use std::collections::HashMap; use std::collections::HashSet; use std::convert::TryInto; use bytesize::ByteSize; use itertools::Itertools; use garage_util::crdt::LwwMap; use garage_util::data::*; use garage_util::error::*; use super::graph_algo::*; use super::schema::*; use super::*; // The Message type will be used to collect information on the algorithm. pub type Message = Vec; impl LayoutVersion { pub fn new(replication_factor: usize) -> Self { // We set the default zone redundancy to be Maximum, meaning that the maximum // possible value will be used depending on the cluster topology let parameters = LayoutParameters { zone_redundancy: ZoneRedundancy::Maximum, }; LayoutVersion { version: 0, replication_factor, partition_size: 0, roles: LwwMap::new(), node_id_vec: Vec::new(), ring_assignment_data: Vec::new(), parameters, } } // ===================== accessors ====================== /// Returns a list of IDs of nodes that currently have /// a role in the cluster pub fn node_ids(&self) -> &[Uuid] { &self.node_id_vec[..] } pub fn num_nodes(&self) -> usize { self.node_id_vec.len() } /// Returns the role of a node in the layout pub fn node_role(&self, node: &Uuid) -> Option<&NodeRole> { match self.roles.get(node) { Some(NodeRoleV(Some(v))) => Some(v), _ => None, } } /// 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 { 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(), )), } } /// Returns the number of partitions associated to this node in the ring pub fn get_node_usage(&self, uuid: &Uuid) -> Result { for (i, id) in self.node_id_vec.iter().enumerate() { if id == uuid { let mut count = 0; for nod in self.ring_assignment_data.iter() { if i as u8 == *nod { count += 1 } } return Ok(count); } } 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(), )) } /// Get the partition in which data would fall on pub fn partition_of(&self, position: &Hash) -> Partition { let top = u16::from_be_bytes(position.as_slice()[0..2].try_into().unwrap()); top >> (16 - PARTITION_BITS) } /// Get the list of partitions and the first hash of a partition key that would fall in it pub fn partitions(&self) -> impl Iterator + '_ { (0..(1 << PARTITION_BITS)).map(|i| { let top = (i as u16) << (16 - PARTITION_BITS); let mut location = [0u8; 32]; location[..2].copy_from_slice(&u16::to_be_bytes(top)[..]); (i as u16, Hash::from(location)) }) } /// Return the n servers in which data for this hash should be replicated pub fn nodes_of(&self, position: &Hash, n: usize) -> Vec { assert_eq!(n, self.replication_factor); let data = &self.ring_assignment_data; if data.len() != self.replication_factor * (1 << PARTITION_BITS) { warn!("Ring not yet ready, read/writes will be lost!"); return vec![]; } let partition_idx = self.partition_of(position) as usize; let partition_start = partition_idx * self.replication_factor; let partition_end = (partition_idx + 1) * self.replication_factor; let partition_nodes = &data[partition_start..partition_end]; partition_nodes .iter() .map(|i| self.node_id_vec[*i as usize]) .collect::>() } // ===================== internal information extractors ====================== /// Returns the uuids of the non_gateway nodes in self.node_id_vec. pub(crate) fn nongateway_nodes(&self) -> impl Iterator + '_ { self.node_id_vec .iter() .copied() .filter(move |uuid| match self.node_role(uuid) { Some(role) if role.capacity.is_some() => true, _ => false, }) } /// Given a node uuids, this function returns the label of its zone fn get_node_zone(&self, uuid: &Uuid) -> Result<&str, Error> { match self.node_role(uuid) { Some(role) => Ok(&role.zone), _ => Err(Error::Message( "The Uuid does not correspond to a node present in the cluster.".into(), )), } } /// Returns the sum of capacities of non gateway nodes in the cluster fn get_total_capacity(&self) -> Result { let mut total_capacity = 0; for uuid in self.nongateway_nodes() { total_capacity += self.get_node_capacity(&uuid)?; } Ok(total_capacity) } /// Returns the effective value of the zone_redundancy parameter fn effective_zone_redundancy(&self) -> usize { match self.parameters.zone_redundancy { ZoneRedundancy::AtLeast(v) => v, ZoneRedundancy::Maximum => { let n_zones = self .roles .items() .iter() .filter_map(|(_, _, role)| role.0.as_ref().map(|x| x.zone.as_str())) .collect::>() .len(); std::cmp::min(n_zones, self.replication_factor) } } } /// Check a cluster layout for internal consistency /// (assignment, roles, parameters, partition size) /// returns true if consistent, false if error pub fn check(&self) -> Result<(), String> { // Check that node_id_vec contains the correct list of nodes let mut expected_nodes = self .roles .items() .iter() .filter(|(_, _, v)| v.0.is_some()) .map(|(id, _, _)| *id) .collect::>(); expected_nodes.sort(); let mut node_id_vec = self.node_id_vec.clone(); node_id_vec.sort(); if expected_nodes != node_id_vec { return Err(format!