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-rw-r--r--src/rpc/graph_algo.rs41
-rw-r--r--src/rpc/layout.rs173
2 files changed, 137 insertions, 77 deletions
diff --git a/src/rpc/graph_algo.rs b/src/rpc/graph_algo.rs
index 1a809b80..a5a1e4ba 100644
--- a/src/rpc/graph_algo.rs
+++ b/src/rpc/graph_algo.rs
@@ -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 ?
}
+
diff --git a/src/rpc/layout.rs b/src/rpc/layout.rs
index ff60ce98..a878f19c 100644
--- a/src/rpc/layout.rs
+++ b/src/rpc/layout.rs
@@ -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());
+
}
}