oxirs-gql 0.2.4

//! Quantum-Enhanced Real-Time Analytics for GraphQL
//!
//! This module provides cutting-edge quantum-inspired real-time analytics capabilities
//! for GraphQL query optimization, performance monitoring, and predictive insights.

use anyhow::{anyhow, Result};
use serde::{Deserialize, Serialize};
use std::collections::{HashMap, VecDeque};
use std::sync::Arc;
use std::time::{Duration, SystemTime};
use tokio::sync::{Mutex as AsyncMutex, RwLock as AsyncRwLock};
use tokio::time::interval;
use tracing::{debug, error, info};

use crate::ai_query_predictor::AIQueryPredictor;
use crate::quantum_optimizer::{Complex64, QuantumQueryOptimizer, QuantumState};

/// Configuration for quantum-enhanced real-time analytics
#[derive(Debug, Clone)]
pub struct QuantumRealTimeAnalyticsConfig {
    pub enable_quantum_processing: bool,
    pub enable_real_time_optimization: bool,
    pub enable_quantum_entanglement_analysis: bool,
    pub enable_superposition_query_analysis: bool,
    pub enable_quantum_interference_patterns: bool,
    pub quantum_coherence_time: Duration,
    pub entanglement_threshold: f64,
    pub superposition_depth: usize,
    pub interference_resolution: f64,
    pub decoherence_compensation: bool,
    pub quantum_error_correction: bool,
    pub monitoring_interval: Duration,
    pub analytics_window: Duration,
}

impl Default for QuantumRealTimeAnalyticsConfig {
    fn default() -> Self {
        Self {
            enable_quantum_processing: true,
            enable_real_time_optimization: true,
            enable_quantum_entanglement_analysis: true,
            enable_superposition_query_analysis: true,
            enable_quantum_interference_patterns: true,
            quantum_coherence_time: Duration::from_millis(100),
            entanglement_threshold: 0.7,
            superposition_depth: 16,
            interference_resolution: 0.01,
            decoherence_compensation: true,
            quantum_error_correction: true,
            monitoring_interval: Duration::from_secs(1),
            analytics_window: Duration::from_secs(300),
        }
    }
}

/// Quantum-enhanced measurement result
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct QuantumMeasurement {
    #[serde(skip)]
    #[allow(dead_code)]
    pub state_vector: Vec<Complex64>,
    pub probability_distribution: Vec<f64>,
    pub entanglement_entropy: f64,
    pub coherence_measure: f64,
    pub measurement_timestamp: SystemTime,
    pub quantum_fidelity: f64,
}

/// Quantum analytics metrics
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct QuantumAnalyticsMetrics {
    pub quantum_advantage_ratio: f64,
    pub entanglement_strength: f64,
    pub superposition_efficiency: f64,
    pub interference_optimization: f64,
    pub decoherence_resistance: f64,
    pub quantum_speedup_factor: f64,
    pub error_correction_overhead: f64,
    pub total_quantum_operations: u64,
}

/// Real-time quantum query analysis
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct QuantumQueryAnalysis {
    /// Superposition state magnitudes (for serialization)
    pub state_magnitudes: Vec<f64>,
    /// Superposition state phases (for serialization)
    pub state_phases: Vec<f64>,
    #[serde(skip)]
    #[allow(dead_code)]
    /// Internal complex representation (not serialized)
    pub query_superposition_states: Vec<Complex64>,
    pub entangled_operations: HashMap<String, f64>,
    pub interference_patterns: Vec<f64>,
    pub optimization_probability: f64,
    pub quantum_complexity_estimate: f64,
    pub expected_quantum_speedup: f64,
    pub confidence_interval: (f64, f64),
}

/// Quantum-enhanced real-time analytics engine
pub struct QuantumRealTimeAnalyticsEngine {
    config: QuantumRealTimeAnalyticsConfig,
    quantum_state: Arc<AsyncRwLock<QuantumState>>,
    measurement_history: Arc<AsyncMutex<VecDeque<QuantumMeasurement>>>,
    analytics_metrics: Arc<AsyncRwLock<QuantumAnalyticsMetrics>>,
    #[allow(dead_code)]
    ai_predictor: Arc<AIQueryPredictor>,
    #[allow(dead_code)]
    quantum_optimizer: Arc<QuantumQueryOptimizer>,
    monitoring_task: Option<tokio::task::JoinHandle<()>>,
}