("node_id_vec does not contain the correct set of nodes\nnode_id_vec: {:?}\nexpected: {:?}", node_id_vec, expected_nodes)); } // Check that the assignment data has the correct length let expected_assignment_data_len = (1 << PARTITION_BITS) * self.replication_factor; if self.ring_assignment_data.len() != expected_assignment_data_len { return Err(format!( "ring_assignment_data has incorrect length {} instead of {}", self.ring_assignment_data.len(), expected_assignment_data_len )); } // Check that the assigned nodes are correct identifiers // of nodes that are assigned a role // and that role is not the role of a gateway nodes for x in self.ring_assignment_data.iter() { if *x as usize >= self.node_id_vec.len() { return Err(format!( "ring_assignment_data contains invalid node id {}", *x )); } let node = self.node_id_vec[*x as usize]; match self.roles.get(&node) { Some(NodeRoleV(Some(x))) if x.capacity.is_some() => (), _ => return Err("ring_assignment_data contains id of a gateway node".into()), } } // Check that every partition is associated to distinct nodes let zone_redundancy = self.effective_zone_redundancy(); let rf = self.replication_factor; for p in 0..(1 << PARTITION_BITS) { let nodes_of_p = self.ring_assignment_data[rf * p..rf * (p + 1)].to_vec(); if nodes_of_p.iter().unique().count() != rf { return Err(format!("partition does not contain {} unique node ids", rf)); } // 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.") }) .collect::>(); if zones_of_p.iter().unique().count() < zone_redundancy { return Err(format!( "nodes of partition are in less than {} distinct zones", zone_redundancy )); } } // 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_assignment_data.iter() { node_usage[*n as usize] += 1; } for (n, usage) in node_usage.iter().enumerate() { if *usage > 0 { let uuid = self.node_id_vec[n]; let partusage = usage * self.partition_size; let nodecap = self.get_node_capacity(&uuid).unwrap(); if partusage > nodecap { return Err(format!( "node usage ({}) is bigger than node capacity ({})", usage * self.partition_size, nodecap )); } } } // Check that the partition size stored is the one computed by the asignation // algorithm. let cl2 = self.clone(); let (_, zone_to_id) = cl2.generate_nongateway_zone_ids().unwrap(); match cl2.compute_optimal_partition_size(&zone_to_id, zone_redundancy) { Ok(s) if s != self.partition_size => { return Err(format!( "partition_size ({}) is different than optimal value ({})", self.partition_size, s )) } Err(e) => return Err(format!("could not calculate optimal partition size: {}", e)), _ => (), } Ok(()) } // ================== updates to layout, internals =================== /// This function calculates a new partition-to-node assignment. /// The computed assignment respects the node replication factor /// and the zone redundancy parameter It maximizes the capacity of a /// partition (assuming all partitions have the same size). /// Among such optimal assignment, it minimizes the distance to /// the former assignment (if any) to minimize the amount of /// data to be moved. /// Staged role changes must be merged with nodes roles before calling this function, /// hence it must only be called from apply_staged_changes() and hence is not public. pub(crate) fn calculate_partition_assignment(&mut self) -> Result { // We update the node ids, since the node role list might have changed with the // changes in the layout. We retrieve the old_assignment reframed with new ids let old_assignment_opt = self.update_node_id_vec()?; let zone_redundancy = self.effective_zone_redundancy(); let mut msg = Message::new(); msg.push("==== COMPUTATION OF A NEW PARTITION ASSIGNATION ====".into()); msg.push("".into()); msg.push(format!