Correction of a few bugs in the tests, modification of ClusterLayout::check
This commit is contained in:
Mendes
parent
7f3249a237
commit
bd842e1388
@ -182,7 +182,7 @@ impl Graph<FlowEdge>{
|
||||
//assignation, we shuffle the neighbours of the nodes. Hence,
|
||||
//the vertices do not consider their neighbours in the same order.
|
||||
self.shuffle_edges();
|
||||
|
||||
|
||||
//We run Dinic's max flow algorithm
|
||||
loop {
|
||||
//We build the level array from Dinic's algorithm.
|
||||
@ -206,7 +206,6 @@ impl Graph<FlowEdge>{
|
||||
//There is no residual flow
|
||||
break;
|
||||
}
|
||||
|
||||
//Now we run DFS respecting the level array
|
||||
let mut next_nbd = vec![0; nb_vertices];
|
||||
let mut lifo = VecDeque::new();
|
||||
@ -220,14 +219,12 @@ impl Graph<FlowEdge>{
|
||||
//The DFS reached the sink, we can add a
|
||||
//residual flow.
|
||||
lifo.pop_back();
|
||||
while !lifo.is_empty() {
|
||||
if let Some((id, _)) = lifo.pop_back() {
|
||||
let nbd = next_nbd[id];
|
||||
self.graph[id][nbd].flow += f as i32;
|
||||
let id_rev = self.graph[id][nbd].dest;
|
||||
let nbd_rev = self.graph[id][nbd].rev;
|
||||
self.graph[id_rev][nbd_rev].flow -= f as i32;
|
||||
}
|
||||
while let Some((id, _)) = lifo.pop_back() {
|
||||
let nbd = next_nbd[id];
|
||||
self.graph[id][nbd].flow += f as i32;
|
||||
let id_rev = self.graph[id][nbd].dest;
|
||||
let nbd_rev = self.graph[id][nbd].rev;
|
||||
self.graph[id_rev][nbd_rev].flow -= f as i32;
|
||||
}
|
||||
lifo.push_back((idsource, flow_upper_bound));
|
||||
continue;
|
||||
@ -243,10 +240,14 @@ impl Graph<FlowEdge>{
|
||||
continue;
|
||||
}
|
||||
//else we can try to send flow from id to its nbd
|
||||
let new_flow = min(f, self.graph[id][nbd].cap - 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 lvldest <= lvlid || new_flow == 0 {
|
||||
if lvldest <= lvlid {
|
||||
//We cannot send flow to nbd.
|
||||
next_nbd[id] += 1;
|
||||
continue;
|
||||
@ -266,7 +267,6 @@ impl Graph<FlowEdge>{
|
||||
// one needs to be present in the cost function.
|
||||
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);
|
||||
@ -364,6 +364,7 @@ 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.
|
||||
@ -401,8 +402,9 @@ fn cycles_of_1_forest(forest: &[Option<usize>]) -> Vec<Vec<usize>> {
|
||||
//We discovered an id that we explored at this iteration t.
|
||||
//It means we are on a cycle
|
||||
let mut cy = vec![id; 1];
|
||||
let id2 = id;
|
||||
while let Some(id2) = forest[id2] {
|
||||
let mut id2 = id;
|
||||
while let Some(id_next) = forest[id2] {
|
||||
id2 = id_next;
|
||||
if id2 != id {
|
||||
cy.push(id2);
|
||||
}
|
||||
@ -429,12 +431,5 @@ fn cycles_of_1_forest(forest: &[Option<usize>]) -> Vec<Vec<usize>> {
|
||||
mod tests {
|
||||
use super::*;
|
||||
|
||||
#[test]
|
||||
fn test_flow() {
|
||||
let left_vec = vec![3; 8];
|
||||
let right_vec = vec![0, 4, 8, 4, 8];
|
||||
//There are asserts in the function that computes the flow
|
||||
}
|
||||
|
||||
//maybe add tests relative to the matching optilization ?
