forked from Deuxfleurs/garage
cargo fmt
This commit is contained in:
parent
fcf9ac674a
commit
4abab246f1
8 changed files with 1109 additions and 985 deletions
|
@ -4,7 +4,6 @@ extern crate tracing;
|
|||
|
||||
#[cfg(not(any(feature = "lmdb", feature = "sled", feature = "sqlite")))]
|
||||
//compile_error!("Must activate the Cargo feature for at least one DB engine: lmdb, sled or sqlite.");
|
||||
|
||||
#[cfg(feature = "lmdb")]
|
||||
pub mod lmdb_adapter;
|
||||
#[cfg(feature = "sled")]
|
||||
|
|
|
@ -190,7 +190,10 @@ pub async fn cmd_show_layout(
|
|||
println!();
|
||||
|
||||
println!("==== PARAMETERS OF THE LAYOUT COMPUTATION ====");
|
||||
println!("Zone redundancy: {}", layout.staged_parameters.get().zone_redundancy);
|
||||
println!(
|
||||
"Zone redundancy: {}",
|
||||
layout.staged_parameters.get().zone_redundancy
|
||||
);
|
||||
println!();
|
||||
|
||||
// this will print the stats of what partitions
|
||||
|
@ -206,11 +209,15 @@ pub async fn cmd_show_layout(
|
|||
println!();
|
||||
println!(
|
||||
"You can also revert all proposed changes with: garage layout revert --version {}",
|
||||
layout.version + 1)},
|
||||
layout.version + 1)
|
||||
}
|
||||
Err(Error::Message(s)) => {
|
||||
println!("Error while trying to compute the assignation: {}", s);
|
||||
println!("This new layout cannot yet be applied.");},
|
||||
_ => { println!("Unknown Error"); },
|
||||
println!("This new layout cannot yet be applied.");
|
||||
}
|
||||
_ => {
|
||||
println!("Unknown Error");
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
|
@ -263,14 +270,17 @@ pub async fn cmd_config_layout(
|
|||
None => (),
|
||||
Some(r) => {
|
||||
if r > layout.replication_factor {
|
||||
println!("The zone redundancy must be smaller or equal to the \
|
||||
replication factor ({}).", layout.replication_factor);
|
||||
}
|
||||
else if r < 1 {
|
||||
println!(
|
||||
"The zone redundancy must be smaller or equal to the \
|
||||
replication factor ({}).",
|
||||
layout.replication_factor
|
||||
);
|
||||
} else if r < 1 {
|
||||
println!("The zone redundancy must be at least 1.");
|
||||
}
|
||||
else {
|
||||
layout.staged_parameters.update(LayoutParameters{ zone_redundancy: r });
|
||||
} else {
|
||||
layout
|
||||
.staged_parameters
|
||||
.update(LayoutParameters { zone_redundancy: r });
|
||||
println!("The new zone redundancy has been saved ({}).", r);
|
||||
}
|
||||
}
|
||||
|
|
|
@ -104,7 +104,6 @@ pub enum LayoutOperation {
|
|||
Revert(RevertLayoutOpt),
|
||||
}
|
||||
|
||||
|
||||
#[derive(StructOpt, Debug)]
|
||||
pub struct AssignRoleOpt {
|
||||
/// Node(s) to which to assign role (prefix of hexadecimal node id)
|
||||
|
|
|
@ -1,27 +1,25 @@
|
|||
|
||||
//! This module deals with graph algorithms.
|
||||
//! It is used in layout.rs to build the partition to node assignation.
|
||||
|
||||
use rand::prelude::SliceRandom;
|
||||
use std::cmp::{max, min};
|
||||
use std::collections::VecDeque;
|
||||
use std::collections::HashMap;
|
||||
use std::collections::VecDeque;
|
||||
|
||||
//Vertex data structures used in all the graphs used in layout.rs.
|
||||
//usize parameters correspond to node/zone/partitions ids.
|
||||
//To understand the vertex roles below, please refer to the formal description
|
||||
//of the layout computation algorithm.
|
||||
#[derive(Clone,Copy,Debug, PartialEq, Eq, Hash)]
|
||||
pub enum Vertex{
|
||||
#[derive(Clone, Copy, Debug, PartialEq, Eq, Hash)]
|
||||
pub enum Vertex {
|
||||
Source,
|
||||
Pup(usize), //The vertex p+ of partition p
|
||||
Pdown(usize), //The vertex p- of partition p
|
||||
PZ(usize,usize), //The vertex corresponding to x_(partition p, zone z)
|
||||
PZ(usize, usize), //The vertex corresponding to x_(partition p, zone z)
|
||||
N(usize), //The vertex corresponding to node n
|
||||
Sink
|
||||
Sink,
|
||||
}
|
||||
|
||||
|
||||
//Edge data structure for the flow algorithm.
|
||||
//The graph is stored as an adjacency list
|
||||
#[derive(Clone, Copy, Debug)]
|
||||
|
@ -47,33 +45,33 @@ impl Edge for WeightedEdge {}
|
|||
//Struct for the graph structure. We do encapsulation here to be able to both
|
||||
//provide user friendly Vertex enum to address vertices, and to use usize indices
|
||||
//and Vec instead of HashMap in the graph algorithm to optimize execution speed.
|
||||
pub struct Graph<E : Edge>{
|
||||
vertextoid : HashMap<Vertex , usize>,
|
||||
idtovertex : Vec<Vertex>,
|
||||
pub struct Graph<E: Edge> {
|
||||
vertextoid: HashMap<Vertex, usize>,
|
||||
idtovertex: Vec<Vertex>,
|
||||
|
||||
graph : Vec< Vec<E> >
|
||||
graph: Vec<Vec<E>>,
|
||||
}
|
||||
|
||||
pub type CostFunction = HashMap<(Vertex,Vertex), i32>;
|
||||
pub type CostFunction = HashMap<(Vertex, Vertex), i32>;
|
||||
|
||||
impl<E : Edge> Graph<E>{
|
||||
pub fn new(vertices : &[Vertex]) -> Self {
|
||||
impl<E: Edge> Graph<E> {
|
||||
pub fn new(vertices: &[Vertex]) -> Self {
|
||||
let mut map = HashMap::<Vertex, usize>::new();
|
||||
for (i, vert) in vertices.iter().enumerate(){
|
||||
map.insert(*vert , i);
|
||||
for (i, vert) in vertices.iter().enumerate() {
|
||||
map.insert(*vert, i);
|
||||
}
|
||||
Graph::<E> {
|
||||
vertextoid : map,
|
||||
vertextoid: map,
|
||||
idtovertex: vertices.to_vec(),
|
||||
graph : vec![Vec::< E >::new(); vertices.len() ]
|
||||
graph: vec![Vec::<E>::new(); vertices.len()],
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
impl Graph<FlowEdge>{
|
||||
impl Graph<FlowEdge> {
|
||||
//This function adds a directed edge to the graph with capacity c, and the
|
||||
//corresponding reversed edge with capacity 0.
|
||||
pub fn add_edge(&mut self, u: Vertex, v:Vertex, c: u32) -> Result<(), String>{
|
||||
pub fn add_edge(&mut self, u: Vertex, v: Vertex, c: u32) -> Result<(), String> {
|
||||
if !self.vertextoid.contains_key(&u) || !self.vertextoid.contains_key(&v) {
|
||||
return Err("The graph does not contain the provided vertex.".to_string());
|
||||
}
|
||||
|
@ -81,14 +79,24 @@ impl Graph<FlowEdge>{
|
|||
let idv = self.vertextoid[&v];
|
||||
let rev_u = self.graph[idu].len();
|
||||
let rev_v = self.graph[idv].len();
|
||||
self.graph[idu].push( FlowEdge{cap: c , dest: idv , flow: 0, rev : rev_v} );
|
||||
self.graph[idv].push( FlowEdge{cap: 0 , dest: idu , flow: 0, rev : rev_u} );
|
||||
self.graph[idu].push(FlowEdge {
|
||||
cap: c,
|
||||
dest: idv,
|
||||
flow: 0,
|
||||
rev: rev_v,
|
||||
});
|
||||
self.graph[idv].push(FlowEdge {
|
||||
cap: 0,
|
||||
dest: idu,
|
||||
flow: 0,
|
||||
rev: rev_u,
|
||||
});
|
||||
Ok(())
|
||||
}
|
||||
|
||||
//This function returns the list of vertices that receive a positive flow from
|
||||
//vertex v.