( "Partitions are \ replicated {} times on at least {} distinct zones.", self.replication_factor, zone_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_nongateway_zone_ids()?; let nb_nongateway_nodes = self.nongateway_nodes().count(); if nb_nongateway_nodes < self.replication_factor { return Err(Error::Message(format!( "The number of nodes with positive \ capacity ({}) is smaller than the replication factor ({}).", nb_nongateway_nodes, self.replication_factor ))); } if id_to_zone.len() < zone_redundancy { return Err(Error::Message(format!( "The number of zones with non-gateway \ nodes ({}) is smaller than the redundancy parameter ({})", id_to_zone.len(), zone_redundancy ))); } // 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, zone_redundancy)?; msg.push("".into()); if old_assignment_opt.is_some() { msg.push(format!( "Optimal partition size: {} ({} in previous layout)", ByteSize::b(partition_size).to_string_as(false), ByteSize::b(self.partition_size).to_string_as(false) )); } else { msg.push(format!( "Optimal partition size: {}", ByteSize::b(partition_size).to_string_as(false) )); } // We write the partition size. self.partition_size = partition_size; if partition_size < 100 { msg.push( "WARNING: The partition size is low (< 100), make sure the capacities of your nodes are correct and are of at least a few MB" .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_assignment_opt, zone_redundancy)?; if let Some(assoc) = &old_assignment_opt { // We minimize the distance to the previous assignment. self.minimize_rebalance_load(&mut gflow, &zone_to_id, assoc)?; } // We display statistics of the computation msg.extend(self.output_stat(&gflow, &old_assignment_opt, &zone_to_id, &id_to_zone)?); // We update the layout structure self.update_ring_from_flow(id_to_zone.len(), &gflow)?; if let Err(e) = self.check() { return Err(Error::Message( format!("Layout check returned an error: {}\nOriginal result of computation: <<<<\n{}\n>>>>", e, msg.join("\n")) )); } Ok(msg) } /// The LwwMap of node roles might have changed. This function updates the node_id_vec /// and returns the assignment given by ring, with the new indices of the nodes, and /// None if the node is not present anymore. /// We work with the assumption that only this function and calculate_new_assignment /// do modify assignment_ring and node_id_vec. fn update_node_id_vec(&mut self) -> Result>>, 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 new_non_gateway_nodes: Vec = self .roles .items() .iter() .filter(|(_, _, v)| matches!(&v.0, Some(r) if r.capacity.is_some())) .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 ))); } let new_gateway_nodes: Vec = self .roles .items() .iter() .filter(|(_, _, v)| matches!(v, NodeRoleV(Some(r)) if r.capacity.is_none())) .map(|(k, _, _)| *k) .collect(); let mut new_node_id_vec = Vec::::new(); new_node_id_vec.extend(new_non_gateway_nodes); new_node_id_vec.extend(new_gateway_nodes); let old_node_id_vec = self.node_id_vec.clone(); self.node_id_vec = new_node_id_vec.clone(); // (2) We retrieve the old association // We rewrite the old association with the new indices. We only consider partition // to node assignments where the node is still in use. if self.ring_assignment_data.is_empty() { // This is a new association return Ok(None); } if self.ring_assignment_data.len() != NB_PARTITIONS * self.replication_factor { return Err(Error::Message( "The old assignment 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 let mut uuid_to_new_id = HashMap::::new(); // 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); } let mut old_assignment = vec![Vec::::new(); NB_PARTITIONS]; let rf = self.replication_factor; for (p, old_assign_p) in old_assignment.iter_mut().enumerate() { for old_id in &self.ring_assignment_data[p * rf..