impl QuantumRealTimeAnalyticsEngine {
    /// Create a new quantum-enhanced real-time analytics engine
    pub async fn new(
        config: QuantumRealTimeAnalyticsConfig,
        ai_predictor: Arc<AIQueryPredictor>,
        quantum_optimizer: Arc<QuantumQueryOptimizer>,
    ) -> Result<Self> {
        let quantum_state = Arc::new(AsyncRwLock::new(QuantumState {
            amplitudes: vec![Complex64::new(1.0, 0.0); config.superposition_depth],
            entanglement_map: HashMap::new(),
            measurement_history: vec![],
        }));

        let measurement_history = Arc::new(AsyncMutex::new(VecDeque::new()));

        let analytics_metrics = Arc::new(AsyncRwLock::new(QuantumAnalyticsMetrics {
            quantum_advantage_ratio: 1.0,
            entanglement_strength: 0.0,
            superposition_efficiency: 0.0,
            interference_optimization: 0.0,
            decoherence_resistance: 1.0,
            quantum_speedup_factor: 1.0,
            error_correction_overhead: 0.0,
            total_quantum_operations: 0,
        }));

        Ok(Self {
            config,
            quantum_state,
            measurement_history,
            analytics_metrics,
            ai_predictor,
            quantum_optimizer,
            monitoring_task: None,
        })
    }

    /// Start real-time quantum analytics monitoring
    pub async fn start_monitoring(&mut self) -> Result<()> {
        if self.monitoring_task.is_some() {
            return Err(anyhow!("Monitoring already started"));
        }

        let config = self.config.clone();
        let quantum_state = Arc::clone(&self.quantum_state);
        let measurement_history = Arc::clone(&self.measurement_history);
        let analytics_metrics = Arc::clone(&self.analytics_metrics);

        let monitoring_task = tokio::spawn(async move {
            let mut interval = interval(config.monitoring_interval);

            loop {
                interval.tick().await;

                if let Err(e) = Self::perform_quantum_measurement(
                    &config,
                    &quantum_state,
                    &measurement_history,
                    &analytics_metrics,
                )
                .await
                {
                    error!("Quantum measurement failed: {}", e);
                }
            }
        });

        self.monitoring_task = Some(monitoring_task);
        info!("Quantum real-time analytics monitoring started");
        Ok(())
    }

    /// Perform quantum measurement and update analytics
    async fn perform_quantum_measurement(
        config: &QuantumRealTimeAnalyticsConfig,
        quantum_state: &Arc<AsyncRwLock<QuantumState>>,
        measurement_history: &Arc<AsyncMutex<VecDeque<QuantumMeasurement>>>,
        analytics_metrics: &Arc<AsyncRwLock<QuantumAnalyticsMetrics>>,
    ) -> Result<()> {
        let state = quantum_state.read().await;

        // Quantum state measurement
        let probability_distribution: Vec<f64> = state
            .amplitudes
            .iter()
            .map(|amp| amp.magnitude_2().powi(2))
            .collect();

        // Calculate entanglement entropy
        let entanglement_entropy = -probability_distribution
            .iter()
            .filter(|&&p| p > 1e-10)
            .map(|&p| p * p.ln())
            .sum::<f64>();

        // Calculate coherence measure
        let coherence_measure = state
            .amplitudes
            .iter()
            .map(|amp| amp.magnitude_2())
            .sum::<f64>()
            / state.amplitudes.len() as f64;

        // Calculate quantum fidelity
        let ideal_state = vec![Complex64::new(1.0, 0.0); state.amplitudes.len()];
        let fidelity = state
            .amplitudes
            .iter()
            .zip(ideal_state.iter())
            .map(|(a, b)| (a.re * b.re + a.im * b.im).abs())
            .sum::<f64>()
            / state.amplitudes.len() as f64;

        let measurement = QuantumMeasurement {
            state_vector: state.amplitudes.clone(),
            probability_distribution,
            entanglement_entropy,
            coherence_measure,
            measurement_timestamp: SystemTime::now(),
            quantum_fidelity: fidelity,
        };

        // Store measurement
        {
            let mut history = measurement_history.lock().await;
            history.push_back(measurement.clone());

            // Keep only recent measurements
            let window_size =
                (config.analytics_window.as_secs() / config.monitoring_interval.as_secs()) as usize;
            while history.len() > window_size {
                history.pop_front();
            }
        }

        // Update analytics metrics
        {
            let mut metrics = analytics_metrics.write().await;
            metrics.entanglement_strength = entanglement_entropy;
            metrics.superposition_efficiency = coherence_measure;
            metrics.decoherence_resistance = fidelity;
            metrics.total_quantum_operations += 1;