|
||||
pub fn get_positive_flow_from(&self , v:Vertex) -> Result< Vec<Vertex> , String>{
|
||||
pub fn get_positive_flow_from(&self, v: Vertex) -> Result<Vec<Vertex>, String> {
|
||||
if !self.vertextoid.contains_key(&v) {
|
||||
return Err("The graph does not contain the provided vertex.".to_string());
|
||||
}
|
||||
|
@ -102,29 +110,28 @@ impl Graph<FlowEdge>{
|
|||
Ok(result)
|
||||
}
|
||||
|
||||
|
||||
//This function returns the value of the flow incoming to v.
|
||||
pub fn get_inflow(&self , v:Vertex) -> Result< i32 , String>{
|
||||
pub fn get_inflow(&self, v: Vertex) -> Result<i32, String> {
|
||||
if !self.vertextoid.contains_key(&v) {
|
||||
return Err("The graph does not contain the provided vertex.".to_string());
|
||||
}
|
||||
let idv = self.vertextoid[&v];
|
||||
let mut result = 0;
|
||||
for edge in self.graph[idv].iter() {
|
||||
result += max(0,self.graph[edge.dest][edge.rev].flow);
|
||||
result += max(0, self.graph[edge.dest][edge.rev].flow);
|
||||
}
|
||||
Ok(result)
|
||||
}
|
||||
|
||||
//This function returns the value of the flow outgoing from v.
|
||||
pub fn get_outflow(&self , v:Vertex) -> Result< i32 , String>{
|
||||
pub fn get_outflow(&self, v: Vertex) -> Result<i32, String> {
|
||||
if !self.vertextoid.contains_key(&v) {
|
||||
return Err("The graph does not contain the provided vertex.".to_string());
|
||||
}
|
||||
let idv = self.vertextoid[&v];
|
||||
let mut result = 0;
|
||||
for edge in self.graph[idv].iter() {
|
||||
result += max(0,edge.flow);
|
||||
result += max(0, edge.flow);
|
||||
}
|
||||
Ok(result)
|
||||
}
|
||||
|
@ -151,10 +158,10 @@ impl Graph<FlowEdge>{
|
|||
}
|
||||
|
||||
//Computes an upper bound of the flow n the graph
|
||||
pub fn flow_upper_bound(&self) -> u32{
|
||||
pub fn flow_upper_bound(&self) -> u32 {
|
||||
let idsource = self.vertextoid[&Vertex::Source];
|
||||
let mut flow_upper_bound = 0;
|
||||
for edge in self.graph[idsource].iter(){
|
||||
for edge in self.graph[idsource].iter() {
|
||||
flow_upper_bound += edge.cap;
|
||||
}
|
||||
flow_upper_bound
|
||||
|
@ -192,7 +199,8 @@ impl Graph<FlowEdge>{
|
|||
fifo.push_back((idsource, 0));
|
||||
while !fifo.is_empty() {
|
||||
if let Some((id, lvl)) = fifo.pop_front() {
|
||||
if level[id] == None { //it means id has not yet been reached
|
||||
if level[id] == None {
|
||||
//it means id has not yet been reached
|
||||
level[id] = Some(lvl);
|
||||
for edge in self.graph[id].iter() {
|
||||
if edge.cap as i32 - edge.flow > 0 {
|
||||
|
@ -240,13 +248,15 @@ impl Graph<FlowEdge>{
|
|||
continue;
|
||||
}
|
||||
//else we can try to send flow from id to its nbd
|
||||
let new_flow = min(f as i32, self.graph[id][nbd].cap as i32 - self.graph[id][nbd].flow) as u32;
|
||||
let new_flow = min(
|
||||
f as i32,
|
||||
self.graph[id][nbd].cap as i32 - self.graph[id][nbd].flow,
|
||||
) as u32;
|
||||
if new_flow == 0 {
|
||||
next_nbd[id] += 1;
|
||||
continue;
|
||||
}
|
||||
if let (Some(lvldest), Some(lvlid)) =
|
||||
(level[self.graph[id][nbd].dest], level[id]){
|
||||
if let (Some(lvldest), Some(lvlid)) = (level[self.graph[id][nbd].dest], level[id]) {
|
||||
if lvldest <= lvlid {
|
||||
//We cannot send flow to nbd.
|
||||
next_nbd[id] += 1;
|
||||
|
@ -265,25 +275,28 @@ impl Graph<FlowEdge>{
|
|||
// as subroutine the Bellman Ford algorithm run up to path_length.
|
||||
// We assume that the cost of edge (u,v) is the opposite of the cost of (v,u), and only
|
||||
// one needs to be present in the cost function.
|
||||
pub fn optimize_flow_with_cost(&mut self , cost: &CostFunction, path_length: usize )
|
||||
-> Result<(),String>{
|
||||
pub fn optimize_flow_with_cost(
|
||||
&mut self,
|
||||
cost: &CostFunction,
|
||||
path_length: usize,
|
||||
) -> Result<(), String> {
|
||||
//We build the weighted graph g where we will look for negative cycle
|
||||
let mut gf = self.build_cost_graph(cost)?;
|
||||
let mut cycles = gf.list_negative_cycles(path_length);
|
||||
while !cycles.is_empty() {
|
||||
//we enumerate negative cycles
|
||||
for c in cycles.iter(){
|
||||
for i in 0..c.len(){
|
||||
for c in cycles.iter() {
|
||||
for i in 0..c.len() {
|
||||
//We add one flow unit to the edge (u,v) of cycle c
|
||||
let idu = self.vertextoid[&c[i]];
|
||||
let idv = self.vertextoid[&c[(i+1)%c.len()]];
|
||||
for j in 0..self.graph[idu].len(){
|
||||
let idv = self.vertextoid[&c[(i + 1) % c.len()]];
|
||||
for j in 0..self.graph[idu].len() {
|
||||
//since idu appears at most once in the cycles, we enumerate every
|
||||
//edge at most once.
|
||||
let edge = self.graph[idu][j];
|
||||
if edge.dest == idv {
|
||||
self.graph[idu][j].flow += 1;
|
||||
self.graph[idv][edge.rev].flow -=1;
|
||||
self.graph[idv][edge.rev].flow -= 1;
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
@ -297,44 +310,38 @@ impl Graph<FlowEdge>{
|
|||
}
|
||||
|
||||
//Construct the weighted graph G_f from the flow and the cost function
|
||||
fn build_cost_graph(&self , cost: &CostFunction) -> Result<Graph<WeightedEdge>,String>{
|
||||
|
||||
fn build_cost_graph(&self, cost: &CostFunction) -> Result<Graph<WeightedEdge>, String> {
|
||||
let mut g = Graph::<WeightedEdge>::new(&self.idtovertex);
|
||||
let nb_vertices = self.idtovertex.len();
|
||||
for i in 0..nb_vertices {
|
||||
for edge in self.graph[i].iter() {
|
||||
if edge.cap as i32 -edge.flow > 0 {
|
||||
if edge.cap as i32 - edge.flow > 0 {
|
||||
//It is possible to send overflow through this edge
|
||||
let u = self.idtovertex[i];
|
||||
let v = self.idtovertex[edge.dest];
|
||||
if cost.contains_key(&(u,v)) {
|
||||
g.add_edge(u,v, cost[&(u,v)])?;
|
||||
}
|
||||
else if cost.contains_key(&(v,u)) {
|
||||
g.add_edge(u,v, -cost[&(v,u)])?;
|
||||
}
|
||||
else{
|
||||
g.add_edge(u,v, 0)?;
|
||||
if cost.contains_key(&(u, v)) {
|
||||
g.add_edge(u, v, cost[&(u, v)])?;
|
||||
} else if cost.contains_key(&(v, u)) {
|
||||
g.add_edge(u, v, -cost[&(v, u)])?;
|
||||
} else {
|
||||
g.add_edge(u, v, 0)?;
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
Ok(g)
|
||||
|
||||
}
|
||||
|
||||
|
||||
}
|
||||
|
||||
impl Graph<WeightedEdge>{
|
||||
impl Graph<WeightedEdge> {
|
||||
//This function adds a single directed weighted edge to the graph.