|
||||
}
|
||||
|
||||
|
||||
@ -3,6 +3,7 @@ use std::collections::HashMap;
|
||||
use std::collections::HashSet;
|
||||
|
||||
use hex::ToHex;
|
||||
use itertools::Itertools;
|
||||
|
||||
use serde::{Deserialize, Serialize};
|
||||
|
||||
@ -185,7 +186,8 @@ impl ClusterLayout {
|
||||
pub fn get_node_capacity(&self, uuid : &Uuid) -> Result<u32,String> {
|
||||
match self.node_role(uuid) {
|
||||
Some(NodeRole{capacity : Some(cap), zone: _, tags: _}) => return Ok(*cap),
|
||||
_ => return Err("The Uuid does not correspond to a node present in the cluster or this node does not have a positive capacity.".to_string())
|
||||
_ => return Err("The Uuid does not correspond to a node present in the \
|
||||
cluster or this node does not have a positive capacity.".to_string())
|
||||
}
|
||||
}
|
||||
|
||||
@ -242,6 +244,47 @@ impl ClusterLayout {
|
||||
}
|
||||
}
|
||||
|
||||
//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();
|
||||
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."));
|
||||
if zones_of_p.unique().count() < self.zone_redundancy {
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
//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() {
|
||||
node_usage[*n as usize] += 1;
|
||||
}
|
||||
for n in 0..MAX_NODE_NUMBER {
|
||||
if node_usage[n] > 0 {
|
||||
let uuid = self.node_id_vec[n];
|
||||
if node_usage[n]*self.partition_size > self.get_node_capacity(&uuid)
|
||||
.expect("Critical Error"){
|
||||
return false;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
//Check that the partition size stored is the one computed by the asignation
|
||||
//algorithm.
|
||||
let cl2 = self.clone();
|
||||
let (_ , zone_to_id) = cl2.generate_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
|
||||
}
|
||||
|
||||
@ -267,7 +310,7 @@ impl ClusterLayout {
|
||||
self.zone_redundancy = redundancy;
|
||||
|
||||
let mut msg = Message::new();
|
||||
msg.push(format!("Computation of a new cluster layout where partitions are
|
||||
msg.push(format!("Computation of a new cluster layout where partitions are \
|
||||
replicated {} times on at least {} distinct zones.", replication, redundancy));
|
||||
|
||||
//We generate for once numerical ids for the zone, to use them as indices in the
|
||||
@ -276,16 +319,19 @@ impl ClusterLayout {
|
||||
|
||||
msg.push(format!("The cluster contains {} nodes spread over {} zones.",
|
||||
self.useful_nodes().len(), id_to_zone.len()));
|
||||
|
||||
|
||||
//We compute the optimal partition size
|
||||
//Capacities should be given in a unit so that partition size is at least 100.
|
||||
//In this case, integer rounding plays a marginal role in the percentages of
|
||||
//optimality.
|
||||
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
|
||||
optimal size of a partition is {}. In the previous layout, it used to
|
||||
msg.push(format!("Given the replication and redundancy constraint, the \
|
||||
optimal size of a partition is {}. In the previous layout, it used to \
|
||||
be {}.", partition_size, self.partition_size));
|
||||
}
|
||||
else {
|
||||
msg.push(format!("Given the replication and redundancy constraints, the
|
||||
msg.push(format!("Given the replication and redundancy constraints, the \
|
||||
optimal size of a partition is {}.", partition_size));
|
||||
}
|
||||
self.partition_size = partition_size;
|
||||
@ -293,13 +339,13 @@ impl ClusterLayout {
|
||||
//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)?;
|
||||
|
||||
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.push("".to_string());
|
||||
|
||||
//We update the layout structure
|
||||
self.update_ring_from_flow(id_to_zone.len() , &gflow)?;
|
||||
@ -321,7 +367,8 @@ impl ClusterLayout {
|
||||
.map(|(k, _, _)| *k).collect();
|
||||
|
||||
if new_non_gateway_nodes.len() > MAX_NODE_NUMBER {
|
||||
return Err(format!("There are more than {} non-gateway nodes in the new layout. This is not allowed.", MAX_NODE_NUMBER).to_string());
|
||||
return Err(format!("There are more than {} non-gateway nodes in the new \
|
||||
layout. This is not allowed.", MAX_NODE_NUMBER).to_string());
|
||||
}
|
||||
|
||||
