oxirs-cluster 0.2.4

//! Adaptive Replication Manager

use anyhow::Result;
use scirs2_core::ml_pipeline::MLPipeline;
use scirs2_core::ndarray_ext::{Array1, Array2};
use std::collections::HashMap;
use std::sync::{Arc, RwLock};
use std::time::Instant;
use super::config::AdaptiveReplicationConfig;
use super::types::*;
pub struct AdaptiveReplicationManager {
    config: AdaptiveReplicationConfig,
    replication_ml: MLPipeline,
    failure_predictor: FailurePredictor,
    replication_optimizer: ReplicationOptimizer,
}

impl AdaptiveReplicationManager {
    async fn new(config: AdaptiveReplicationConfig) -> Result<Self> {
        Ok(Self {
            config,
            replication_ml: MLPipeline::new(),
            failure_predictor: FailurePredictor::new(),
            replication_optimizer: ReplicationOptimizer::new(),
        })
    }

    async fn optimize_replication_strategy(&self, cluster_state: &ClusterState) -> Result<ReplicationOptimizationResult> {
        let mut replication_adjustments = Vec::new();
        let mut performance_improvement = 1.0;

        // Intelligent replication factor adjustment
        if self.config.enable_intelligent_replication_factor {
            let factor_adjustments = self.optimize_replication_factors(cluster_state).await?;
            replication_adjustments.extend(factor_adjustments);
            performance_improvement *= 1.1;
        }

        // Failure prediction and preemptive replication
        if self.config.enable_failure_prediction {
            let failure_predictions = self.failure_predictor.predict_failures(cluster_state).await?;
            let preemptive_adjustments = self.handle_failure_predictions(&failure_predictions, cluster_state).await?;
            replication_adjustments.extend(preemptive_adjustments);
            performance_improvement *= 1.05;
        }

        // Cross-region replication optimization
        if self.config.enable_cross_region_optimization {
            let cross_region_optimization = self.optimize_cross_region_replication(cluster_state).await?;
            replication_adjustments.extend(cross_region_optimization);
            performance_improvement *= 1.08;
        }

        Ok(ReplicationOptimizationResult {
            replication_adjustments,
            performance_improvement,
            optimal_replication_factors: self.calculate_optimal_replication_factors(cluster_state),
            cross_region_optimization_score: self.calculate_cross_region_score(cluster_state),
        })
    }

    async fn optimize_replication_factors(&self, cluster_state: &ClusterState) -> Result<Vec<ReplicationAdjustment>> {
        let mut adjustments = Vec::new();

        for (_, node_state) in cluster_state.nodes.iter() {
            // Calculate optimal replication factor based on node characteristics
            let optimal_factor = self.calculate_optimal_factor_for_node(node_state, cluster_state);

            adjustments.push(ReplicationAdjustment {
                node_id: node_state.node_id,
                old_factor: self.config.base_replication_factor,
                new_factor: optimal_factor,
                reason: "Load-based optimization".to_string(),
            });
        }

        Ok(adjustments)
    }

    fn calculate_optimal_factor_for_node(&self, node_state: &NodeState, _cluster_state: &ClusterState) -> usize {
        // Calculate optimal replication factor based on node load and reliability
        let base_factor = self.config.base_replication_factor;

        if node_state.load > 0.8 {
            // High load nodes get higher replication for availability
            (base_factor + 1).min(self.config.max_replication_factor)
        } else if node_state.load < 0.3 {
            // Low load nodes can handle with lower replication
            (base_factor - 1).max(2)
        } else {
            base_factor
        }
    }

    async fn handle_failure_predictions(
        &self,
        failure_predictions: &[FailurePrediction],
        _cluster_state: &ClusterState,
    ) -> Result<Vec<ReplicationAdjustment>> {
        let mut adjustments = Vec::new();

        for prediction in failure_predictions {
            if prediction.failure_probability > 0.7 {
                adjustments.push(ReplicationAdjustment {
                    node_id: prediction.node_id,
                    old_factor: self.config.base_replication_factor,
                    new_factor: self.config.max_replication_factor,
                    reason: format!("Preemptive replication due to failure prediction: {:.2}", prediction.failure_probability),
                });
            }
        }

        Ok(adjustments)
    }

    async fn optimize_cross_region_replication(&self, _cluster_state: &ClusterState) -> Result<Vec<ReplicationAdjustment>> {
        // Optimize replication across regions for better disaster recovery
        Ok(vec![])
    }

    fn calculate_optimal_replication_factors(&self, cluster_state: &ClusterState) -> HashMap<String, usize> {
        let mut factors = HashMap::new();

        for (_, node_state) in cluster_state.nodes.iter() {
            let optimal_factor = self.calculate_optimal_factor_for_node(node_state, cluster_state);
            factors.insert(format!("node_{}", node_state.node_id), optimal_factor);
        }

        factors
    }

    fn calculate_cross_region_score(&self, _cluster_state: &ClusterState) -> f64 {
        // Calculate cross-region replication effectiveness
        0.85 // Placeholder value
    }
}

/// Failure predictor for preemptive actions
#[derive(Debug)]
pub struct FailurePredictor {
    prediction_model: MLPipeline,
    failure_history: VecDeque<FailureEvent>,
}

impl FailurePredictor {
    fn new() -> Self {
        Self {
            prediction_model: MLPipeline::new(),
            failure_history: VecDeque::with_capacity(1000),
        }
    }

    async fn predict_failures(&self, cluster_state: &ClusterState) -> Result<Vec<FailurePrediction>> {
        let mut predictions = Vec::new();

        for (_, node_state) in cluster_state.nodes.iter() {
            let failure_probability = self.calculate_failure_probability(node_state);

            predictions.push(FailurePrediction {
                node_id: node_state.node_id,
                failure_probability,
                predicted_failure_time: SystemTime::now() + Duration::from_secs(3600), // 1 hour prediction window
                failure_type: self.predict_failure_type(node_state),
            });
        }

        Ok(predictions)
    }

    fn calculate_failure_probability(&self, node_state: &NodeState) -> f64 {
        // Simple failure probability calculation based on node metrics
        let mut probability: f64 = 0.0;

        // High CPU usage increases failure probability
        if node_state.cpu_usage > 0.9 {
            probability += 0.3;
        }

        // High memory usage increases failure probability
        if node_state.memory_usage > 0.95 {
            probability += 0.4;
        }

        // Network issues increase failure probability
        if node_state.network_utilization > 0.9 {
            probability += 0.2;
        }

        // Time since last heartbeat
        if let Ok(duration) = SystemTime::now().duration_since(node_state.last_heartbeat) {
            if duration > Duration::from_secs(30) {
                probability += 0.5;
            }
        }

        probability.min(1.0)
    }

    fn predict_failure_type(&self, node_state: &NodeState) -> FailureType {
        if node_state.memory_usage > 0.95 {
            FailureType::OutOfMemory
        } else if node_state.cpu_usage > 0.95 {
            FailureType::CpuOverload
        } else if node_state.network_utilization > 0.9 {
            FailureType::NetworkIssue
        } else {
            FailureType::Hardware
        }
    }
}

/// Replication optimizer
#[derive(Debug)]
pub struct ReplicationOptimizer {
    optimization_model: MLPipeline,
}

impl ReplicationOptimizer {
    fn new() -> Self {
        Self {
            optimization_model: MLPipeline::new(),
        }
    }
}