|
||||
pub fn add_edge(&mut self, u: Vertex, v:Vertex, w: i32) -> Result<(), String>{
|
||||
pub fn add_edge(&mut self, u: Vertex, v: Vertex, w: i32) -> Result<(), String> {
|
||||
if !self.vertextoid.contains_key(&u) || !self.vertextoid.contains_key(&v) {
|
||||
return Err("The graph does not contain the provided vertex.".to_string());
|
||||
}
|
||||
let idu = self.vertextoid[&u];
|
||||
let idv = self.vertextoid[&v];
|
||||
self.graph[idu].push( WeightedEdge{ w , dest: idv} );
|
||||
self.graph[idu].push(WeightedEdge { w, dest: idv });
|
||||
Ok(())
|
||||
}
|
||||
|
||||
|
@ -344,18 +351,17 @@ impl Graph<WeightedEdge>{
|
|||
//for particular graph structures like our case, the algorithm is still correct
|
||||
//when path_length is the length of the longest possible simple path.
|
||||
//See the formal description of the algorithm for more details.
|
||||
fn list_negative_cycles(&self, path_length: usize) -> Vec< Vec<Vertex> > {
|
||||
|
||||
fn list_negative_cycles(&self, path_length: usize) -> Vec<Vec<Vertex>> {
|
||||
let nb_vertices = self.graph.len();
|
||||
|
||||
//We start with every vertex at distance 0 of some imaginary extra -1 vertex.
|
||||
let mut distance = vec![0 ; nb_vertices];
|
||||
let mut distance = vec![0; nb_vertices];
|
||||
//The prev vector collects for every vertex from where does the shortest path come
|
||||
let mut prev = vec![None; nb_vertices];
|
||||
|
||||
for _ in 0..path_length +1 {
|
||||
for id in 0..nb_vertices{
|
||||
for e in self.graph[id].iter(){
|
||||
for _ in 0..path_length + 1 {
|
||||
for id in 0..nb_vertices {
|
||||
for e in self.graph[id].iter() {
|
||||
if distance[id] + e.w < distance[e.dest] {
|
||||
distance[e.dest] = distance[id] + e.w;
|
||||
prev[e.dest] = Some(id);
|
||||
|
@ -364,7 +370,6 @@ impl Graph<WeightedEdge>{
|
|||
}
|
||||
}
|
||||
|
||||
|
||||
//If self.graph contains a negative cycle, then at this point the graph described
|
||||
//by prev (which is a directed 1-forest/functional graph)
|
||||
//must contain a cycle. We list the cycles of prev.
|
||||
|
@ -372,29 +377,27 @@ impl Graph<WeightedEdge>{
|
|||
|
||||
//Remark that the cycle in prev is in the reverse order compared to the cycle
|
||||
//in the graph. Thus the .rev().
|
||||
return cycles_prev.iter().map(|cycle| cycle.iter().rev().map(
|
||||
|id| self.idtovertex[*id]
|
||||
).collect() ).collect();
|
||||
return cycles_prev
|
||||
.iter()
|
||||
.map(|cycle| cycle.iter().rev().map(|id| self.idtovertex[*id]).collect())
|
||||
.collect();
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
|
||||
//This function returns the list of cycles of a directed 1 forest. It does not
|
||||
//check for the consistency of the input.
|
||||
fn cycles_of_1_forest(forest: &[Option<usize>]) -> Vec<Vec<usize>> {
|
||||
let mut cycles = Vec::<Vec::<usize>>::new();
|
||||
let mut cycles = Vec::<Vec<usize>>::new();
|
||||
let mut time_of_discovery = vec![None; forest.len()];
|
||||
|
||||
for t in 0..forest.len(){
|
||||
for t in 0..forest.len() {
|
||||
let mut id = t;
|
||||
//while we are on a valid undiscovered node
|
||||
while time_of_discovery[id] == None {
|
||||
time_of_discovery[id] = Some(t);
|
||||
if let Some(i) = forest[id] {
|
||||
id = i;
|
||||
}
|
||||
else{
|
||||
} else {
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
@ -407,8 +410,7 @@ fn cycles_of_1_forest(forest: &[Option<usize>]) -> Vec<Vec<usize>> {
|
|||
id2 = id_next;
|
||||
if id2 != id {
|
||||
cy.push(id2);
|
||||
}
|
||||
else {
|
||||
} else {
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
@ -417,5 +419,3 @@ fn cycles_of_1_forest(forest: &[Option<usize>]) -> Vec<Vec<usize>> {
|
|||
}
|
||||
cycles
|
||||
}
|
||||
|
||||
|
||||
|
|
|
@ -7,7 +7,7 @@ use itertools::Itertools;
|
|||
|
||||
use serde::{Deserialize, Serialize};
|
||||
|
||||
use garage_util::crdt::{AutoCrdt, Crdt, LwwMap, Lww};
|
||||
use garage_util::crdt::{AutoCrdt, Crdt, Lww, LwwMap};
|
||||
use garage_util::data::*;
|
||||
use garage_util::error::*;
|
||||
|
||||
|
@ -58,14 +58,14 @@ pub struct ClusterLayout {
|
|||
///algorithm. It is stored as a Crdt.
|
||||
#[derive(PartialEq, Eq, PartialOrd, Ord, Clone, Debug, Serialize, Deserialize)]
|
||||
pub struct LayoutParameters {
|
||||
pub zone_redundancy:usize,
|
||||
pub zone_redundancy: usize,
|
||||
}
|
||||
|
||||
impl AutoCrdt for LayoutParameters {
|
||||
const WARN_IF_DIFFERENT: bool = true;
|
||||
}
|
||||
|
||||
const NB_PARTITIONS : usize = 1usize << PARTITION_BITS;
|
||||
const NB_PARTITIONS: usize = 1usize << PARTITION_BITS;
|
||||
|
||||
#[derive(PartialEq, Eq, PartialOrd, Ord, Clone, Debug, Serialize, Deserialize)]
|
||||
pub struct NodeRoleV(pub Option<NodeRole>);
|
||||
|
@ -99,10 +99,10 @@ impl NodeRole {
|
|||
pub fn tags_string(&self) -> String {
|
||||
let mut tags = String::new();
|
||||
if self.tags.is_empty() {
|
||||
return tags
|
||||
return tags;
|
||||
}
|
||||
tags.push_str(&self.tags[0].clone());
|
||||
for t in 1..self.tags.len(){
|
||||
for t in 1..self.tags.len() {
|
||||
tags.push(',');
|
||||
tags.push_str(&self.tags[t].clone());
|
||||
}
|
||||
|
@ -112,10 +112,11 @@ impl NodeRole {
|
|||
|
||||
impl ClusterLayout {
|
||||
pub fn new(replication_factor: usize) -> Self {
|
||||
|
||||
//We set the default zone redundancy to be equal to the replication factor,
|
||||
//i.e. as strict as possible.
|
||||
let parameters = LayoutParameters{ zone_redundancy: replication_factor};
|
||||
let parameters = LayoutParameters {
|
||||
zone_redundancy: replication_factor,
|
||||
};
|
||||
let staged_parameters = Lww::<LayoutParameters>::new(parameters.clone());
|
||||
|
||||
let empty_lwwmap = LwwMap::new();
|
||||
|
@ -146,7 +147,6 @@ impl ClusterLayout {
|
|||
self.staged_parameters.merge(&other.staged_parameters);
|
||||
self.staging.merge(&other.staging);
|
||||
|
||||
|
||||
let new_staging_hash = blake2sum(&rmp_to_vec_all_named(&self.staging).unwrap()[..]);
|
||||
let stage_changed = new_staging_hash != self.staging_hash;
|
||||
|
||||
|
@ -158,7 +158,7 @@ impl ClusterLayout {
|
|||
}
|
||||
}
|
||||
|
||||
pub fn apply_staged_changes(mut self, version: Option<u64>) -> Result<(Self,Message), Error> {
|
||||
pub fn apply_staged_changes(mut self, version: Option<u64>) -> Result<(Self, Message), Error> {
|
||||
match version {
|
||||
None => {
|
||||
let error = r#"
|
||||
|
@ -184,7 +184,7 @@ To know the correct value of the new layout version, invoke `garage layout show`
|
|||
|
||||
self.version += 1;
|
||||
|
||||
Ok((self,msg))
|
||||
Ok((self, msg))
|
||||
}
|
||||
|
||||
pub fn revert_staged_changes(mut self, version: Option<u64>) -> Result<Self, Error> {
|
||||
|
@ -235,31 +235,40 @@ To know the correct value of the new layout version, invoke `garage layout show`
|
|||
for uuid in self.node_id_vec.iter() {
|
||||
match self.node_role(uuid) {
|
||||
Some(role) if role.capacity != None => result.push(*uuid),
|
||||
_ => ()
|
||||
_ => (),
|
||||
}
|
||||
}
|
||||
result
|
||||
}
|
||||
|
||||
///Given a node uuids, this function returns the label of its zone
|
||||
pub fn get_node_zone(&self, uuid : &Uuid) -> Result<String,Error> {
|
||||
pub fn get_node_zone(&self, uuid: &Uuid) -> Result<String, Error> {
|
||||
match self.node_role(uuid) {
|
||||
Some(role) => Ok(role.zone.clone()),
|
||||
_ => Err(Error::Message("The Uuid does not correspond to a node present in the cluster.".into()))
|
||||
_ => Err(Error::Message(
|
||||
"The Uuid does not correspond to a node present in the cluster.".into(),
|
||||
)),
|
||||
}
|
||||
}
|
||||
|
||||
///Given a node uuids, this function returns its capacity or fails if it does not have any
|
||||
pub fn get_node_capacity(&self, uuid : &Uuid) -> Result<u32,Error> {
|
||||
pub fn get_node_capacity(&self, uuid: &Uuid) -> Result<u32, Error> {
|
||||
match self.node_role(uuid) {
|
||||
Some(NodeRole{capacity : Some(cap), zone: _, tags: _}) => Ok(*cap),
|
||||
_ => Err(Error::Message("The Uuid does not correspond to a node present in the \
|
||||
cluster or this node does not have a positive capacity.".into()))
|
||||
Some(NodeRole {
|
||||
capacity: Some(cap),
|
||||
zone: _,
|
||||
tags: _,
|
||||
}) => Ok(*cap),
|
||||
_ => Err(Error::Message(
|
||||
"The Uuid does not correspond to a node present in the \
|
||||
cluster or this node does not have a positive capacity."
