src/rpc/graph_algo.rs

@@ -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();
@@ -220,15 +219,13 @@ impl Graph<FlowEdge>{
                     //The DFS reached the sink, we can add a
                     //residual flow.
                     lifo.pop_back();
-                    while !lifo.is_empty() {
+                    while let Some((id, _)) = lifo.pop_back() {
-                        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;
                     }
-                    }
                     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;
+            let mut id2 = id;
-            while let Some(id2) = forest[id2] {
+            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 ?
-}

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 
@@ -278,14 +321,17 @@ impl ClusterLayout {
                          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 
+            msg.push(format!("Given the replication and redundancy constraint, the \
-                optimal size of a partition is {}. In the previous layout, it used to 
+                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;
@@ -525,7 +575,8 @@ 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(());
     }
@@ -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. 
+        msg.push(format!(""));
-        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!("If the percentage is to low, it might be that the \
-        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));
+        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();
@@ -563,17 +621,6 @@ impl ClusterLayout {
                 let pz_nodes = gflow.get_positive_flow_from(Vertex::PZ(p,z))?;
                 if pz_nodes.len() > 0 {
                     stored_partitions_zone[z] += 1;
-                }
-                for vert in pz_nodes.iter() {
-                    if let Vertex::N(n) = *vert {
-                        stored_partitions[n] += 1;
-                        if let Some(old_assoc) = old_assoc_opt {
-                            if !old_assoc[p].contains(&n) {
-                                new_partitions[n] += 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() {
@@ -585,10 +632,27 @@ impl ClusterLayout {
                         }
                     }
                 }
+                for vert in pz_nodes.iter() {
+                    if let Vertex::N(n) = *vert {
+                        stored_partitions[n] += 1;
+                        if let Some(old_assoc) = old_assoc_opt {
+                            if !old_assoc[p].contains(&n) {
+                                new_partitions[n] += 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, \
                 {} 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;
@@ -627,7 +684,6 @@ impl ClusterLayout {
             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));
-            msg.push(format!(""));
             
             for n in nodes_of_z.iter() {
                 let available_cap_n = stored_partitions[*n] as u32 *self.partition_size;
@@ -636,7 +692,7 @@ impl ClusterLayout {
                                 .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().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,
@@ -769,6 +830,7 @@ mod tests {
 
 	#[test]
 	fn test_assignation() {
+        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"]
@@ -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();
+		show_msg(&cl.calculate_partition_assignation(3,3).unwrap());
-		check_assignation(&cl);
+		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();
+		show_msg(&cl.calculate_partition_assignation(3,3).unwrap());
-		check_assignation(&cl);
+		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();
+		show_msg(&cl.calculate_partition_assignation(3,3).unwrap());
-		check_assignation(&cl);
+		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();
+		show_msg(&cl.calculate_partition_assignation(3,1).unwrap());
-		check_assignation(&cl);
+		assert!(cl.check());
+
 	}
 }