(p + 1) * rf] { let uuid = old_node_id_vec[*old_id as usize]; if uuid_to_new_id.contains_key(&uuid) { old_assign_p.push(uuid_to_new_id[&uuid]); } } } // We write the ring self.ring_assignment_data = Vec::::new(); Ok(Some(old_assignment)) } /// This function generates ids for the zone of the nodes appearing in /// self.node_id_vec. fn generate_nongateway_zone_ids(&self) -> Result<(Vec, HashMap), Error> { let mut id_to_zone = Vec::::new(); let mut zone_to_id = HashMap::::new(); let nongateway_nodes = self.nongateway_nodes().collect::>(); for uuid in nongateway_nodes.iter() { let r = self.node_role(uuid).unwrap(); if !zone_to_id.contains_key(&r.zone) && r.capacity.is_some() { zone_to_id.insert(r.zone.clone(), id_to_zone.len()); id_to_zone.push(r.zone.clone()); } } Ok((id_to_zone, zone_to_id)) } /// This function computes by dichotomy the largest realizable partition size, given /// the layout roles and parameters. fn compute_optimal_partition_size( &self, zone_to_id: &HashMap, zone_redundancy: usize, ) -> Result { let empty_set = HashSet::<(usize, usize)>::new(); let mut g = self.generate_flow_graph(1, zone_to_id, &empty_set, zone_redundancy)?; g.compute_maximal_flow()?; if g.get_flow_value()? < (NB_PARTITIONS * self.replication_factor) as i64 { 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, zone_redundancy, )?; g.compute_maximal_flow()?; if g.get_flow_value()? < (NB_PARTITIONS * self.replication_factor) as i64 { 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 { let mut vertices = vec![Vertex::Source, Vertex::Sink]; for p in 0..NB_PARTITIONS { vertices.push(Vertex::Pup(p)); vertices.push(Vertex::Pdown(p)); for z in 0..nb_zones { vertices.push(Vertex::PZ(p, z)); } } for n in 0..nb_nodes { vertices.push(Vertex::N(n)); } vertices } /// Generates the graph to compute the maximal flow corresponding to the optimal /// partition assignment. /// exclude_assoc is the set of (partition, node) association that we are forbidden /// to use (hence we do not add the corresponding edge to the graph). This parameter /// is used to compute a first flow that uses only edges appearing in the previous /// assignment. This produces a solution that heuristically should be close to the /// previous one. fn generate_flow_graph( &self, partition_size: u64, zone_to_id: &HashMap, exclude_assoc: &HashSet<(usize, usize)>, zone_redundancy: usize, ) -> Result, Error> { let vertices = LayoutVersion::generate_graph_vertices( zone_to_id.len(), self.nongateway_nodes().count(), ); let mut g = Graph::::new(&vertices); let nb_zones = zone_to_id.len(); for p in 0..NB_PARTITIONS { g.add_edge(Vertex::Source, Vertex::Pup(p), zone_redundancy as u64)?; g.add_edge( Vertex::Source, Vertex::Pdown(p), (self.replication_factor - zone_redundancy) as u64, )?; 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 u64, )?; } } for n in 0..self.nongateway_nodes().count() { 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 / partition_size)?; for p in 0..NB_PARTITIONS { if !exclude_assoc.contains(&(p, n)) { g.add_edge(Vertex::PZ(p, node_zone), Vertex::N(n), 1)?; } } } Ok(g) } /// This function computes a first optimal assignment (in the form of a flow graph). fn compute_candidate_assignment( &self, zone_to_id: &HashMap, prev_assign_opt: &Option>>, zone_redundancy: usize, ) -> Result, Error> { // We list the (partition,node) associations that are not used in the // previous assignment let mut exclude_edge = HashSet::<(usize, usize)>::new(); if let Some(prev_assign) = prev_assign_opt { let nb_nodes = self.nongateway_nodes().count(); for (p, prev_assign_p) in prev_assign.iter().enumerate() { for n in 0..nb_nodes { exclude_edge.insert((p, n)); } for n in prev_assign_p.iter() { exclude_edge.remove(&(p, *n)); } } } // We compute the best flow using only the edges used in the previous assignment let mut g = self.generate_flow_graph( self.partition_size, zone_to_id, &exclude_edge, zone_redundancy, )?; g.compute_maximal_flow()?; // We add the excluded edges and compute the maximal flow with the full graph. // The algorithm is such that it will start with the flow that we just computed // and find ameliorating paths from that. 