let mut new_gateway_nodes: Vec<Uuid> = self.roles.items().iter()
|
||||
@ -346,7 +393,8 @@ impl ClusterLayout {
|
||||
return Ok(None);
|
||||
}
|
||||
if self.ring_assignation_data.len() != nb_partitions * self.replication_factor {
|
||||
return Err("The old assignation does not have a size corresponding to the old replication factor or the number of partitions.".to_string());
|
||||
return Err("The old assignation does not have a size corresponding to \
|
||||
the old replication factor or the number of partitions.".to_string());
|
||||
}
|
||||
|
||||
//We build a translation table between the uuid and new ids
|
||||
@ -384,7 +432,8 @@ impl ClusterLayout {
|
||||
|
||||
for uuid in self.node_id_vec.iter() {
|
||||
if self.roles.get(uuid) == None {
|
||||
return Err("The uuid was not found in the node roles (this should not happen, it might be a critical error).".to_string());
|
||||
return Err("The uuid was not found in the node roles (this should \
|
||||
not happen, it might be a critical error).".to_string());
|
||||
}
|
||||
match self.node_role(&uuid) {
|
||||
Some(r) => if !zone_to_id.contains_key(&r.zone) && r.capacity != None {
|
||||
@ -405,7 +454,8 @@ impl ClusterLayout {
|
||||
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("The storage capacity of he cluster is to small. It is impossible to store partitions of size 1.".to_string());
|
||||
return Err("The storage capacity of he cluster is to small. It is \
|
||||
impossible to store partitions of size 1.".to_string());
|
||||
}
|
||||
|
||||
let mut s_down = 1;
|
||||
@ -525,11 +575,12 @@ impl ClusterLayout {
|
||||
}
|
||||
|
||||
if self.ring_assignation_data.len() != NB_PARTITIONS*self.replication_factor {
|
||||
return Err("Critical Error : the association ring we produced does not have the right size.".to_string());
|
||||
return Err("Critical Error : the association ring we produced does not \
|
||||
have the right size.".to_string());
|
||||
}
|
||||
return Ok(());
|
||||
}
|
||||
|
||||
|
||||
|
||||
//This function returns a message summing up the partition repartition of the new
|
||||
//layout.
|
||||
@ -546,9 +597,16 @@ impl ClusterLayout {
|
||||
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(format!("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."));
|
||||
msg.push(format!("Recall that because of the replication, the actual available storage capacity is {} / {} = {}.", used_cap , self.replication_factor , used_cap/self.replication_factor as u32));
|
||||
msg.push(format!(""));
|
||||
msg.push(format!("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."));
|
||||
msg.push(format!("Recall that because of the replication, the actual available \
|
||||
storage capacity is {} / {} = {}.",
|
||||
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();
|
||||
@ -563,6 +621,16 @@ impl ClusterLayout {
|
||||
let pz_nodes = gflow.get_positive_flow_from(Vertex::PZ(p,z))?;
|
||||
if pz_nodes.len() > 0 {
|
||||
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])?]);
|
||||
}
|
||||
if !old_zones_of_p.contains(&z) {
|
||||
new_partitions_zone[z] += 1;
|
||||
}
|
||||
}
|
||||
}
|
||||
for vert in pz_nodes.iter() {
|
||||
if let Vertex::N(n) = *vert {
|
||||
@ -574,21 +642,17 @@ impl ClusterLayout {
|
||||
}
|
||||
}
|
||||
}
|
||||
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])?]);
|
||||
}
|
||||
if !old_zones_of_p.contains(&z) {
|
||||
new_partitions_zone[z] += 1;
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if *old_assoc_opt == None {
|
||||
new_partitions = stored_partitions.clone();
|
||||
new_partitions_zone = stored_partitions_zone.clone();
|
||||
}
|
||||
|
||||
//We display the statistics
|
||||
|
||||
msg.push(format!(""));
|
||||
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 \
|
||||
@ -608,16 +672,9 @@ impl ClusterLayout {
|
||||
.map(|n| stored_partitions[*n]).sum();
|
||||
msg.push(format!(""));
|
||||
|
||||
if *old_assoc_opt != None {
|
||||
msg.push(format!("Zone {}: {} distinct partitions stored ({} new, \
|
||||
msg.push(format!("Zone {}: {} distinct partitions stored ({} new, \
|
||||
{} partition copies) ", id_to_zone[z], stored_partitions_zone[z],