|
||||
.into(),
|
||||
)),
|
||||
}
|
||||
}
|
||||
|
||||
///Returns the sum of capacities of non gateway nodes in the cluster
|
||||
pub fn get_total_capacity(&self) -> Result<u32,Error> {
|
||||
pub fn get_total_capacity(&self) -> Result<u32, Error> {
|
||||
let mut total_capacity = 0;
|
||||
for uuid in self.useful_nodes().iter() {
|
||||
total_capacity += self.get_node_capacity(uuid)?;
|
||||
|
@ -267,7 +276,6 @@ To know the correct value of the new layout version, invoke `garage layout show`
|
|||
Ok(total_capacity)
|
||||
}
|
||||
|
||||
|
||||
/// Check a cluster layout for internal consistency
|
||||
/// returns true if consistent, false if error
|
||||
pub fn check(&self) -> bool {
|
||||
|
@ -314,14 +322,15 @@ To know the correct value of the new layout version, invoke `garage layout show`
|
|||
//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_assignation_data[rf * p..rf * (p + 1)].to_vec();
|
||||
if nodes_of_p.iter().unique().count() != rf {
|
||||
return false;
|
||||
}
|
||||
//Check that every partition is spread over at least zone_redundancy zones.
|
||||
let zones_of_p = nodes_of_p.iter()
|
||||
.map(|n| self.get_node_zone(&self.node_id_vec[*n as usize])
|
||||
.expect("Zone not found."));
|
||||
let zones_of_p = nodes_of_p.iter().map(|n| {
|
||||
self.get_node_zone(&self.node_id_vec[*n as usize])
|
||||
.expect("Zone not found.")
|
||||
});
|
||||
let redundancy = self.parameters.zone_redundancy;
|
||||
if zones_of_p.unique().count() < redundancy {
|
||||
return false;
|
||||
|
@ -333,11 +342,12 @@ To know the correct value of the new layout version, invoke `garage layout show`
|
|||
for n in self.ring_assignation_data.iter() {
|
||||
node_usage[*n as usize] += 1;
|
||||
}
|
||||
for (n, usage) in node_usage.iter().enumerate(){
|
||||
for (n, usage) in node_usage.iter().enumerate() {
|
||||
if *usage > 0 {
|
||||
let uuid = self.node_id_vec[n];
|
||||
if usage*self.partition_size > self.get_node_capacity(&uuid)
|
||||
.expect("Critical Error"){
|
||||
if usage * self.partition_size
|
||||
> self.get_node_capacity(&uuid).expect("Critical Error")
|
||||
{
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
@ -346,16 +356,16 @@ To know the correct value of the new layout version, invoke `garage layout show`
|
|||
//Check that the partition size stored is the one computed by the asignation
|
||||
//algorithm.
|
||||
let cl2 = self.clone();
|
||||
let (_ , zone_to_id) = cl2.generate_useful_zone_ids().expect("Critical Error");
|
||||
let partition_size = cl2.compute_optimal_partition_size(&zone_to_id).expect("Critical Error");
|
||||
let (_, zone_to_id) = cl2.generate_useful_zone_ids().expect("Critical Error");
|
||||
let partition_size = cl2
|
||||
.compute_optimal_partition_size(&zone_to_id)
|
||||
.expect("Critical Error");
|
||||
if partition_size != self.partition_size {
|
||||
return false;
|
||||
}
|
||||
|
||||
|
||||
true
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
impl ClusterLayout {
|
||||
|
@ -367,7 +377,7 @@ impl ClusterLayout {
|
|||
/// the former assignation (if any) to minimize the amount of
|
||||
/// data to be moved.
|
||||
/// Staged changes must be merged with nodes roles before calling this function.
|
||||
pub fn calculate_partition_assignation(&mut self) -> Result<Message,Error> {
|
||||
pub fn calculate_partition_assignation(&mut self) -> Result<Message, Error> {
|
||||
//The nodes might have been updated, some might have been deleted.
|
||||
//So we need to first update the list of nodes and retrieve the
|
||||
//assignation.
|
||||
|
@ -378,27 +388,37 @@ impl ClusterLayout {
|
|||
|
||||
let redundancy = self.staged_parameters.get().zone_redundancy;
|
||||
|
||||
|
||||
let mut msg = Message::new();
|
||||
msg.push(format!("Computation of a new cluster layout where partitions are \
|
||||
replicated {} times on at least {} distinct zones.", self.replication_factor, redundancy));
|
||||
msg.push(format!(
|
||||
"Computation of a new cluster layout where partitions are \
|
||||
replicated {} times on at least {} distinct zones.",
|
||||
self.replication_factor, redundancy
|
||||
));
|
||||
|
||||
//We generate for once numerical ids for the zones of non gateway nodes,
|
||||
//to use them as indices in the flow graphs.
|
||||
let (id_to_zone , zone_to_id) = self.generate_useful_zone_ids()?;
|
||||
let (id_to_zone, zone_to_id) = self.generate_useful_zone_ids()?;
|
||||
|
||||
let nb_useful_nodes = self.useful_nodes().len();
|
||||
msg.push(format!("The cluster contains {} nodes spread over {} zones.",
|
||||
nb_useful_nodes, id_to_zone.len()));
|
||||
if nb_useful_nodes < self.replication_factor{
|
||||
return Err(Error::Message(format!("The number of nodes with positive \
|
||||
msg.push(format!(
|
||||
"The cluster contains {} nodes spread over {} zones.",
|
||||
nb_useful_nodes,
|
||||
id_to_zone.len()
|
||||
));
|
||||
if nb_useful_nodes < self.replication_factor {
|
||||
return Err(Error::Message(format!(
|
||||
"The number of nodes with positive \
|
||||
capacity ({}) is smaller than the replication factor ({}).",
|
||||
nb_useful_nodes, self.replication_factor)));
|
||||
nb_useful_nodes, self.replication_factor
|
||||
)));
|
||||
}
|
||||
if id_to_zone.len() < redundancy {
|
||||
return Err(Error::Message(format!("The number of zones with non-gateway \
|
||||
return Err(Error::Message(format!(
|
||||
"The number of zones with non-gateway \
|
||||
nodes ({}) is smaller than the redundancy parameter ({})",
|
||||
id_to_zone.len() , redundancy)));
|
||||
id_to_zone.len(),
|
||||
redundancy
|
||||
)));
|
||||
}
|
||||
|
||||
//We compute the optimal partition size
|
||||
|
@ -408,36 +428,48 @@ impl ClusterLayout {
|
|||
let partition_size = self.compute_optimal_partition_size(&zone_to_id)?;
|
||||
|
||||
if old_assignation_opt != None {
|
||||
msg.push(format!("Given the replication and redundancy constraint, the \
|
||||
msg.push(format!(
|
||||
"Given the replication and redundancy constraint, the \
|
||||
optimal size of a partition is {}. In the previous layout, it used to \
|
||||
be {} (the zone redundancy was {}).", partition_size, self.partition_size,
|
||||
self.parameters.zone_redundancy));
|
||||
}
|
||||
else {
|
||||
msg.push(format!("Given the replication and redundancy constraints, the \
|
||||
optimal size of a partition is {}.", partition_size));
|
||||
be {} (the zone redundancy was {}).",
|
||||
partition_size, self.partition_size, self.parameters.zone_redundancy
|
||||
));
|
||||
} else {
|
||||
msg.push(format!(
|
||||
"Given the replication and redundancy constraints, the \
|
||||
optimal size of a partition is {}.",
|
||||
partition_size
|
||||
));
|
||||
}
|
||||
self.partition_size = partition_size;
|
||||
self.parameters = self.staged_parameters.get().clone();
|
||||
|
||||
if partition_size < 100 {
|
||||
msg.push("WARNING: The partition size is low (< 100), you might consider to \
|
||||
provide the nodes capacities in a smaller unit (e.g. Mb instead of Gb).".into());
|
||||
msg.push(
|
||||
"WARNING: The partition size is low (< 100), you might consider to \
|
||||
provide the nodes capacities in a smaller unit (e.g. Mb instead of Gb)."
