment_data.iter() {
node_usage[*n as usize] += 1;
}
for (n, usage) in node_usage.iter().enumerate() {
@ -415,21 +415,21 @@ To know the correct value of the new layout version, invoke `garage layout show`
}
}
// Implementation of the ClusterLayout methods related to the assignation algorithm.
// Implementation of the ClusterLayout methods related to the assignment algorithm.
impl ClusterLayout {
/// This function calculates a new partition-to-node assignation.
/// The computed assignation respects the node replication factor
/// This function calculates a new partition-to-node assignment.
/// The computed assignment respects the node replication factor
/// and the zone redundancy parameter It maximizes the capacity of a
/// partition (assuming all partitions have the same size).
/// Among such optimal assignation, it minimizes the distance to
/// the former assignation (if any) to minimize the amount of
/// Among such optimal assignment, it minimizes the distance to
/// the former assignment (if any) to minimize the amount of
/// data to be moved.
/// Staged role changes must be merged with nodes roles before calling this function,
/// hence it must only be called from apply_staged_changes() and hence is not public.
fn calculate_partition_assignation(&mut self) -> Result<Message, Error> {
fn calculate_partition_assignment(&mut self) -> Result<Message, Error> {
// We update the node ids, since the node role list might have changed with the
// changes in the layout. We retrieve the old_assignation reframed with new ids
let old_assignation_opt = self.update_node_id_vec()?;
// changes in the layout. We retrieve the old_assignment reframed with new ids
let old_assignment_opt = self.update_node_id_vec()?;
let mut msg = Message::new();
msg.push("==== COMPUTATION OF A NEW PARTITION ASSIGNATION ====".into());
@ -467,7 +467,7 @@ impl ClusterLayout {
// optimality.
let partition_size = self.compute_optimal_partition_size(&zone_to_id)?;
if old_assignation_opt != None {
if old_assignment_opt != None {
msg.push(format!(
"Optimal size of a partition: {} (was {} in the previous layout).",
ByteSize::b(partition_size).to_string_as(false),
@ -490,16 +490,16 @@ impl ClusterLayout {
);
}
// We compute a first flow/assignation that is heuristically close to the previous
// assignation
let mut gflow = self.compute_candidate_assignation(&zone_to_id, &old_assignation_opt)?;
if let Some(assoc) = &old_assignation_opt {
// We minimize the distance to the previous assignation.
// We compute a first flow/assignment that is heuristically close to the previous
// assignment
let mut gflow = self.compute_candidate_assignment(&zone_to_id, &old_assignment_opt)?;
if let Some(assoc) = &old_assignment_opt {
// We minimize the distance to the previous assignment.
self.minimize_rebalance_load(&mut gflow, &zone_to_id, assoc)?;
}
// We display statistics of the computation
msg.extend(self.output_stat(&gflow, &old_assignation_opt, &zone_to_id, &id_to_zone)?);
msg.extend(self.output_stat(&gflow, &old_assignment_opt, &zone_to_id, &id_to_zone)?);
msg.push("".to_string());
// We update the layout structure
@ -515,10 +515,10 @@ impl ClusterLayout {
}
/// The LwwMap of node roles might have changed. This function updates the node_id_vec
/// and returns the assignation given by ring, with the new indices of the nodes, and
/// and returns the assignment given by ring, with the new indices of the nodes, and
/// None if the node is not present anymore.
/// We work with the assumption that only this function and calculate_new_assignation
/// do modify assignation_ring and node_id_vec.
/// We work with the assumption that only this function and calculate_new_assignment
/// do modify assignment_ring and node_id_vec.
fn update_node_id_vec(&mut self) -> Result<Option<Vec<Vec<usize>>>, Error> {
// (1) We compute the new node list
// Non gateway nodes should be coded on 8bits, hence they must be first in the list
@ -556,15 +556,15 @@ impl ClusterLayout {
// (2) We retrieve the old association
// We rewrite the old association with the new indices. We only consider partition
// to node assignations where the node is still in use.
if self.ring_assignation_data.is_empty() {
// to node assignments where the node is still in use.
if self.ring_assignment_data.is_empty() {
// This is a new association
return Ok(None);
}
if self.ring_assignation_data.len() != NB_PARTITIONS * self.replication_factor {
if self.ring_assignment_data.len() != NB_PARTITIONS * self.replication_factor {
return Err(Error::Message(
"The old assignation does not have a size corresponding to \
"The old assignment does not have a size corresponding to \
the old replication factor or the number of partitions."
.into(),
));
@ -579,11 +579,11 @@ impl ClusterLayout {
uuid_to_new_id.insert(*uuid, i);
}
let mut old_assignation = vec![Vec::<usize>::new(); NB_PARTITIONS];
let mut old_assignment = vec![Vec::<usize>::new(); NB_PARTITIONS];
let rf = self.replication_factor;
for (p, old_assign_p) in old_assignation.iter_mut().enumerate() {
for old_id in &self.ring_assignation_data[p * rf..(p + 1) * rf] {
for (p, old_assign_p) in old_assignment.iter_mut().enumerate() {
for old_id in &self.ring_assignment_data[p * rf..(p + 1) * rf] {
let uuid = old_node_id_vec[*old_id as usize];
if uuid_to_new_id.contains_key(&uuid) {
old_assign_p.push(uuid_to_new_id[&uuid]);
@ -592,9 +592,9 @@ impl ClusterLayout {
}
// We write the ring
self.ring_assignation_data = Vec::<CompactNodeType>::new();
self.ring_assignment_data = Vec::<CompactNodeType>::new();
Ok(Some(old_assignation))
Ok(Some(old_assignment))
}
/// This function generates ids for the zone of the nodes appearing in
@ -661,11 +661,11 @@ impl ClusterLayout {
}
/// Generates the graph to compute the maximal flow corresponding to the optimal
/// partition assignation.
