oxirs-cluster 0.2.4

//! Revolutionary Cluster Types and State Structures

use serde::{Deserialize, Serialize};
use std::collections::{HashMap, BTreeMap};
use std::net::SocketAddr;
use std::time::{Duration, SystemTime};
use crate::raft::OxirsNodeId;
pub struct ClusterState {
    pub nodes: HashMap<OxirsNodeId, NodeState>,
    pub network_topology: NetworkTopology,
    pub data_distribution: DataDistribution,
    pub replication_state: ReplicationState,
    pub performance_metrics: ClusterPerformanceMetrics,
    pub consensus_state: ConsensusState,
    pub timestamp: SystemTime,
}

/// Node state
#[derive(Debug, Clone)]
pub struct NodeState {
    pub node_id: OxirsNodeId,
    pub address: SocketAddr,
    pub status: NodeStatus,
    pub load: f64,
    pub memory_usage: f64,
    pub cpu_usage: f64,
    pub network_utilization: f64,
    pub data_size: u64,
    pub last_heartbeat: SystemTime,
}

/// Node status
#[derive(Debug, Clone)]
pub enum NodeStatus {
    Active,
    Inactive,
    Degraded,
    Failed,
}

/// Network topology
#[derive(Debug, Clone)]
pub struct NetworkTopology {
    pub connections: HashMap<OxirsNodeId, Vec<NodeConnection>>,
    pub latency_matrix: HashMap<(OxirsNodeId, OxirsNodeId), Duration>,
    pub bandwidth_matrix: HashMap<(OxirsNodeId, OxirsNodeId), f64>,
}

/// Node connection
#[derive(Debug, Clone)]
pub struct NodeConnection {
    pub target_node: OxirsNodeId,
    pub latency: Duration,
    pub bandwidth_mbps: f64,
    pub quality: f64,
}

/// Data distribution state
#[derive(Debug, Clone)]
pub struct DataDistribution {
    pub shard_assignments: HashMap<String, Vec<OxirsNodeId>>,
    pub data_sizes: HashMap<OxirsNodeId, u64>,
    pub hot_spots: Vec<DataHotSpot>,
}

/// Data hot spot
#[derive(Debug, Clone)]
pub struct DataHotSpot {
    pub shard_id: String,
    pub access_frequency: f64,
    pub responsible_nodes: Vec<OxirsNodeId>,
}

/// Replication state
#[derive(Debug, Clone)]
pub struct ReplicationState {
    pub replication_factors: HashMap<String, usize>,
    pub replica_assignments: HashMap<String, Vec<OxirsNodeId>>,
    pub replication_lag: HashMap<(OxirsNodeId, OxirsNodeId), Duration>,
}

/// Cluster performance metrics
#[derive(Debug, Clone)]
pub struct ClusterPerformanceMetrics {
    pub query_throughput_qps: f64,
    pub consensus_latency_ms: u64,
    pub availability: f64,
    pub consistency_level: f64,
    pub network_utilization: f64,
    pub memory_utilization: f64,
    pub cpu_utilization: f64,
}

/// Consensus state
#[derive(Debug, Clone)]
pub struct ConsensusState {
    pub current_leader: Option<OxirsNodeId>,
    pub current_term: u64,
    pub commit_index: u64,
    pub last_applied: u64,
    pub election_timeout: Duration,
    pub heartbeat_interval: Duration,
}

/// Cluster optimization context
#[derive(Debug, Clone)]
pub struct ClusterOptimizationContext {
    pub optimization_goals: Vec<OptimizationGoal>,
    pub resource_constraints: ResourceConstraints,
    pub sla_requirements: SLARequirements,
    pub current_workload: WorkloadCharacteristics,
}

/// Optimization goal
#[derive(Debug, Clone)]
pub enum OptimizationGoal {
    MaximizeThroughput,
    MinimizeLatency,
    MaximizeAvailability,
    MinimizeCost,
    BalanceLoad,
}

/// Resource constraints
#[derive(Debug, Clone)]
pub struct ResourceConstraints {
    pub max_nodes: usize,
    pub max_memory_per_node: u64,
    pub max_cpu_per_node: f64,
    pub max_network_bandwidth: f64,
    pub budget_constraints: f64,
}