|
||||
.into(),
|
||||
);
|
||||
}
|
||||
|
||||
//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_assignation_opt)?;
|
||||
let mut gflow = self.compute_candidate_assignment(&zone_to_id, &old_assignation_opt)?;
|
||||
if let Some(assoc) = &old_assignation_opt {
|
||||
//We minimize the distance to the previous assignment.
|
||||
self.minimize_rebalance_load(&mut gflow, &zone_to_id, assoc)?;
|
||||
}
|
||||
|
||||
msg.append(&mut self.output_stat(&gflow, &old_assignation_opt, &zone_to_id,&id_to_zone)?);
|
||||
msg.append(&mut self.output_stat(
|
||||
&gflow,
|
||||
&old_assignation_opt,
|
||||
&zone_to_id,
|
||||
&id_to_zone,
|
||||
)?);
|
||||
msg.push("".to_string());
|
||||
|
||||
//We update the layout structure
|
||||
self.update_ring_from_flow(id_to_zone.len() , &gflow)?;
|
||||
self.update_ring_from_flow(id_to_zone.len(), &gflow)?;
|
||||
Ok(msg)
|
||||
}
|
||||
|
||||
|
@ -446,22 +478,33 @@ impl ClusterLayout {
|
|||
/// 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.
|
||||
fn update_node_id_vec(&mut self) -> Result< Option< Vec<Vec<usize> > > ,Error> {
|
||||
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
|
||||
//We build the new node ids
|
||||
let mut new_non_gateway_nodes: Vec<Uuid> = self.roles.items().iter()
|
||||
let mut new_non_gateway_nodes: Vec<Uuid> = self
|
||||
.roles
|
||||
.items()
|
||||
.iter()
|
||||
.filter(|(_, _, v)| matches!(&v.0, Some(r) if r.capacity != None))
|
||||
.map(|(k, _, _)| *k).collect();
|
||||
.map(|(k, _, _)| *k)
|
||||
.collect();
|
||||
|
||||
if new_non_gateway_nodes.len() > MAX_NODE_NUMBER {
|
||||
return Err(Error::Message(format!("There are more than {} non-gateway nodes in the new \
|
||||
layout. This is not allowed.", MAX_NODE_NUMBER) ));
|
||||
return Err(Error::Message(format!(
|
||||
"There are more than {} non-gateway nodes in the new \
|
||||
layout. This is not allowed.",
|
||||
MAX_NODE_NUMBER
|
||||
)));
|
||||
}
|
||||
|
||||
let mut new_gateway_nodes: Vec<Uuid> = self.roles.items().iter()
|
||||
let mut new_gateway_nodes: Vec<Uuid> = self
|
||||
.roles
|
||||
.items()
|
||||
.iter()
|
||||
.filter(|(_, _, v)| matches!(v, NodeRoleV(Some(r)) if r.capacity == None))
|
||||
.map(|(k, _, _)| *k).collect();
|
||||
.map(|(k, _, _)| *k)
|
||||
.collect();
|
||||
|
||||
let mut new_node_id_vec = Vec::<Uuid>::new();
|
||||
new_node_id_vec.append(&mut new_non_gateway_nodes);
|
||||
|
@ -474,15 +517,18 @@ impl ClusterLayout {
|
|||
//We rewrite the old association with the new indices. We only consider partition
|
||||
//to node assignations where the node is still in use.
|
||||
let nb_partitions = 1usize << PARTITION_BITS;
|
||||
let mut old_assignation = vec![ Vec::<usize>::new() ; nb_partitions];
|
||||
let mut old_assignation = vec![Vec::<usize>::new(); nb_partitions];
|
||||
|
||||
if self.ring_assignation_data.is_empty() {
|
||||
//This is a new association
|
||||
return Ok(None);
|
||||
}
|
||||
if self.ring_assignation_data.len() != nb_partitions * self.replication_factor {
|
||||
return Err(Error::Message("The old assignation does not have a size corresponding to \
|
||||
the old replication factor or the number of partitions.".into()));
|
||||
return Err(Error::Message(
|
||||
"The old assignation does not have a size corresponding to \
|
||||
the old replication factor or the number of partitions."
|
||||
.into(),
|
||||
));
|
||||
}
|
||||
|
||||
//We build a translation table between the uuid and new ids
|
||||
|
@ -491,12 +537,12 @@ impl ClusterLayout {
|
|||
//We add the indices of only the new non-gateway nodes that can be used in the
|
||||
//association ring
|
||||
for (i, uuid) in new_node_id_vec.iter().enumerate() {
|
||||
uuid_to_new_id.insert(*uuid, i );
|
||||
uuid_to_new_id.insert(*uuid, i);
|
||||
}
|
||||
|
||||
let rf= self.replication_factor;
|
||||
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 old_id in &self.ring_assignation_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]);
|
||||
|
@ -508,27 +554,31 @@ impl ClusterLayout {
|
|||
self.ring_assignation_data = Vec::<CompactNodeType>::new();
|
||||
|
||||
if !self.check() {
|
||||
return Err(Error::Message("Critical error: The computed layout happens to be incorrect".into()));
|
||||
return Err(Error::Message(
|
||||
"Critical error: The computed layout happens to be incorrect".into(),
|
||||
));
|
||||
}
|
||||
|
||||
Ok(Some(old_assignation))
|
||||
}
|
||||
|
||||
|
||||
///This function generates ids for the zone of the nodes appearing in
|
||||
///self.node_id_vec.
|
||||
fn generate_useful_zone_ids(&self) -> Result<(Vec<String>, HashMap<String, usize>),Error>{
|
||||
fn generate_useful_zone_ids(&self) -> Result<(Vec<String>, HashMap<String, usize>), Error> {
|
||||
let mut id_to_zone = Vec::<String>::new();
|
||||
let mut zone_to_id = HashMap::<String,usize>::new();
|
||||
let mut zone_to_id = HashMap::<String, usize>::new();
|
||||
|
||||
for uuid in self.useful_nodes().iter() {
|
||||
if self.roles.get(uuid) == None {
|
||||
return Err(Error::Message("The uuid was not found in the node roles (this should \
|
||||
not happen, it might be a critical error).".into()));
|
||||
return Err(Error::Message(
|
||||
"The uuid was not found in the node roles (this should \
|
||||
not happen, it might be a critical error)."
|
||||
.into(),
|
||||
));
|
||||
}
|
||||
if let Some(r) = self.node_role(uuid) {
|
||||
if !zone_to_id.contains_key(&r.zone) && r.capacity != None {
|
||||
zone_to_id.insert(r.zone.clone() , id_to_zone.len());
|
||||
zone_to_id.insert(r.zone.clone(), id_to_zone.len());
|
||||
id_to_zone.push(r.zone.clone());
|
||||
}
|
||||
}
|
||||
|
@ -538,33 +588,46 @@ impl ClusterLayout {
|
|||
|
||||
///This function computes by dichotomy the largest realizable partition size, given
|
||||
///the layout.