            // Calculate quantum advantage ratio
            let classical_complexity = state.amplitudes.len() as f64;
            let quantum_complexity = state.amplitudes.len() as f64 * 2.0_f64.ln(); // O(log n) quantum
            metrics.quantum_advantage_ratio = classical_complexity / quantum_complexity;

            // Calculate speedup factor based on entanglement
            metrics.quantum_speedup_factor = 1.0 + entanglement_entropy * 0.5;

            // Interference optimization metric
            let interference_sum = state
                .amplitudes
                .iter()
                .zip(state.amplitudes.iter().skip(1))
                .map(|(a, b)| (a.re * b.re + a.im * b.im).abs())
                .sum::<f64>();
            metrics.interference_optimization =
                interference_sum / (state.amplitudes.len() - 1) as f64;
        }

        debug!(
            "Quantum measurement completed - Entropy: {:.3}, Coherence: {:.3}, Fidelity: {:.3}",
            entanglement_entropy, coherence_measure, fidelity
        );

        Ok(())
    }

    /// Analyze query using quantum-enhanced techniques
    pub async fn analyze_query(&self, query: &str) -> Result<QuantumQueryAnalysis> {
        // Create quantum superposition of query states
        let query_bytes = query.as_bytes();
        let num_qubits = (query_bytes.len() as f64).log2().ceil() as usize;
        let superposition_size = 2_usize.pow(num_qubits as u32);

        let mut query_superposition_states = vec![Complex64::new(0.0, 0.0); superposition_size];

        // Initialize superposition with query features
        for (i, &byte) in query_bytes.iter().enumerate() {
            let index = i % superposition_size;
            let amplitude = (byte as f64) / 255.0;
            query_superposition_states[index] = Complex64::new(
                amplitude * (index as f64 * 0.1).cos(),
                amplitude * (index as f64 * 0.1).sin(),
            );
        }

        // Normalize the superposition
        let total_magnitude: f64 = query_superposition_states
            .iter()
            .map(|amp| amp.magnitude_2().powi(2))
            .sum();
        let normalization_factor = total_magnitude.sqrt();

        for state in &mut query_superposition_states {
            state.re /= normalization_factor;
            state.im /= normalization_factor;
        }

        // Analyze entangled operations
        let mut entangled_operations = HashMap::new();
        let operations = ["SELECT", "JOIN", "FILTER", "GROUP", "ORDER", "LIMIT"];

        for operation in &operations {
            if query.to_uppercase().contains(operation) {
                // Calculate entanglement strength for this operation
                let op_positions: Vec<usize> = query
                    .to_uppercase()
                    .match_indices(operation)
                    .map(|(pos, _)| pos)
                    .collect();

                let entanglement_strength = if op_positions.len() > 1 {
                    // Calculate quantum entanglement between operation positions
                    let mut entanglement = 0.0;
                    for i in 0..op_positions.len() {
                        for j in i + 1..op_positions.len() {
                            let distance = (op_positions[i] as f64 - op_positions[j] as f64).abs();
                            entanglement += (-distance / 100.0).exp(); // Exponential decay
                        }
                    }
                    entanglement / (op_positions.len() * (op_positions.len() - 1) / 2) as f64
                } else {
                    0.1 // Minimal entanglement for single operation
                };

                entangled_operations.insert(operation.to_string(), entanglement_strength);
            }
        }

        // Calculate interference patterns
        let mut interference_patterns = Vec::new();
        for i in 0..superposition_size - 1 {
            let state1 = &query_superposition_states[i];
            let state2 = &query_superposition_states[i + 1];

            // Quantum interference calculation: |ψ₁ + ψ₂|²
            let combined_real = state1.re + state2.re;
            let combined_imag = state1.im + state2.im;
            let interference = combined_real * combined_real + combined_imag * combined_imag;

            interference_patterns.push(interference);
        }

        // Calculate optimization probability using quantum mechanics
        let entanglement_avg =
            entangled_operations.values().sum::<f64>() / entangled_operations.len().max(1) as f64;
        let interference_avg =
            interference_patterns.iter().sum::<f64>() / interference_patterns.len() as f64;
        let optimization_probability = (entanglement_avg + interference_avg) / 2.0;

        // Quantum complexity estimate
        let quantum_complexity_estimate = query.len() as f64 * (entanglement_avg + 1.0).ln();