/// SLA requirements
#[derive(Debug, Clone)]
pub struct SLARequirements {
    pub max_latency_ms: u64,
    pub min_availability: f64,
    pub min_throughput_qps: f64,
    pub max_data_loss_tolerance: f64,
}

/// Workload characteristics
#[derive(Debug, Clone)]
pub struct WorkloadCharacteristics {
    pub read_write_ratio: f64,
    pub query_complexity_distribution: HashMap<String, f64>,
    pub temporal_patterns: Vec<TemporalPattern>,
    pub geographic_distribution: HashMap<String, f64>,
}

/// Temporal pattern
#[derive(Debug, Clone)]
pub struct TemporalPattern {
    pub pattern_type: String,
    pub intensity: f64,
    pub duration: Duration,
    pub frequency: f64,
}

/// AI consensus optimizer
pub struct ConsensusContext {
    pub current_workload: f64,
    pub network_conditions: NetworkConditions,
    pub node_reliability: HashMap<OxirsNodeId, f64>,
}

#[derive(Debug, Clone)]
pub struct NetworkConditions {
    pub average_latency: Duration,
    pub packet_loss_rate: f64,
    pub bandwidth_utilization: f64,
}

/// Optimization results structures
#[derive(Debug, Clone)]
pub struct ClusterOptimizationResult {
    pub optimization_time: Duration,
    pub coordination_analysis: ClusterCoordinationAnalysis,
    pub consensus_optimization: Option<ConsensusOptimizationResult>,
    pub data_distribution_optimization: Option<DataDistributionOptimizationResult>,
    pub replication_optimization: Option<ReplicationOptimizationResult>,
    pub network_optimization: Option<NetworkOptimizationResult>,
    pub scaling_prediction: Option<ScalingPrediction>,
    pub applied_optimizations: AppliedClusterOptimizations,
    pub performance_improvement: f64,
}

#[derive(Debug, Clone)]
pub struct ClusterCoordinationAnalysis {
    pub requires_coordination_optimization: bool,
    pub consensus_coordination_required: bool,
    pub data_coordination_required: bool,
    pub network_coordination_required: bool,
    pub coordination_complexity: f64,
    pub coordination_strategy: ClusterCoordinationStrategy,
    pub component_dependencies: Vec<ComponentDependency>,
}

#[derive(Debug, Clone)]
pub enum ClusterCoordinationStrategy {
    Simple,
    Moderate,
    Advanced,
    AIControlled,
}

#[derive(Debug, Clone)]
pub struct ComponentDependency {
    pub source_component: String,
    pub target_component: String,
    pub dependency_type: DependencyType,
    pub strength: f64,
}

#[derive(Debug, Clone)]
pub enum DependencyType {
    Performance,
    Consistency,
    Availability,
    Resource,
}

#[derive(Debug, Clone)]
pub struct ConsensusOptimizationResult {
    pub applied_optimizations: Vec<String>,
    pub performance_improvement: f64,
    pub optimal_leader: OxirsNodeId,
    pub optimized_timeouts: OptimizedTimeouts,
    pub consensus_efficiency_score: f64,
}

#[derive(Debug, Clone)]
pub struct OptimizedTimeouts {
    pub election_timeout: Duration,
    pub heartbeat_interval: Duration,
    pub append_entries_timeout: Duration,
    pub vote_request_timeout: Duration,
}

#[derive(Debug, Clone)]
pub struct TimeoutOptimizationResult {
    pub applied_optimizations: Vec<String>,
    pub improvement_factor: f64,
    pub optimal_election_timeout: Duration,
    pub optimal_heartbeat_interval: Duration,
}

#[derive(Debug, Clone)]
pub struct QuantumConsensusOptimization {
    pub optimizations: Vec<String>,
    pub improvement_factor: f64,
    pub quantum_coherence_score: f64,
}

#[derive(Debug, Clone)]
pub struct DataDistributionOptimizationResult {
    pub optimization_actions: Vec<String>,
    pub performance_improvement: f64,
    pub new_shard_assignments: HashMap<String, Vec<OxirsNodeId>>,
    pub load_balancing_score: f64,
}

