use anyhow::Result;
use std::sync::{Arc, RwLock};
use super::consensus_optimizer::AIConsensusOptimizer;
use super::data_distribution::IntelligentDataDistributionEngine;
use super::replication_manager::AdaptiveReplicationManager;
use super::network_optimizer::QuantumNetworkOptimizer;
use super::analytics::AdvancedClusterAnalytics;
use super::types::*;
pub struct ClusterUnifiedCoordinator {
config: RevolutionaryClusterConfig,
coordination_ml: MLPipeline,
component_states: HashMap<String, ClusterComponentState>,
coordination_history: VecDeque<ClusterCoordinationEvent>,
}
impl ClusterUnifiedCoordinator {
async fn new(config: RevolutionaryClusterConfig) -> Result<Self> {
Ok(Self {
config,
coordination_ml: MLPipeline::new(),
component_states: HashMap::new(),
coordination_history: VecDeque::with_capacity(1000),
})
}
async fn analyze_cluster_coordination_requirements(
&self,
cluster_state: &ClusterState,
_optimization_context: &ClusterOptimizationContext,
) -> Result<ClusterCoordinationAnalysis> {
let consensus_coordination_required = self.analyze_consensus_coordination_needs(cluster_state);
let data_coordination_required = self.analyze_data_coordination_needs(cluster_state);
let network_coordination_required = self.analyze_network_coordination_needs(cluster_state);
let requires_coordination_optimization =
consensus_coordination_required ||
data_coordination_required ||
network_coordination_required;
let coordination_complexity = self.calculate_coordination_complexity(cluster_state);
let coordination_strategy = self.determine_coordination_strategy(coordination_complexity);
Ok(ClusterCoordinationAnalysis {
requires_coordination_optimization,
consensus_coordination_required,
data_coordination_required,
network_coordination_required,
coordination_complexity,
coordination_strategy,
component_dependencies: self.analyze_component_dependencies(cluster_state),
})
}
fn analyze_consensus_coordination_needs(&self, cluster_state: &ClusterState) -> bool {
cluster_state.performance_metrics.consensus_latency_ms > 200
}
fn analyze_data_coordination_needs(&self, cluster_state: &ClusterState) -> bool {
cluster_state.data_distribution.hot_spots.len() > 2
}
fn analyze_network_coordination_needs(&self, cluster_state: &ClusterState) -> bool {
cluster_state.performance_metrics.network_utilization > 0.8
}
fn calculate_coordination_complexity(&self, cluster_state: &ClusterState) -> f64 {
let node_count_factor = (cluster_state.nodes.len() as f64).ln() / 10.0;
let performance_factor = if cluster_state.performance_metrics.query_throughput_qps > 5000.0 { 0.3 } else { 0.1 };
let network_factor = cluster_state.performance_metrics.network_utilization * 0.2;
(node_count_factor + performance_factor + network_factor).min(1.0)
}
fn determine_coordination_strategy(&self, complexity: f64) -> ClusterCoordinationStrategy {
match complexity {
x if x < 0.3 => ClusterCoordinationStrategy::Simple,
x if x < 0.6 => ClusterCoordinationStrategy::Moderate,
x if x < 0.8 => ClusterCoordinationStrategy::Advanced,
_ => ClusterCoordinationStrategy::AIControlled,
}
}
fn analyze_component_dependencies(&self, _cluster_state: &ClusterState) -> Vec<ComponentDependency> {
vec![
ComponentDependency {
source_component: "consensus".to_string(),
target_component: "networking".to_string(),
dependency_type: DependencyType::Performance,
strength: 0.8,
},
ComponentDependency {
source_component: "data_distribution".to_string(),
target_component: "replication".to_string(),
dependency_type: DependencyType::Consistency,
strength: 0.9,
},
]
}
}
fn format_duration(duration: Duration) -> String {
let total_seconds = duration.as_secs();
if total_seconds < 60 {
format!("{} seconds", total_seconds)
} else if total_seconds < 3600 {
format!("{} minutes", total_seconds / 60)
} else {
format!("{} hours", total_seconds / 3600)
}
}