|
||||
new_partitions_zone[z], replicated_partitions));
|
||||
}
|
||||
else{
|
||||
msg.push(format!("Zone {}: {} distinct partitions stored ({} partition \
|
||||
copies) ",
|
||||
id_to_zone[z], stored_partitions_zone[z], replicated_partitions));
|
||||
}
|
||||
|
||||
let available_cap_z : u32 = self.partition_size*replicated_partitions as u32;
|
||||
let mut total_cap_z = 0;
|
||||
@ -625,18 +682,17 @@ impl ClusterLayout {
|
||||
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}%).",
|
||||
msg.push(format!(" Available capacity / Total capacity: {}/{} ({:.1}%).",
|
||||
available_cap_z, total_cap_z, percent_cap_z));
|
||||
msg.push(format!(""));
|
||||
|
||||
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) ; \
|
||||
msg.push(format!(" Node {}: {} partitions ({} new) ; \
|
||||
available/total capacity: {} / {} ({:.1}%) ; tags:{}",
|
||||
&self.node_id_vec[*n].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 ,
|
||||
@ -654,16 +710,14 @@ impl ClusterLayout {
|
||||
#[cfg(test)]
|
||||
mod tests {
|
||||
use super::*;
|
||||
use itertools::Itertools;
|
||||
|
||||
use std::io::*;
|
||||
// use itertools::Itertools;
|
||||
/*
|
||||
fn check_assignation(cl: &ClusterLayout) {
|
||||
//Check that input data has the right format
|
||||
let nb_partitions = 1usize << PARTITION_BITS;
|
||||
assert!([1, 2, 3].contains(&cl.replication_factor));
|
||||
assert!(cl.ring_assignation_data.len() == nb_partitions * cl.replication_factor);
|
||||
|
||||
let (node_zone, node_capacity) = cl.get_node_zone_capacity();
|
||||
|
||||
//Check that is is a correct assignation with zone redundancy
|
||||
let rf = cl.replication_factor;
|
||||
for i in 0..nb_partitions {
|
||||
@ -743,6 +797,13 @@ mod tests {
|
||||
}
|
||||
}
|
||||
}
|
||||
*/
|
||||
|
||||
fn show_msg(msg : &Message) {
|
||||
for s in msg.iter(){
|
||||
println!("{}",s);
|
||||
}
|
||||
}
|
||||
|
||||
fn update_layout(
|
||||
cl: &mut ClusterLayout,
|
||||
@ -769,7 +830,8 @@ mod tests {
|
||||
|
||||
#[test]
|
||||
fn test_assignation() {
|
||||
let mut node_id_vec = vec![1, 2, 3];
|
||||
std::io::stdout().flush().ok().expect("Could not flush stdout");
|
||||
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"]
|
||||
.into_iter()
|
||||
@ -782,14 +844,16 @@ mod tests {
|
||||
roles: LwwMap::new(),
|
||||
|
||||
replication_factor: 3,
|
||||
zone_redundancy: 1,
|
||||
partition_size: 0,
|
||||
ring_assignation_data: vec![],
|
||||
version: 0,
|
||||
staging: LwwMap::new(),
|
||||
staging_hash: sha256sum(&[1; 32]),
|
||||
staging_hash: blake2sum(&rmp_to_vec_all_named(&LwwMap::<Uuid, NodeRoleV>::new()).unwrap()[..]),
|
||||
};
|
||||
update_layout(&mut cl, &node_id_vec, &node_capacity_vec, &node_zone_vec);
|
||||
cl.calculate_partition_assignation();
|
||||
check_assignation(&cl);
|
||||
show_msg(&cl.calculate_partition_assignation(3,3).unwrap());
|
||||
assert!(cl.check());
|
||||
|
||||
node_id_vec = vec![1, 2, 3, 4, 5, 6, 7, 8, 9];
|
||||
node_capacity_vec = vec![4000, 1000, 1000, 3000, 1000, 1000, 2000, 10000, 2000];
|
||||
@ -798,17 +862,18 @@ mod tests {
|
||||
.map(|x| x.to_string())
|
||||
.collect();
|
||||
update_layout(&mut cl, &node_id_vec, &node_capacity_vec, &node_zone_vec);
|
||||
cl.calculate_partition_assignation();
|
||||
check_assignation(&cl);
|
||||
show_msg(&cl.calculate_partition_assignation(3,3).unwrap());
|
||||
assert!(cl.check());
|
||||
|
||||
node_capacity_vec = vec![4000, 1000, 2000, 7000, 1000, 1000, 2000, 10000, 2000];
|
||||
update_layout(&mut cl, &node_id_vec, &node_capacity_vec, &node_zone_vec);
|
||||
cl.calculate_partition_assignation();
|
||||
check_assignation(&cl);
|
||||
show_msg(&cl.calculate_partition_assignation(3,3).unwrap());
|
||||
assert!(cl.check());
|
||||
|
||||
node_capacity_vec = vec![4000, 4000, 2000, 7000, 1000, 9000, 2000, 10, 2000];
|
||||
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);
|
||||
cl.calculate_partition_assignation();
|
||||
check_assignation(&cl);
|
||||
show_msg(&cl.calculate_partition_assignation(3,1).unwrap());
|
||||
assert!(cl.check());
|
||||
|
||||
}
|
||||
}
|
||||
|
||||
Loading…
Reference in New Issue
Block a user