#[derive(Debug, Clone)]
pub struct DataPlacementOptimization {
    pub actions: Vec<String>,
    pub improvement: f64,
    pub placement_scores: Vec<f64>,
}

#[derive(Debug, Clone)]
pub struct ShardingOptimization {
    pub actions: Vec<String>,
    pub improvement: f64,
}

#[derive(Debug, Clone)]
pub struct LoadBalancingOptimization {
    pub actions: Vec<String>,
    pub improvement: f64,
}

#[derive(Debug, Clone)]
pub struct ReplicationOptimizationResult {
    pub replication_adjustments: Vec<ReplicationAdjustment>,
    pub performance_improvement: f64,
    pub optimal_replication_factors: HashMap<String, usize>,
    pub cross_region_optimization_score: f64,
}

#[derive(Debug, Clone)]
pub struct ReplicationAdjustment {
    pub node_id: OxirsNodeId,
    pub old_factor: usize,
    pub new_factor: usize,
    pub reason: String,
}

#[derive(Debug, Clone)]
pub struct FailurePrediction {
    pub node_id: OxirsNodeId,
    pub failure_probability: f64,
    pub predicted_failure_time: SystemTime,
    pub failure_type: FailureType,
}

#[derive(Debug, Clone)]
pub enum FailureType {
    Hardware,
    Network,
    OutOfMemory,
    CpuOverload,
    NetworkIssue,
}

#[derive(Debug, Clone)]
pub struct FailureEvent {
    pub timestamp: SystemTime,
    pub node_id: OxirsNodeId,
    pub failure_type: FailureType,
    pub recovery_time: Option<Duration>,
}

#[derive(Debug, Clone)]
pub struct NetworkOptimizationResult {
    pub routing_optimizations: Vec<String>,
    pub performance_improvement: f64,
    pub optimal_topology: NetworkTopology,
    pub network_efficiency_score: f64,
}

#[derive(Debug, Clone)]
pub struct QuantumNetworkOptimization {
    pub optimizations: Vec<String>,
    pub improvement: f64,
}

#[derive(Debug, Clone)]
pub struct RoutingOptimization {
    pub optimizations: Vec<String>,
    pub improvement: f64,
}

#[derive(Debug, Clone)]
pub struct CongestionPrediction {
    pub source_node: OxirsNodeId,
    pub target_node: OxirsNodeId,
    pub congestion_probability: f64,
    pub predicted_congestion_time: SystemTime,
    pub current_utilization: f64,
    pub available_bandwidth: f64,
}

#[derive(Debug, Clone)]
pub struct CongestionEvent {
    pub timestamp: SystemTime,
    pub source_node: OxirsNodeId,
    pub target_node: OxirsNodeId,
    pub severity: f64,
    pub duration: Duration,
}

#[derive(Debug, Clone)]
pub struct AppliedClusterOptimizations {
    pub coordination_optimizations: Vec<String>,
    pub consensus_optimizations: Vec<String>,
    pub data_distribution_optimizations: Vec<String>,
    pub replication_optimizations: Vec<String>,
    pub network_optimizations: Vec<String>,
}

impl AppliedClusterOptimizations {
    fn new() -> Self {
        Self {
            coordination_optimizations: Vec::new(),
            consensus_optimizations: Vec::new(),
            data_distribution_optimizations: Vec::new(),
            replication_optimizations: Vec::new(),
            network_optimizations: Vec::new(),
        }
    }
}

#[derive(Debug, Clone)]
pub struct ScalingPrediction {
    pub scale_up_probability: f64,
    pub scale_down_probability: f64,
    pub optimal_node_count: usize,
    pub scaling_timeline: Duration,
    pub scaling_recommendations: Vec<String>,
    pub cost_impact_analysis: CostImpactAnalysis,
}

#[derive(Debug, Clone)]
pub struct CapacityPrediction {
    pub current_node_count: usize,
    pub optimal_node_count: usize,
    pub current_throughput: f64,
    pub expected_throughput: f64,
    pub scaling_timeline: Duration,
    pub expected_performance_improvement: f64,
}