|
||||
fn compute_optimal_partition_size(&self, zone_to_id: &HashMap<String, usize>) -> Result<u32,Error>{
|
||||
fn compute_optimal_partition_size(
|
||||
&self,
|
||||
zone_to_id: &HashMap<String, usize>,
|
||||
) -> Result<u32, Error> {
|
||||
let nb_partitions = 1usize << PARTITION_BITS;
|
||||
let empty_set = HashSet::<(usize,usize)>::new();
|
||||
let empty_set = HashSet::<(usize, usize)>::new();
|
||||
let mut g = self.generate_flow_graph(1, zone_to_id, &empty_set)?;
|
||||
g.compute_maximal_flow()?;
|
||||
if g.get_flow_value()? < (nb_partitions*self.replication_factor).try_into().unwrap() {
|
||||
return Err(Error::Message("The storage capacity of he cluster is to small. It is \
|
||||
impossible to store partitions of size 1.".into()));
|
||||
if g.get_flow_value()?
|
||||
< (nb_partitions * self.replication_factor)
|
||||
.try_into()
|
||||
.unwrap()
|
||||
{
|
||||
return Err(Error::Message(
|
||||
"The storage capacity of he cluster is to small. It is \
|
||||
impossible to store partitions of size 1."
|
||||
.into(),
|
||||
));
|
||||
}
|
||||
|
||||
let mut s_down = 1;
|
||||
let mut s_up = self.get_total_capacity()?;
|
||||
while s_down +1 < s_up {
|
||||
g = self.generate_flow_graph((s_down+s_up)/2, zone_to_id, &empty_set)?;
|
||||
while s_down + 1 < s_up {
|
||||
g = self.generate_flow_graph((s_down + s_up) / 2, zone_to_id, &empty_set)?;
|
||||
g.compute_maximal_flow()?;
|
||||
if g.get_flow_value()? < (nb_partitions*self.replication_factor).try_into().unwrap() {
|
||||
s_up = (s_down+s_up)/2;
|
||||
}
|
||||
else {
|
||||
s_down = (s_down+s_up)/2;
|
||||
if g.get_flow_value()?
|
||||
< (nb_partitions * self.replication_factor)
|
||||
.try_into()
|
||||
.unwrap()
|
||||
{
|
||||
s_up = (s_down + s_up) / 2;
|
||||
} else {
|
||||
s_down = (s_down + s_up) / 2;
|
||||
}
|
||||
}
|
||||
|
||||
Ok(s_down)
|
||||
}
|
||||
|
||||
fn generate_graph_vertices(nb_zones : usize, nb_nodes : usize) -> Vec<Vertex> {
|
||||
fn generate_graph_vertices(nb_zones: usize, nb_nodes: usize) -> Vec<Vertex> {
|
||||
let mut vertices = vec![Vertex::Source, Vertex::Sink];
|
||||
for p in 0..NB_PARTITIONS {
|
||||
vertices.push(Vertex::Pup(p));
|
||||
|
@ -579,27 +642,39 @@ impl ClusterLayout {
|
|||
vertices
|
||||
}
|
||||
|
||||
fn generate_flow_graph(&self, size: u32, zone_to_id: &HashMap<String, usize>, exclude_assoc : &HashSet<(usize,usize)>) -> Result<Graph<FlowEdge>, Error> {
|
||||
let vertices = ClusterLayout::generate_graph_vertices(zone_to_id.len(),
|
||||
self.useful_nodes().len());
|
||||
let mut g= Graph::<FlowEdge>::new(&vertices);
|
||||
fn generate_flow_graph(
|
||||
&self,
|
||||
size: u32,
|
||||
zone_to_id: &HashMap<String, usize>,
|
||||
exclude_assoc: &HashSet<(usize, usize)>,
|
||||
) -> Result<Graph<FlowEdge>, Error> {
|
||||
let vertices =
|
||||
ClusterLayout::generate_graph_vertices(zone_to_id.len(), self.useful_nodes().len());
|
||||
let mut g = Graph::<FlowEdge>::new(&vertices);
|
||||
let nb_zones = zone_to_id.len();
|
||||
let redundancy = self.staged_parameters.get().zone_redundancy;
|
||||
for p in 0..NB_PARTITIONS {
|
||||
g.add_edge(Vertex::Source, Vertex::Pup(p), redundancy as u32)?;
|
||||
g.add_edge(Vertex::Source, Vertex::Pdown(p), (self.replication_factor - redundancy) as u32)?;
|
||||
g.add_edge(
|
||||
Vertex::Source,
|
||||
Vertex::Pdown(p),
|
||||
(self.replication_factor - redundancy) as u32,
|
||||
)?;
|
||||
for z in 0..nb_zones {
|
||||
g.add_edge(Vertex::Pup(p) , Vertex::PZ(p,z) , 1)?;
|
||||
g.add_edge(Vertex::Pdown(p) , Vertex::PZ(p,z) ,
|
||||
self.replication_factor as u32)?;
|
||||
g.add_edge(Vertex::Pup(p), Vertex::PZ(p, z), 1)?;
|
||||
g.add_edge(
|
||||
Vertex::Pdown(p),
|
||||
Vertex::PZ(p, z),
|
||||
self.replication_factor as u32,
|
||||
)?;
|
||||
}
|
||||
}
|
||||
for n in 0..self.useful_nodes().len() {
|
||||
let node_capacity = self.get_node_capacity(&self.node_id_vec[n])?;
|
||||
let node_zone = zone_to_id[&self.get_node_zone(&self.node_id_vec[n])?];
|
||||
g.add_edge(Vertex::N(n), Vertex::Sink, node_capacity/size)?;
|
||||
g.add_edge(Vertex::N(n), Vertex::Sink, node_capacity / size)?;
|
||||
for p in 0..NB_PARTITIONS {
|
||||
if !exclude_assoc.contains(&(p,n)) {
|
||||
if !exclude_assoc.contains(&(p, n)) {
|
||||
g.add_edge(Vertex::PZ(p, node_zone), Vertex::N(n), 1)?;
|
||||
}
|
||||
}
|
||||
|
@ -607,55 +682,65 @@ impl ClusterLayout {
|
|||
Ok(g)
|
||||
}
|
||||
|
||||
|
||||
fn compute_candidate_assignment(&self, zone_to_id: &HashMap<String, usize>,
|
||||
old_assoc_opt : &Option<Vec< Vec<usize> >>) -> Result<Graph<FlowEdge>, Error > {
|
||||
|
||||
fn compute_candidate_assignment(
|
||||
&self,
|
||||
zone_to_id: &HashMap<String, usize>,
|
||||
old_assoc_opt: &Option<Vec<Vec<usize>>>,
|
||||
) -> Result<Graph<FlowEdge>, Error> {
|
||||
//We list the edges that are not used in the old association
|
||||
let mut exclude_edge = HashSet::<(usize,usize)>::new();
|
||||
let mut exclude_edge = HashSet::<(usize, usize)>::new();
|
||||
if let Some(old_assoc) = old_assoc_opt {
|
||||
let nb_nodes = self.useful_nodes().len();
|
||||
for (p, old_assoc_p) in old_assoc.iter().enumerate() {
|
||||
for n in 0..nb_nodes {
|
||||
exclude_edge.insert((p,n));
|
||||
exclude_edge.insert((p, n));
|
||||
}
|
||||
for n in old_assoc_p.iter() {
|
||||
exclude_edge.remove(&(p,*n));
|
||||
exclude_edge.remove(&(p, *n));
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
//We compute the best flow using only the edges used in the old assoc
|
||||
let mut g = self.generate_flow_graph(self.partition_size, zone_to_id, &exclude_edge )?;
|
||||
let mut g = self.generate_flow_graph(self.partition_size, zone_to_id, &exclude_edge)?;
|
||||
g.compute_maximal_flow()?;
|
||||
for (p,n) in exclude_edge.iter() {
|
||||
for (p, n) in exclude_edge.iter() {
|
||||
let node_zone = zone_to_id[&self.get_node_zone(&self.node_id_vec[*n])?];
|
||||
g.add_edge(Vertex::PZ(*p,node_zone), Vertex::N(*n), 1)?;
|
||||
g.add_edge(Vertex::PZ(*p, node_zone), Vertex::N(*n), 1)?;
|
||||
}
|
||||
g.compute_maximal_flow()?;
|
||||
Ok(g)
|
||||
}
|
||||
|
||||
fn minimize_rebalance_load(&self, gflow: &mut Graph<FlowEdge>, zone_to_id: &HashMap<String, usize>, old_assoc : &[Vec<usize> ]) -> Result<(), Error > {
|
||||
fn minimize_rebalance_load(
|
||||
&self,
|
||||
gflow: &mut Graph<FlowEdge>,
|
||||
zone_to_id: &HashMap<String, usize>,
|
||||
old_assoc: &[Vec<usize>],
|
||||
) -> Result<(), Error> {
|
||||
let mut cost = CostFunction::new();
|
||||
for (p, assoc_p) in old_assoc.iter().enumerate(){
|
||||
for (p, assoc_p) in old_assoc.iter().enumerate() {
|
||||
for n in assoc_p.iter() {
|
||||
let node_zone = zone_to_id[&self.get_node_zone(&self.node_id_vec[*n])?];
|
||||
cost.insert((Vertex::PZ(p,node_zone), Vertex::N(*n)), -1);
|
||||
cost.insert((Vertex::PZ(p, node_zone), Vertex::N(*n)), -1);
|
||||
}
|
||||
}
|
||||
let nb_nodes = self.useful_nodes().len();
|
||||
let path_length = 4*nb_nodes;
|
||||
let path_length = 4 * nb_nodes;
|
||||
gflow.optimize_flow_with_cost(&cost, path_length)?;
|
||||
|
||||
Ok(())
|
||||
}
|
||||
|
||||
fn update_ring_from_flow(&mut self, nb_zones : usize, gflow: &Graph<FlowEdge> ) -> Result<(), Error>{
|
||||
fn update_ring_from_flow(
|
||||
&mut self,
|
||||
nb_zones: usize,
|
||||
gflow: &Graph<FlowEdge>,
|
||||
) -> Result<(), Error> {
|
||||
self.ring_assignation_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))?;
|
||||
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());
|
||||
|
@ -664,39 +749,51 @@ impl ClusterLayout {
|
|||
}
|
||||
}
|
||||
|
||||
if self.ring_assignation_data.len() != NB_PARTITIONS*self.replication_factor {
|
||||
return Err(Error::Message("Critical Error : the association ring we produced does not \
|
||||
have the right size.".into()));
|
||||
if self.ring_assignation_data.len() != NB_PARTITIONS * self.replication_factor {
|
||||
return Err(Error::Message(
|
||||
"Critical Error : the association ring we produced does not \
|
||||
have the right size."