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.compute_maximal_flow()?; Ok(g) } /// This function updates the flow graph gflow to minimize the distance between /// its corresponding assignment and the previous one fn minimize_rebalance_load( &self, gflow: &mut Graph, zone_to_id: &HashMap, prev_assign: &[Vec], ) -> Result<(), Error> { // We define a cost function on the edges (pairs of vertices) corresponding // to the distance between the two assignments. let mut cost = CostFunction::new(); for (p, assoc_p) in prev_assign.iter().enumerate() { for n in assoc_p.iter() { 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); } } // We compute the maximal length of a simple path in gflow. It is used in the // Bellman-Ford algorithm in optimize_flow_with_cost to set the number // of iterations. let nb_nodes = self.nongateway_nodes().count(); let path_length = 4 * nb_nodes; gflow.optimize_flow_with_cost(&cost, path_length)?; Ok(()) } /// This function updates the assignment ring from the flow graph. fn update_ring_from_flow( &mut self, nb_zones: usize, gflow: &Graph, ) -> Result<(), Error> { self.ring_assignment_data = Vec::::new(); for p in 0..NB_PARTITIONS { for z in 0..nb_zones { let assoc_vertex = gflow.get_positive_flow_from(Vertex::PZ(p, z))?; for vertex in assoc_vertex.iter() { if let Vertex::N(n) = vertex { self.ring_assignment_data.push((*n).try_into().unwrap()); } } } } if self.ring_assignment_data.len() != NB_PARTITIONS * self.replication_factor { return Err(Error::Message( "Critical Error : the association ring we produced does not \ have the right size." .into(), )); } Ok(()) } /// This function returns a message summing up the partition repartition of the new /// layout, and other statistics of the partition assignment computation. fn output_stat( &self, gflow: &Graph, prev_assign_opt: &Option>>, zone_to_id: &HashMap, id_to_zone: &[String], ) -> Result { let mut msg = Message::new(); let used_cap = self.partition_size * NB_PARTITIONS as u64 * self.replication_factor as u64; let total_cap = self.get_total_capacity()?; let percent_cap = 100.0 * (used_cap as f32) / (total_cap as f32); msg.push(format!( "Usable capacity / total cluster capacity: {} / {} ({:.1} %)", ByteSize::b(used_cap).to_string_as(false), ByteSize::b(total_cap).to_string_as(false), percent_cap )); msg.push(format!( "Effective capacity (replication factor {}): {}", self.replication_factor, ByteSize::b(used_cap / self.replication_factor as u64).to_string_as(false) )); if percent_cap < 80. { msg.push("".into()); msg.push( "If the percentage is too low, it might be that the \ cluster topology and redundancy constraints are forcing the use of nodes/zones with small \ storage capacities." .into(), ); msg.push( "You might want to move storage capacity between zones or relax the redundancy constraint." .into(), ); msg.push( "See the detailed statistics below and look for saturated nodes/zones.".into(), ); } // We define and fill in the following tables let storing_nodes = self.nongateway_nodes().collect::>(); let mut new_partitions = vec![0; storing_nodes.len()]; let mut stored_partitions = vec![0; storing_nodes.len()]; let mut new_partitions_zone = vec![0; id_to_zone.len()]; let mut stored_partitions_zone = vec![0; id_to_zone.len()]; 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))?; if !pz_nodes.is_empty() { stored_partitions_zone[z] += 1; if let Some(prev_assign) = prev_assign_opt { let mut old_zones_of_p = Vec::::new(); for n in prev_assign[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 { stored_partitions[n] += 1; if let Some(prev_assign) = prev_assign_opt { if !prev_assign[p].contains(&n) { new_partitions[n] += 1; } } } } } } if prev_assign_opt.is_none() { new_partitions = stored_partitions.clone(); //new_partitions_zone = stored_partitions_zone.clone(); } // We display the statistics msg.push("".into()); if prev_assign_opt.is_some() { 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()); } let mut table = vec![]; for z in 0..id_to_zone.len() { let mut nodes_of_z = Vec::::new(); 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(); table.push(format!( "{}\tTags\tPartitions\tCapacity\tUsable capacity", id_to_zone[z] )); let available_cap_z: u64 = self.partition_size * replicated_partitions as u64; 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); for n in nodes_of_z.iter() { let available_cap_n = stored_partitions[*n] as u64 * 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(""))?.tags_string(); table.push(format!( " {:?}\t{}\t{} ({} new)\t{}\t{} ({:.1}%)", self.node_id_vec[*n], tags_n, stored_partitions[*n], new_partitions[*n], ByteSize::b(total_cap_n).to_string_as(false), ByteSize::b(available_cap_n).to_string_as(false), (available_cap_n as f32) / (total_cap_n as f32) * 100.0, )); } table.push(format!