#[derive(Debug, Clone)]
pub struct CostImpactAnalysis {
    pub current_monthly_cost: f64,
    pub projected_monthly_cost: f64,
    pub cost_change: f64,
    pub cost_per_performance_unit: f64,
    pub roi_analysis: String,
}

#[derive(Debug, Clone)]
pub struct ScalingEvent {
    pub timestamp: SystemTime,
    pub scaling_action: ScalingAction,
    pub node_count_before: usize,
    pub node_count_after: usize,
    pub performance_impact: f64,
}

#[derive(Debug, Clone)]
pub enum ScalingAction {
    ScaleUp,
    ScaleDown,
    Rebalance,
}

// Analytics structures
#[derive(Debug, Clone)]
pub struct ClusterAnalytics {
    pub performance_summary: PerformanceSummary,
    pub detected_anomalies: Vec<DetectedAnomaly>,
    pub trend_analysis: TrendAnalysis,
    pub recommendations: Vec<String>,
}

#[derive(Debug, Clone)]
pub struct PerformanceSummary {
    pub average_throughput_qps: f64,
    pub average_latency_ms: u64,
    pub average_availability: f64,
    pub performance_trend: PerformanceTrend,
}

impl Default for PerformanceSummary {
    fn default() -> Self {
        Self {
            average_throughput_qps: 0.0,
            average_latency_ms: 0,
            average_availability: 0.0,
            performance_trend: PerformanceTrend::Unknown,
        }
    }
}

#[derive(Debug, Clone)]
pub enum PerformanceTrend {
    Improving,
    Stable,
    Degrading,
    Unknown,
}

#[derive(Debug, Clone)]
pub struct ClusterPerformanceSnapshot {
    pub timestamp: SystemTime,
    pub metrics: ClusterPerformanceMetrics,
    pub node_count: usize,
    pub total_data_size: u64,
}

#[derive(Debug, Clone)]
pub struct DetectedAnomaly {
    pub anomaly_type: AnomalyType,
    pub severity: AnomalySeverity,
    pub description: String,
    pub affected_nodes: Vec<OxirsNodeId>,
    pub timestamp: SystemTime,
}

#[derive(Debug, Clone)]
pub enum AnomalyType {
    LowThroughput,
    HighLatency,
    MemoryLeak,
    NetworkCongestion,
    ConsensusFailure,
}

#[derive(Debug, Clone)]
pub enum AnomalySeverity {
    Low,
    Medium,
    High,
    Critical,
}

#[derive(Debug, Clone)]
pub struct TrendAnalysis {
    pub throughput_trend: TrendDirection,
    pub latency_trend: TrendDirection,
    pub availability_trend: TrendDirection,
    pub capacity_projection: CapacityProjection,
}

#[derive(Debug, Clone)]
pub enum TrendDirection {
    Increasing,
    Decreasing,
    Stable,
    Unknown,
}

#[derive(Debug, Clone)]
pub struct CapacityProjection {
    pub projected_node_count_1_month: usize,
    pub projected_throughput_1_month: f64,
    pub scaling_recommendation: String,
}

#[derive(Debug, Clone)]
pub struct TrendDataPoint {
    pub timestamp: SystemTime,
    pub throughput: f64,
    pub latency: f64,
    pub availability: f64,
    pub node_count: usize,
}

// Component state tracking
#[derive(Debug, Clone)]
pub struct ClusterComponentState {
    pub component_name: String,
    pub performance_score: f64,
    pub resource_utilization: f64,
    pub last_optimization: SystemTime,
    pub optimization_history: Vec<String>,
}

#[derive(Debug, Clone)]
pub struct ClusterCoordinationEvent {
    pub timestamp: SystemTime,
    pub coordination_type: String,
    pub components_involved: Vec<String>,
    pub performance_impact: f64,
}