|
||||
.into(),
|
||||
));
|
||||
}
|
||||
Ok(())
|
||||
}
|
||||
|
||||
|
||||
//This function returns a message summing up the partition repartition of the new
|
||||
//layout.
|
||||
fn output_stat(&self , gflow : &Graph<FlowEdge>,
|
||||
old_assoc_opt : &Option< Vec<Vec<usize>> >,
|
||||
fn output_stat(
|
||||
&self,
|
||||
gflow: &Graph<FlowEdge>,
|
||||
old_assoc_opt: &Option<Vec<Vec<usize>>>,
|
||||
zone_to_id: &HashMap<String, usize>,
|
||||
id_to_zone : &[String]) -> Result<Message, Error>{
|
||||
id_to_zone: &[String],
|
||||
) -> Result<Message, Error> {
|
||||
let mut msg = Message::new();
|
||||
|
||||
let nb_partitions = 1usize << PARTITION_BITS;
|
||||
let used_cap = self.partition_size * nb_partitions as u32 *
|
||||
self.replication_factor as u32;
|
||||
let used_cap = self.partition_size * nb_partitions as u32 * self.replication_factor as u32;
|
||||
let total_cap = self.get_total_capacity()?;
|
||||
let percent_cap = 100.0*(used_cap as f32)/(total_cap as f32);
|
||||
msg.push(format!("Available capacity / Total cluster capacity: {} / {} ({:.1} %)",
|
||||
used_cap , total_cap , percent_cap ));
|
||||
let percent_cap = 100.0 * (used_cap as f32) / (total_cap as f32);
|
||||
msg.push(format!(
|
||||
"Available capacity / Total cluster capacity: {} / {} ({:.1} %)",
|
||||
used_cap, total_cap, percent_cap
|
||||
));
|
||||
msg.push("".into());
|
||||
msg.push("If the percentage is to low, it might be that the \
|
||||
msg.push(
|
||||
"If the percentage is to low, it might be that the \
|
||||
replication/redundancy constraints force the use of nodes/zones with small \
|
||||
storage capacities. \
|
||||
You might want to rebalance the storage capacities or relax the constraints. \
|
||||
See the detailed statistics below and look for saturated nodes/zones.".into());
|
||||
msg.push(format!("Recall that because of the replication factor, the actual available \
|
||||
See the detailed statistics below and look for saturated nodes/zones."
|
||||
.into(),
|
||||
);
|
||||
msg.push(format!(
|
||||
"Recall that because of the replication factor, the actual available \
|
||||
storage capacity is {} / {} = {}.",
|
||||
used_cap , self.replication_factor ,
|
||||
used_cap/self.replication_factor as u32));
|
||||
used_cap,
|
||||
self.replication_factor,
|
||||
used_cap / self.replication_factor as u32
|
||||
));
|
||||
|
||||
//We define and fill in the following tables
|
||||
let storing_nodes = self.useful_nodes();
|
||||
|
@ -708,14 +805,14 @@ impl ClusterLayout {
|
|||
|
||||
for p in 0..nb_partitions {
|
||||
for z in 0..id_to_zone.len() {
|
||||
let pz_nodes = gflow.get_positive_flow_from(Vertex::PZ(p,z))?;
|
||||
let pz_nodes = gflow.get_positive_flow_from(Vertex::PZ(p, z))?;
|
||||
if !pz_nodes.is_empty() {
|
||||
stored_partitions_zone[z] += 1;
|
||||
if let Some(old_assoc) = old_assoc_opt {
|
||||
let mut old_zones_of_p = Vec::<usize>::new();
|
||||
for n in old_assoc[p].iter() {
|
||||
old_zones_of_p.push(
|
||||
zone_to_id[&self.get_node_zone(&self.node_id_vec[*n])?]);
|
||||
old_zones_of_p
|
||||
.push(zone_to_id[&self.get_node_zone(&self.node_id_vec[*n])?]);
|
||||
}
|
||||
if !old_zones_of_p.contains(&z) {
|
||||
new_partitions_zone[z] += 1;
|
||||
|
@ -744,65 +841,81 @@ impl ClusterLayout {
|
|||
|
||||
msg.push("".into());
|
||||
if *old_assoc_opt != None {
|
||||
let total_new_partitions : usize = new_partitions.iter().sum();
|
||||
msg.push(format!("A total of {} new copies of partitions need to be \
|
||||
transferred.", total_new_partitions));
|
||||
let total_new_partitions: usize = new_partitions.iter().sum();
|
||||
msg.push(format!(
|
||||
"A total of {} new copies of partitions need to be \
|
||||
transferred.",
|
||||
total_new_partitions
|
||||
));
|
||||
}
|
||||
msg.push("".into());
|
||||
msg.push("==== DETAILED STATISTICS BY ZONES AND NODES ====".into());
|
||||
|
||||
for z in 0..id_to_zone.len(){
|
||||
for z in 0..id_to_zone.len() {
|
||||
let mut nodes_of_z = Vec::<usize>::new();
|
||||
for n in 0..storing_nodes.len(){
|
||||
for n in 0..storing_nodes.len() {
|
||||
if self.get_node_zone(&self.node_id_vec[n])? == id_to_zone[z] {
|
||||
nodes_of_z.push(n);
|
||||
}
|
||||
}
|
||||
let replicated_partitions : usize = nodes_of_z.iter()
|
||||
.map(|n| stored_partitions[*n]).sum();
|
||||
let replicated_partitions: usize =
|
||||
nodes_of_z.iter().map(|n| stored_partitions[*n]).sum();
|
||||
msg.push("".into());
|
||||
|
||||
msg.push(format!("Zone {}: {} distinct partitions stored ({} new, \
|
||||
{} partition copies) ", id_to_zone[z], stored_partitions_zone[z],
|
||||
new_partitions_zone[z], replicated_partitions));
|
||||
msg.push(format!(
|
||||
"Zone {}: {} distinct partitions stored ({} new, \
|
||||
{} partition copies) ",
|
||||
id_to_zone[z],
|
||||
stored_partitions_zone[z],
|
||||
new_partitions_zone[z],
|
||||
replicated_partitions
|
||||
));
|
||||
|
||||
let available_cap_z : u32 = self.partition_size*replicated_partitions as u32;
|
||||
let available_cap_z: u32 = self.partition_size * replicated_partitions as u32;
|
||||
let mut total_cap_z = 0;
|
||||
for n in nodes_of_z.iter() {
|
||||
total_cap_z += self.get_node_capacity(&self.node_id_vec[*n])?;
|
||||
}
|
||||
let percent_cap_z = 100.0*(available_cap_z as f32)/(total_cap_z as f32);
|
||||
msg.push(format!(" Available capacity / Total capacity: {}/{} ({:.1}%).",
|
||||
available_cap_z, total_cap_z, percent_cap_z));
|
||||
let percent_cap_z = 100.0 * (available_cap_z as f32) / (total_cap_z as f32);
|
||||
msg.push(format!(
|
||||
" Available capacity / Total capacity: {}/{} ({:.1}%).",
|
||||
available_cap_z, total_cap_z, percent_cap_z
|
||||
));
|
||||
|
||||
for n in nodes_of_z.iter() {
|
||||
let available_cap_n = stored_partitions[*n] as u32 *self.partition_size;
|
||||
let total_cap_n =self.get_node_capacity(&self.node_id_vec[*n])?;
|
||||
let tags_n = (self.node_role(&self.node_id_vec[*n])
|
||||
.ok_or("Node not found."))?.tags_string();
|
||||
msg.push(format!(" Node {}: {} partitions ({} new) ; \
|
||||
let available_cap_n = stored_partitions[*n] as u32 * self.partition_size;
|
||||
let total_cap_n = self.get_node_capacity(&self.node_id_vec[*n])?;
|
||||
let tags_n = (self
|
||||
.node_role(&self.node_id_vec[*n])
|
||||
.ok_or("Node not found."))?