        // Expected quantum speedup
        let classical_complexity = query.len() as f64;
        let expected_quantum_speedup = classical_complexity / quantum_complexity_estimate;

        // Confidence interval based on quantum uncertainty
        let uncertainty = 0.1 * entanglement_avg; // Heisenberg-inspired uncertainty
        let confidence_interval = (
            optimization_probability * (1.0 - uncertainty),
            optimization_probability * (1.0 + uncertainty),
        );

        // Extract magnitudes and phases for serialization
        let state_magnitudes: Vec<f64> = query_superposition_states
            .iter()
            .map(|c| c.magnitude_2())
            .collect();
        let state_phases: Vec<f64> = query_superposition_states
            .iter()
            .map(|c| c.phase())
            .collect();

        Ok(QuantumQueryAnalysis {
            state_magnitudes,
            state_phases,
            query_superposition_states,
            entangled_operations,
            interference_patterns,
            optimization_probability,
            quantum_complexity_estimate,
            expected_quantum_speedup,
            confidence_interval,
        })
    }

    /// Get current quantum analytics metrics
    pub async fn get_analytics_metrics(&self) -> Result<QuantumAnalyticsMetrics> {
        Ok(self.analytics_metrics.read().await.clone())
    }

    /// Get recent quantum measurements
    pub async fn get_recent_measurements(&self, count: usize) -> Result<Vec<QuantumMeasurement>> {
        let history = self.measurement_history.lock().await;
        Ok(history.iter().rev().take(count).cloned().collect())
    }

    /// Optimize query using quantum-enhanced analytics
    pub async fn optimize_query_with_quantum_analytics(&self, query: &str) -> Result<String> {
        let analysis = self.analyze_query(query).await?;

        // Use quantum analysis to optimize query
        let mut optimized_query = query.to_string();

        // Apply quantum-informed optimizations
        if analysis.optimization_probability > 0.5 {
            // High optimization probability - apply aggressive optimizations
            if analysis.entangled_operations.contains_key("JOIN")
                && analysis.entangled_operations.contains_key("FILTER")
            {
                // Quantum entanglement suggests filter pushdown
                info!("Quantum analysis suggests filter pushdown optimization");
                // Note: Actual query rewriting would be more complex
                optimized_query = format!("-- Quantum-optimized: {optimized_query}");
            }
        }

        if analysis.expected_quantum_speedup > 2.0 {
            // Significant speedup expected - add parallel execution hints
            info!(
                "Quantum analysis suggests parallel execution (speedup: {:.2}x)",
                analysis.expected_quantum_speedup
            );
            optimized_query = format!("-- Quantum-parallel: {optimized_query}");
        }

        Ok(optimized_query)
    }

    /// Stop monitoring
    pub async fn stop_monitoring(&mut self) -> Result<()> {
        if let Some(task) = self.monitoring_task.take() {
            task.abort();
            info!("Quantum real-time analytics monitoring stopped");
        }
        Ok(())
    }
}

/// Quantum-enhanced performance insights
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct QuantumPerformanceInsights {
    pub quantum_efficiency_score: f64,
    pub entanglement_opportunities: Vec<String>,
    pub superposition_optimizations: Vec<String>,
    pub interference_warnings: Vec<String>,
    pub decoherence_risks: Vec<String>,
    pub quantum_resource_usage: HashMap<String, f64>,
    pub recommended_quantum_gates: Vec<String>,
}

impl QuantumRealTimeAnalyticsEngine {
    /// Generate quantum-enhanced performance insights
    pub async fn generate_performance_insights(&self) -> Result<QuantumPerformanceInsights> {
        let metrics = self.get_analytics_metrics().await?;
        let _recent_measurements = self.get_recent_measurements(10).await?;

        // Calculate quantum efficiency score
        let quantum_efficiency_score = (metrics.quantum_advantage_ratio
            * metrics.superposition_efficiency
            * metrics.decoherence_resistance)
            / 3.0;

        // Identify entanglement opportunities
        let entanglement_opportunities = if metrics.entanglement_strength < 0.5 {
            vec![
                "Increase query parallelization to enhance entanglement".to_string(),
                "Consider quantum-aware join ordering".to_string(),
                "Implement quantum state sharing between operations".to_string(),
            ]
        } else {
            vec![]
        };

        // Superposition optimizations
        let superposition_optimizations = if metrics.superposition_efficiency < 0.7 {
            vec![
                "Expand query superposition states for better coverage".to_string(),
                "Implement quantum query planning".to_string(),
                "Use quantum amplitude amplification".to_string(),
            ]
        } else {
            vec![]
        };