/// Cluster optimization statistics
#[derive(Debug, Clone)]
pub struct ClusterOptimizationStatistics {
    pub total_optimizations: usize,
    pub consensus_optimizations: usize,
    pub data_distribution_optimizations: usize,
    pub replication_optimizations: usize,
    pub network_optimizations: usize,
    pub average_optimization_time: Duration,
    pub average_performance_improvement: f64,
    pub total_time_saved: Duration,
}

impl ClusterOptimizationStatistics {
    fn new() -> Self {
        Self {
            total_optimizations: 0,
            consensus_optimizations: 0,
            data_distribution_optimizations: 0,
            replication_optimizations: 0,
            network_optimizations: 0,
            average_optimization_time: Duration::ZERO,
            average_performance_improvement: 1.0,
            total_time_saved: Duration::ZERO,
        }
    }

    fn record_optimization(
        &mut self,
        _node_count: usize,
        optimization_time: Duration,
        applied_optimizations: AppliedClusterOptimizations,
    ) {
        self.total_optimizations += 1;

        if !applied_optimizations.consensus_optimizations.is_empty() {
            self.consensus_optimizations += 1;
        }
        if !applied_optimizations.data_distribution_optimizations.is_empty() {
            self.data_distribution_optimizations += 1;
        }
        if !applied_optimizations.replication_optimizations.is_empty() {
            self.replication_optimizations += 1;
        }
        if !applied_optimizations.network_optimizations.is_empty() {
            self.network_optimizations += 1;
        }

        // Update average optimization time
        let total_time = self.average_optimization_time * self.total_optimizations as u32
            + optimization_time;
        self.average_optimization_time = total_time / self.total_optimizations as u32;
    }
}

/// Revolutionary cluster optimizer factory
pub struct RevolutionaryClusterOptimizerFactory;

impl RevolutionaryClusterOptimizerFactory {
    /// Create optimizer with consensus focus
    pub async fn create_consensus_focused() -> Result<RevolutionaryClusterOptimizer> {
        let mut config = RevolutionaryClusterConfig::default();
        config.consensus_config.enable_ai_leader_selection = true;
        config.consensus_config.enable_quantum_consensus = true;
        config.consensus_config.optimization_strategy = ConsensusOptimizationStrategy::HybridQuantumAI;

        RevolutionaryClusterOptimizer::new(config).await
    }

    /// Create optimizer with data distribution focus
    pub async fn create_data_distribution_focused() -> Result<RevolutionaryClusterOptimizer> {
        let mut config = RevolutionaryClusterConfig::default();
        config.data_distribution_config.enable_ml_data_placement = true;
        config.data_distribution_config.enable_dynamic_sharding = true;
        config.data_distribution_config.distribution_strategy = DataDistributionStrategy::MLOptimized;

        RevolutionaryClusterOptimizer::new(config).await
    }

    /// Create optimizer with network focus
    pub async fn create_network_focused() -> Result<RevolutionaryClusterOptimizer> {
        let mut config = RevolutionaryClusterConfig::default();
        config.network_config.enable_quantum_network_optimization = true;
        config.network_config.enable_adaptive_routing = true;
        config.network_config.optimization_strategy = NetworkOptimizationStrategy::QuantumEnhanced;

        RevolutionaryClusterOptimizer::new(config).await
    }

    /// Create balanced optimizer
    pub async fn create_balanced() -> Result<RevolutionaryClusterOptimizer> {
        RevolutionaryClusterOptimizer::new(RevolutionaryClusterConfig::default()).await
    }
}

#[cfg(test)]
mod tests {
    use super::*;
    use std::net::{IpAddr, Ipv4Addr};

    #[tokio::test]
    async fn test_revolutionary_cluster_optimizer_creation() {
        let config = RevolutionaryClusterConfig::default();
        let optimizer = RevolutionaryClusterOptimizer::new(config).await;
        assert!(optimizer.is_ok());
    }

    #[tokio::test]
    async fn test_cluster_optimization() {
        let optimizer = RevolutionaryClusterOptimizerFactory::create_balanced()
            .await
            .unwrap();

        let cluster_state = create_test_cluster_state();
        let optimization_context = create_test_optimization_context();

        let result = optimizer
            .optimize_cluster_operations(&cluster_state, &optimization_context)
            .await;
        assert!(result.is_ok());

        let optimization_result = result.unwrap();
        assert!(optimization_result.performance_improvement >= 1.0);
    }