( " TOTAL\t\t{} ({} unique)\t{}\t{} ({:.1}%)", replicated_partitions, stored_partitions_zone[z], //new_partitions_zone[z], ByteSize::b(total_cap_z).to_string_as(false), ByteSize::b(available_cap_z).to_string_as(false), percent_cap_z )); table.push("".into()); } msg.push(format_table::format_table_to_string(table)); Ok(msg) } } // ==================================================================================== #[cfg(test)] mod tests { 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 assignment // was not optimal. The naive algorithm is the following : // - we compute the max number of partitions associated to every node, capped at the // partition number. It gives the number of tokens of every node. // - every zone has a number of tokens equal to the sum of the tokens of its nodes. // - we cycle over the partitions and associate zone tokens while respecting the // zone redundancy constraint. // NOTE: the naive algorithm is not optimal. Counter example: // take nb_partition = 3 ; replication_factor = 5; redundancy = 4; // 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: &LayoutVersion) -> Result { let over_size = cl.partition_size + 1; let mut zone_token = HashMap::::new(); let (zones, zone_to_id) = cl.generate_nongateway_zone_ids()?; if zones.is_empty() { return Ok(false); } for z in zones.iter() { zone_token.insert(z.clone(), 0); } for uuid in cl.nongateway_nodes() { 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), ); } // 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() { id_zone_token[zone_to_id[z]] = *t; } let mut nb_token = vec![0; NB_PARTITIONS]; let mut last_zone = vec![zones.len(); NB_PARTITIONS]; let mut curr_zone = 0; let redundancy = cl.effective_zone_redundancy(); 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) { curr_zone += 1; if curr_zone >= zones.len() { return Ok(true); } } id_zone_token[curr_zone] -= 1; if last_zone[p] != curr_zone { nb_token[p] += 1; last_zone[p] = curr_zone; } } } return Ok(false); } fn show_msg(msg: &Message) { for s in msg.iter() { println!("{}", s); } } fn update_layout( cl: &mut LayoutVersion, node_id_vec: &Vec, node_capacity_vec: &Vec, node_zone_vec: &Vec, zone_redundancy: usize, ) { for i in 0..node_id_vec.len() { if let Some(x) = FixedBytes32::try_from(&[i as u8; 32]) { cl.node_id_vec.push(x); } let update = cl.staging_roles.update_mutator( cl.node_id_vec[i], NodeRoleV(Some(NodeRole { zone: (node_zone_vec[i].to_string()), capacity: (Some(node_capacity_vec[i])), tags: (vec![]), })), ); cl.staging_roles.merge(&update); } cl.staging_parameters.update(LayoutParameters { zone_redundancy: ZoneRedundancy::AtLeast(zone_redundancy), }); cl.staging_hash = cl.calculate_staging_hash(); } #[test] fn test_assignment() { let mut node_id_vec = vec![1, 2, 3]; let mut node_capacity_vec = vec![4000, 1000, 2000]; let mut node_zone_vec = vec!["A", "B", "C"] .into_iter() .map(|x| x.to_string()) .collect(); let mut cl = LayoutVersion::new(3); update_layout(&mut cl, &node_id_vec, &node_capacity_vec, &node_zone_vec, 3); let v = cl.version; let (mut cl, msg) = cl.apply_staged_changes(Some(v + 1)).unwrap(); show_msg(&msg); assert_eq!(cl.check(), Ok(())); assert!(matches!(check_against_naive(&cl), Ok(true))); 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]; node_zone_vec = vec!["A", "B", "C", "C", "C", "B", "G", "H", "I"] .into_iter() .map(|x| x.to_string()) .collect(); update_layout(&mut cl, &node_id_vec, &node_capacity_vec, &node_zone_vec, 2); let v = cl.version; let (mut cl, msg) = cl.apply_staged_changes(Some(v + 1)).unwrap(); show_msg(&msg); assert_eq!(cl.check(), Ok(())); assert!(matches!(check_against_naive(&cl), Ok(true))); 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, 3); let v = cl.version; let (mut cl, msg) = cl.apply_staged_changes(Some(v + 1)).unwrap(); show_msg(&msg); assert_eq!(cl.check(), Ok(())); assert!(matches!(check_against_naive(&cl), Ok(true))); 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); let v = cl.version; let (cl, msg) = cl.apply_staged_changes(Some(v + 1)).unwrap(); show_msg(&msg); assert_eq!(cl.check(), Ok(())); assert!(matches!(check_against_naive(&cl), Ok(true))); } }