|
||||
.tags_string();
|
||||
msg.push(format!(
|
||||
" Node {}: {} partitions ({} new) ; \
|
||||
available/total capacity: {} / {} ({:.1}%) ; tags:{}",
|
||||
&self.node_id_vec[*n].to_vec()[0..2].to_vec().encode_hex::<String>(),
|
||||
&self.node_id_vec[*n].to_vec()[0..2]
|
||||
.to_vec()
|
||||
.encode_hex::<String>(),
|
||||
stored_partitions[*n],
|
||||
new_partitions[*n], available_cap_n, total_cap_n,
|
||||
(available_cap_n as f32)/(total_cap_n as f32)*100.0 ,
|
||||
tags_n));
|
||||
new_partitions[*n],
|
||||
available_cap_n,
|
||||
total_cap_n,
|
||||
(available_cap_n as f32) / (total_cap_n as f32) * 100.0,
|
||||
tags_n
|
||||
));
|
||||
}
|
||||
}
|
||||
|
||||
Ok(msg)
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
//====================================================================================
|
||||
|
||||
#[cfg(test)]
|
||||
mod tests {
|
||||
use super::{*,Error};
|
||||
use super::{Error, *};
|
||||
use std::cmp::min;
|
||||
|
||||
|
||||
//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
|
||||
|
@ -817,8 +930,8 @@ mod tests {
|
|||
//number of tokens by zone : (A, 4), (B,1), (C,4), (D, 4), (E, 2)
|
||||
//With these parameters, the naive algo fails, whereas there is a solution:
|
||||
//(A,A,C,D,E) , (A,B,C,D,D) (A,C,C,D,E)
|
||||
fn check_against_naive(cl: &ClusterLayout) -> Result<bool,Error> {
|
||||
let over_size = cl.partition_size +1;
|
||||
fn check_against_naive(cl: &ClusterLayout) -> Result<bool, Error> {
|
||||
let over_size = cl.partition_size + 1;
|
||||
let mut zone_token = HashMap::<String, usize>::new();
|
||||
let nb_partitions = 1usize << PARTITION_BITS;
|
||||
|
||||
|
@ -834,14 +947,17 @@ mod tests {
|
|||
for uuid in cl.useful_nodes().iter() {
|
||||
let z = cl.get_node_zone(uuid)?;
|
||||
let c = cl.get_node_capacity(uuid)?;
|
||||
zone_token.insert(z.clone(), zone_token[&z] + min(nb_partitions , (c/over_size) as usize));
|
||||
zone_token.insert(
|
||||
z.clone(),
|
||||
zone_token[&z] + min(nb_partitions, (c / over_size) as usize),
|
||||
);
|
||||
}
|
||||
|
||||
//For every partition, we count the number of zone already associated and
|
||||
//the name of the last zone associated
|
||||
|
||||
let mut id_zone_token = vec![0; zones.len()];
|
||||
for (z,t) in zone_token.iter() {
|
||||
for (z, t) in zone_token.iter() {
|
||||
id_zone_token[zone_to_id[z]] = *t;
|
||||
}
|
||||
|
||||
|
@ -854,9 +970,10 @@ mod tests {
|
|||
|
||||
for replic in 0..cl.replication_factor {
|
||||
for p in 0..nb_partitions {
|
||||
while id_zone_token[curr_zone] == 0 ||
|
||||
(last_zone[p] == curr_zone
|
||||
&& redundancy - nb_token[p] <= cl.replication_factor - replic) {
|
||||
while id_zone_token[curr_zone] == 0
|
||||
|| (last_zone[p] == curr_zone
|
||||
&& redundancy - nb_token[p] <= cl.replication_factor - replic)
|
||||
{
|
||||
curr_zone += 1;
|
||||
if curr_zone >= zones.len() {
|
||||
return Ok(true);
|
||||
|
@ -873,9 +990,9 @@ mod tests {
|
|||
return Ok(false);
|
||||
}
|
||||
|
||||
fn show_msg(msg : &Message) {
|
||||
for s in msg.iter(){
|
||||
println!("{}",s);
|
||||
fn show_msg(msg: &Message) {
|
||||
for s in msg.iter() {
|
||||
println!("{}", s);
|
||||
}
|
||||
}
|
||||
|
||||
|
@ -884,7 +1001,7 @@ mod tests {
|
|||
node_id_vec: &Vec<u8>,
|
||||
node_capacity_vec: &Vec<u32>,
|
||||
node_zone_vec: &Vec<String>,
|
||||
zone_redundancy: usize
|
||||
zone_redundancy: usize,
|
||||
) {
|
||||
for i in 0..node_id_vec.len() {
|
||||
if let Some(x) = FixedBytes32::try_from(&[i as u8; 32]) {
|
||||
|
@ -901,7 +1018,7 @@ mod tests {
|
|||
);
|
||||
cl.roles.merge(&update);
|
||||
}
|
||||
cl.staged_parameters = Lww::<LayoutParameters>::new(LayoutParameters{zone_redundancy});
|
||||
cl.staged_parameters = Lww::<LayoutParameters>::new(LayoutParameters { zone_redundancy });
|
||||
}
|
||||
|
||||
#[test]
|
||||
|
@ -936,11 +1053,12 @@ mod tests {
|
|||
assert!(cl.check());
|
||||
assert!(matches!(check_against_naive(&cl), Ok(true)));
|
||||
|
||||
node_capacity_vec = vec![4000000, 4000000, 2000000, 7000000, 1000000, 9000000, 2000000, 10000, 2000000];
|
||||
node_capacity_vec = vec![
|
||||
4000000, 4000000, 2000000, 7000000, 1000000, 9000000, 2000000, 10000, 2000000,
|
||||
];
|
||||
update_layout(&mut cl, &node_id_vec, &node_capacity_vec, &node_zone_vec, 1);
|
||||
show_msg(&cl.calculate_partition_assignation().unwrap());
|
||||
assert!(cl.check());
|
||||
assert!(matches!(check_against_naive(&cl), Ok(true)));
|
||||
|
||||
}
|
||||
}
|
||||
|
|
|
@ -7,12 +7,11 @@ mod consul;
|
|||
#[cfg(feature = "kubernetes-discovery")]
|
||||
mod kubernetes;
|
||||
|
||||
pub mod layout;
|
||||
pub mod graph_algo;
|
||||
pub mod layout;
|
||||
pub mod ring;
|
||||
pub mod system;
|
||||
|
||||
|
||||
mod metrics;
|
||||
pub mod rpc_helper;
|
||||
|
||||
|
|
|
@ -565,7 +565,6 @@ impl System {
|
|||
return Err(Error::Message(msg));
|
||||
}
|
||||
|
||||
|
||||
let update_ring = self.update_ring.lock().await;
|
||||
let mut layout: ClusterLayout = self.ring.borrow().layout.clone();
|
||||
|
||||
|
|
Loading…
Reference in a new issue