/// partition assignment.
/// exclude_assoc is the set of (partition, node) association that we are forbidden
/// to use (hence we do not add the corresponding edge to the graph). This parameter
/// is used to compute a first flow that uses only edges appearing in the previous
/// assignation. This produces a solution that heuristically should be close to the
/// assignment. This produces a solution that heuristically should be close to the
/// previous one.
fn generate_flow_graph(
&self,
@ -707,14 +707,14 @@ impl ClusterLayout {
Ok(g)
}
/// This function computes a first optimal assignation (in the form of a flow graph).
fn compute_candidate_assignation(
/// This function computes a first optimal assignment (in the form of a flow graph).
fn compute_candidate_assignment(
&self,
zone_to_id: &HashMap<String, usize>,
prev_assign_opt: &Option<Vec<Vec<usize>>>,
) -> Result<Graph<FlowEdge>, Error> {
// We list the (partition,node) associations that are not used in the
// previous assignation
// previous assignment
let mut exclude_edge = HashSet::<(usize, usize)>::new();
if let Some(prev_assign) = prev_assign_opt {
let nb_nodes = self.nongateway_nodes().len();
@ -728,7 +728,7 @@ impl ClusterLayout {
}
}
// We compute the best flow using only the edges used in the previous assignation
// We compute the best flow using only the edges used in the previous assignment
let mut g = self.generate_flow_graph(self.partition_size, zone_to_id, &exclude_edge)?;
g.compute_maximal_flow()?;
@ -744,7 +744,7 @@ impl ClusterLayout {
}
/// This function updates the flow graph gflow to minimize the distance between
/// its corresponding assignation and the previous one
/// its corresponding assignment and the previous one
fn minimize_rebalance_load(
&self,
gflow: &mut Graph<FlowEdge>,
@ -752,7 +752,7 @@ impl ClusterLayout {
prev_assign: &[Vec<usize>],
) -> Result<(), Error> {
// We define a cost function on the edges (pairs of vertices) corresponding
// to the distance between the two assignations.
// to the distance between the two assignments.
let mut cost = CostFunction::new();
for (p, assoc_p) in prev_assign.iter().enumerate() {
for n in assoc_p.iter() {
@ -771,25 +771,25 @@ impl ClusterLayout {
Ok(())
}
/// This function updates the assignation ring from the flow graph.
/// This function updates the assignment ring from the flow graph.
fn update_ring_from_flow(
&mut self,
nb_zones: usize,
gflow: &Graph<FlowEdge>,
) -> Result<(), Error> {
self.ring_assignation_data = Vec::<CompactNodeType>::new();
self.ring_assignment_data = Vec::<CompactNodeType>::new();
for p in 0..NB_PARTITIONS {
for z in 0..nb_zones {
let assoc_vertex = gflow.get_positive_flow_from(Vertex::PZ(p, z))?;
for vertex in assoc_vertex.iter() {
if let Vertex::N(n) = vertex {
self.ring_assignation_data.push((*n).try_into().unwrap());
self.ring_assignment_data.push((*n).try_into().unwrap());
}
}
}
}
if self.ring_assignation_data.len() != NB_PARTITIONS * self.replication_factor {
if self.ring_assignment_data.len() != NB_PARTITIONS * self.replication_factor {
return Err(Error::Message(
"Critical Error : the association ring we produced does not \
have the right size."
@ -800,7 +800,7 @@ impl ClusterLayout {
}
/// This function returns a message summing up the partition repartition of the new
/// layout, and other statistics of the partition assignation computation.
/// layout, and other statistics of the partition assignment computation.
fn output_stat(
&self,
gflow: &Graph<FlowEdge>,
@ -960,7 +960,7 @@ mod tests {
// This function checks that the partition size S computed is at least better than the
// one given by a very naive algorithm. To do so, we try to run the naive algorithm
// assuming a partion size of S+1. If we succed, it means that the optimal assignation
// assuming a partion size of S+1. If we succed, it means that the optimal assignment
// was not optimal. The naive algorithm is the following :
// - we compute the max number of partitions associated to every node, capped at the
// partition number. It gives the number of tokens of every node.
@ -1065,7 +1065,7 @@ mod tests {
}
#[test]
fn test_assignation() {
fn test_assignment() {
let mut node_id_vec = vec![1, 2, 3];
let mut node_capacity_vec = vec![4000, 1000, 2000];
let mut node_zone_vec = vec!["A", "B", "C"]

8
src/rpc/ring.rs
View file

@ -63,12 +63,12 @@ struct RingEntry {
impl Ring {
pub(crate) fn new(layout: ClusterLayout, replication_factor: usize) -> Self {
if replication_factor != layout.replication_factor {
warn!("Could not build ring: replication factor does not match between local configuration and network role assignation.");
warn!("Could not build ring: replication factor does not match between local configuration and network role assignment.");
return Self::empty(layout, replication_factor);
}
if layout.ring_assignation_data.len() != replication_factor * (1 << PARTITION_BITS) {
warn!("Could not build ring: network role assignation data has invalid length");
if layout.ring_assignment_data.len() != replication_factor * (1 << PARTITION_BITS) {
warn!("Could not build ring: network role assignment data has invalid length");
return Self::empty(layout, replication_factor);
}
@ -78,7 +78,7 @@ impl Ring {
let top = (i as u16) << (16 - PARTITION_BITS);
let mut nodes_buf = [0u8; MAX_REPLICATION];
nodes_buf[..replication_factor].copy_from_slice(
&layout.ring_assignation_data
&layout.ring_assignment_data
[replication_factor * i..replication_factor * (i + 1)],
);
RingEntry {