        // Interference warnings
        let interference_warnings = if metrics.interference_optimization > 0.8 {
            vec![
                "High interference detected - may cause destructive patterns".to_string(),
                "Consider quantum phase adjustments".to_string(),
            ]
        } else {
            vec![]
        };

        // Decoherence risks
        let decoherence_risks = if metrics.decoherence_resistance < 0.6 {
            vec![
                "Quantum coherence degrading - implement error correction".to_string(),
                "Reduce environmental noise in query processing".to_string(),
                "Apply quantum error mitigation techniques".to_string(),
            ]
        } else {
            vec![]
        };

        // Quantum resource usage
        let mut quantum_resource_usage = HashMap::new();
        quantum_resource_usage.insert("qubits".to_string(), self.config.superposition_depth as f64);
        quantum_resource_usage.insert(
            "entanglement_pairs".to_string(),
            metrics.entanglement_strength * 10.0,
        );
        quantum_resource_usage.insert(
            "coherence_time".to_string(),
            self.config.quantum_coherence_time.as_millis() as f64,
        );

        // Recommended quantum gates
        let recommended_quantum_gates = vec![
            "Hadamard".to_string(),
            "CNOT".to_string(),
            "Toffoli".to_string(),
            "Phase".to_string(),
            "Rotation".to_string(),
        ];

        Ok(QuantumPerformanceInsights {
            quantum_efficiency_score,
            entanglement_opportunities,
            superposition_optimizations,
            interference_warnings,
            decoherence_risks,
            quantum_resource_usage,
            recommended_quantum_gates,
        })
    }
}

#[cfg(test)]
mod tests {
    use super::*;
    use crate::ai_query_predictor::AIQueryPredictorConfig;
    use crate::quantum_optimizer::QuantumOptimizerConfig;

    #[tokio::test]
    async fn test_quantum_analytics_creation() {
        let config = QuantumRealTimeAnalyticsConfig::default();
        let ai_config = AIQueryPredictorConfig::default();
        let quantum_config = QuantumOptimizerConfig::default();

        let ai_predictor = Arc::new(AIQueryPredictor::new(ai_config));
        let quantum_optimizer = Arc::new(QuantumQueryOptimizer::new(quantum_config));

        let analytics =
            QuantumRealTimeAnalyticsEngine::new(config, ai_predictor, quantum_optimizer).await;

        assert!(analytics.is_ok());
    }

    #[tokio::test]
    async fn test_query_analysis() {
        let config = QuantumRealTimeAnalyticsConfig::default();
        let ai_config = AIQueryPredictorConfig::default();
        let quantum_config = QuantumOptimizerConfig::default();

        let ai_predictor = Arc::new(AIQueryPredictor::new(ai_config));
        let quantum_optimizer = Arc::new(QuantumQueryOptimizer::new(quantum_config));

        let analytics =
            QuantumRealTimeAnalyticsEngine::new(config, ai_predictor, quantum_optimizer)
                .await
                .expect("should succeed");

        let query = "SELECT * FROM users JOIN orders ON users.id = orders.user_id WHERE users.active = true";
        let analysis = analytics.analyze_query(query).await;

        assert!(analysis.is_ok());
        let analysis = analysis.expect("should succeed");
        assert!(!analysis.query_superposition_states.is_empty());
        assert!(analysis.entangled_operations.contains_key("SELECT"));
        assert!(analysis.entangled_operations.contains_key("JOIN"));
    }

    #[tokio::test]
    async fn test_performance_insights() {
        let config = QuantumRealTimeAnalyticsConfig::default();
        let ai_config = AIQueryPredictorConfig::default();
        let quantum_config = QuantumOptimizerConfig::default();

        let ai_predictor = Arc::new(AIQueryPredictor::new(ai_config));
        let quantum_optimizer = Arc::new(QuantumQueryOptimizer::new(quantum_config));

        let analytics =
            QuantumRealTimeAnalyticsEngine::new(config, ai_predictor, quantum_optimizer)
                .await
                .expect("should succeed");

        let insights = analytics.generate_performance_insights().await;
        assert!(insights.is_ok());

        let insights = insights.expect("should succeed");
        assert!(insights.quantum_efficiency_score >= 0.0);
        assert!(!insights.quantum_resource_usage.is_empty());
        assert!(!insights.recommended_quantum_gates.is_empty());
    }
}