    #[tokio::test]
    async fn test_consensus_focused_optimizer() {
        let optimizer = RevolutionaryClusterOptimizerFactory::create_consensus_focused()
            .await
            .unwrap();

        let cluster_state = create_test_cluster_state();
        let consensus_context = ConsensusContext {
            current_workload: 0.8,
            network_conditions: NetworkConditions {
                average_latency: Duration::from_millis(50),
                packet_loss_rate: 0.01,
                bandwidth_utilization: 0.7,
            },
            node_reliability: HashMap::new(),
        };

        let result = optimizer
            .optimize_consensus_protocol(&cluster_state, &consensus_context)
            .await;
        assert!(result.is_ok());

        let consensus_result = result.unwrap();
        assert!(consensus_result.performance_improvement >= 1.0);
        assert!(consensus_result.consensus_efficiency_score >= 0.0);
    }

    #[tokio::test]
    async fn test_scaling_prediction() {
        let optimizer = RevolutionaryClusterOptimizerFactory::create_balanced()
            .await
            .unwrap();

        let cluster_state = create_test_cluster_state();

        let result = optimizer.predict_scaling_needs(&cluster_state).await;
        assert!(result.is_ok());

        let scaling_prediction = result.unwrap();
        assert!(scaling_prediction.optimal_node_count > 0);
        assert!(!scaling_prediction.scaling_recommendations.is_empty());
    }

    fn create_test_cluster_state() -> ClusterState {
        let mut nodes = HashMap::new();
        nodes.insert(1, NodeState {
            node_id: 1,
            address: SocketAddr::new(IpAddr::V4(Ipv4Addr::new(127, 0, 0, 1)), 8080),
            status: NodeStatus::Active,
            load: 0.6,
            memory_usage: 0.7,
            cpu_usage: 0.5,
            network_utilization: 0.4,
            data_size: 1000000,
            last_heartbeat: SystemTime::now(),
        });

        ClusterState {
            nodes,
            network_topology: NetworkTopology {
                connections: HashMap::new(),
                latency_matrix: HashMap::new(),
                bandwidth_matrix: HashMap::new(),
            },
            data_distribution: DataDistribution {
                shard_assignments: HashMap::new(),
                data_sizes: HashMap::new(),
                hot_spots: Vec::new(),
            },
            replication_state: ReplicationState {
                replication_factors: HashMap::new(),
                replica_assignments: HashMap::new(),
                replication_lag: HashMap::new(),
            },
            performance_metrics: ClusterPerformanceMetrics {
                query_throughput_qps: 5000.0,
                consensus_latency_ms: 50,
                availability: 0.999,
                consistency_level: 0.95,
                network_utilization: 0.6,
                memory_utilization: 0.7,
                cpu_utilization: 0.5,
            },
            consensus_state: ConsensusState {
                current_leader: Some(1),
                current_term: 10,
                commit_index: 100,
                last_applied: 100,
                election_timeout: Duration::from_millis(500),
                heartbeat_interval: Duration::from_millis(100),
            },
            timestamp: SystemTime::now(),
        }
    }

    fn create_test_optimization_context() -> ClusterOptimizationContext {
        ClusterOptimizationContext {
            optimization_goals: vec![OptimizationGoal::MaximizeThroughput],
            resource_constraints: ResourceConstraints {
                max_nodes: 10,
                max_memory_per_node: 8 * 1024 * 1024 * 1024, // 8GB
                max_cpu_per_node: 8.0,
                max_network_bandwidth: 1000.0, // 1Gbps
                budget_constraints: 10000.0,
            },
            sla_requirements: SLARequirements {
                max_latency_ms: 100,
                min_availability: 0.999,
                min_throughput_qps: 1000.0,
                max_data_loss_tolerance: 0.001,
            },
            current_workload: WorkloadCharacteristics {
                read_write_ratio: 0.8,
                query_complexity_distribution: HashMap::new(),
                temporal_patterns: Vec::new(),
                geographic_distribution: HashMap::new(),
            },
        }
    }
}