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Diffstat (limited to 'src/rpc/layout/version.rs')
| -rw-r--r-- | src/rpc/layout/version.rs | 846 |
1 files changed, 846 insertions, 0 deletions
diff --git a/src/rpc/layout/version.rs b/src/rpc/layout/version.rs new file mode 100644 index 00000000..ee4b2821 --- /dev/null +++ b/src/rpc/layout/version.rs @@ -0,0 +1,846 @@ +use std::collections::HashMap; +use std::collections::HashSet; +use std::convert::TryInto; + +use bytesize::ByteSize; +use itertools::Itertools; + +use garage_util::crdt::{Crdt, LwwMap}; +use garage_util::data::*; +use garage_util::error::*; + +use super::graph_algo::*; +use super::*; + +// The Message type will be used to collect information on the algorithm. +pub type Message = Vec<String>; + +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(), + nongateway_node_count: 0, + ring_assignment_data: Vec::new(), + parameters, + } + } + + // ===================== accessors ====================== + + /// Returns a list of IDs of nodes that have a role in this + /// version of the cluster layout, including gateway nodes + pub fn all_nodes(&self) -> &[Uuid] { + &self.node_id_vec[..] + } + + /// Returns a list of IDs of nodes that have a storage capacity + /// assigned in this version of the cluster layout + pub fn nongateway_nodes(&self) -> &[Uuid] { + &self.node_id_vec[..self.nongateway_node_count] + } + + /// Returns the role of a node in the layout, if it has one + pub fn node_role(&self, node: &Uuid) -> Option<&NodeRole> { + match self.roles.get(node) { + Some(NodeRoleV(Some(v))) => Some(v), + _ => None, + } + } + + /// Returns the capacity of a node in the layout, if it has one + pub fn get_node_capacity(&self, uuid: &Uuid) -> Option<u64> { + match self.node_role(uuid) { + Some(NodeRole { + capacity: Some(cap), + zone: _, + tags: _, + }) => Some(*cap), + _ => None, + } + } + + /// Given a node uuids, this function returns the label of its zone if it has one + pub fn get_node_zone(&self, uuid: &Uuid) -> Option<&str> { + match self.node_role(uuid) { + Some(role) => Some(&role.zone), + _ => None, + } + } + + /// Returns the number of partitions associated to this node in the ring + pub fn get_node_usage(&self, uuid: &Uuid) -> Result<usize, Error> { + 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<Item = (Partition, Hash)> + '_ { + (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) -> impl Iterator<Item = Uuid> + '_ { + assert_eq!(n, self.replication_factor); + + let data = &self.ring_assignment_data; + + let partition_nodes = if data.len() == self.replication_factor * (1 << PARTITION_BITS) { + 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; + &data[partition_start..partition_end] + } else { + warn!("Ring not yet ready, read/writes will be lost!"); + &[] + }; + + partition_nodes + .iter() + .map(move |i| self.node_id_vec[*i as usize]) + } + + // ===================== internal information extractors ====================== + + pub(crate) fn expect_get_node_capacity(&self, uuid: &Uuid) -> u64 { + self.get_node_capacity(uuid) + .expect("non-gateway node with zero capacity") + } + + pub(crate) fn expect_get_node_zone(&self, uuid: &Uuid) -> &str { + self.get_node_zone(uuid).expect("node without a zone") + } + + /// Returns the sum of capacities of non gateway nodes in the cluster + fn get_total_capacity(&self) -> u64 { + let mut total_capacity = 0; + for uuid in self.nongateway_nodes() { + total_capacity += self.expect_get_node_capacity(uuid); + } + total_capacity + } + + /// Returns the effective value of the zone_redundancy parameter + pub(crate) 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::<HashSet<&str>>() + .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 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 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::<Vec<_>>(); + 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 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.expect_get_node_zone(&self.node_id_vec[*n as usize])) + .collect::<Vec<_>>(); + 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.expect_get_node_capacity(&uuid); + 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 =================== + + pub(crate) fn calculate_next_version( + mut self, + staging: &LayoutStaging, + ) -> Result<(Self, Message), Error> { + self.version += 1; + + self.roles.merge(&staging.roles); + self.roles.retain(|(_, _, v)| v.0.is_some()); + self.parameters = *staging.parameters.get(); + + let msg = self.calculate_partition_assignment()?; + + Ok((self, msg)) + } + + /// 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. + fn calculate_partition_assignment(&mut self) -> Result<Message, Error> { + // 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()?; + + if self.nongateway_nodes().len() < self.replication_factor { + return Err(Error::Message(format!( + "The number of nodes with positive \ + capacity ({}) is smaller than the replication factor ({}).", + self.nongateway_nodes().len(), + 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<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 new_non_gateway_nodes: Vec<Uuid> = 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<Uuid> = self + .roles + .items() + .iter() + .filter(|(_, _, v)| matches!(v, NodeRoleV(Some(r)) if r.capacity.is_none())) + .map(|(k, _, _)| *k) + .collect(); + + let old_node_id_vec = std::mem::take(&mut self.node_id_vec); + + self.nongateway_node_count = new_non_gateway_nodes.len(); + self.node_id_vec.clear(); + self.node_id_vec.extend(new_non_gateway_nodes); + self.node_id_vec.extend(new_gateway_nodes); + + let new_node_id_vec = &self.node_id_vec; + + // (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::<Uuid, usize>::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::<usize>::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 clear the ring assignemnt data + self.ring_assignment_data = Vec::<CompactNodeType>::new(); + + Ok(Some(old_assignment)) + } + + /// This function generates ids for the zone of the nodes appearing in + /// self.node_id_vec. + pub(crate) fn generate_nongateway_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(); + + for uuid in self.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<String, usize>, + zone_redundancy: usize, + ) -> Result<u64, Error> { + 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<Vertex> { + 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<String, usize>, + exclude_assoc: &HashSet<(usize, usize)>, + zone_redundancy: usize, + ) -> Result<Graph<FlowEdge>, Error> { + let vertices = + LayoutVersion::generate_graph_vertices(zone_to_id.len(), self.nongateway_nodes().len()); + let mut g = Graph::<FlowEdge>::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().len() { + let node_capacity = self.expect_get_node_capacity(&self.node_id_vec[n]); + let node_zone = zone_to_id[self.expect_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<String, usize>, + prev_assign_opt: &Option<Vec<Vec<usize>>>, + zone_redundancy: usize, + ) -> Result<Graph<FlowEdge>, 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().len(); + 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.expect_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<FlowEdge>, + zone_to_id: &HashMap<String, usize>, + prev_assign: &[Vec<usize>], + ) -> 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.expect_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().len(); + 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<FlowEdge>, + ) -> Result<(), Error> { + self.ring_assignment_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))?; + 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<FlowEdge>, + prev_assign_opt: &Option<Vec<Vec<usize>>>, + zone_to_id: &HashMap<String, usize>, + id_to_zone: &[String], + ) -> Result<Message, Error> { + 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(); + 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::<usize>::new(); + for n in prev_assign[p].iter() { + old_zones_of_p + .push(zone_to_id[self.expect_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::<usize>::new(); + for n in 0..storing_nodes.len() { + if self.expect_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.expect_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.expect_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) + } +} |