foxhunt/ml/src/stress_testing/performance_analyzer.rs

//! Performance analysis for ML stress testing

use anyhow::Result;
use serde::{Deserialize, Serialize};
use std::collections::HashMap;
use std::time::{Duration, SystemTime};

use super::{PhaseResult, RequirementsCheck, StressTestConfig};

/// Latency statistics
#[derive(Debug, Clone, Default, Serialize, Deserialize)]
pub struct LatencyStats {
    pub mean: f64,
    pub min: u64,
    pub max: u64,
    pub p50: u64,
    pub p95: u64,
    pub p99: u64,
    pub count: u64,
}

/// Comprehensive stress test report
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct StressTestReport {
    pub config: StressTestConfig,
    pub total_duration: Duration,
    pub phase_results: Vec<PhaseResult>,
    pub total_predictions: u64,
    pub total_errors: u64,
    pub error_rate: f64,
    pub latency_stats: LatencyStats,
    pub requirements_met: RequirementsCheck,
    pub throughput_achieved: f64,
    pub recommendations: Vec<String>,
}

/// Performance analyzer for stress testing
#[derive(Debug, Clone)]
pub struct PerformanceAnalyzer {
    start_time: Option<SystemTime>,
    measurements: Vec<PerformanceMeasurement>,
}

#[derive(Debug, Clone)]
struct PerformanceMeasurement {
    timestamp: SystemTime,
    metric_name: String,
    value: f64,
    labels: HashMap<String, String>,
}

impl PerformanceAnalyzer {
    pub fn new() -> Self {
        Self {
            start_time: None,
            measurements: Vec::new(),
        }
    }

    pub async fn start_monitoring(&self) -> Result<()> {
        // Implementation would start background monitoring
        // For now, this is a placeholder
        Ok(())
    }

    pub fn record_measurement(
        &mut self,
        metric_name: &str,
        value: f64,
        labels: HashMap<String, String>,
    ) {
        self.measurements.push(PerformanceMeasurement {
            timestamp: SystemTime::now(),
            metric_name: metric_name.to_string(),
            value,
            labels,
        });
    }

    pub fn generate_summary(&self) -> PerformanceSummary {
        let mut latencies = Vec::new();
        let mut errors = 0;
        let mut total_requests = 0;

        for measurement in &self.measurements {
            match measurement.metric_name.as_str() {
                "latency" => latencies.push(measurement.value as u64),
                "error" => errors += 1,
                "request" => total_requests += 1,
                _ => {},
            }
        }

        let latency_stats = if latencies.is_empty() {
            LatencyStats::default()
        } else {
            self.calculate_latency_stats(&latencies)
        };

        let error_rate = if total_requests > 0 {
            errors as f64 / total_requests as f64
        } else {
            0.0
        };

        PerformanceSummary {
            latency_stats,
            error_rate,
            total_requests: total_requests as u64,
            total_errors: errors as u64,
        }
    }

    fn calculate_latency_stats(&self, latencies: &[u64]) -> LatencyStats {
        let mut sorted = latencies.to_vec();
        sorted.sort_unstable();

        let len = sorted.len();
        let mean = sorted.iter().sum::<u64>() as f64 / len as f64;

        LatencyStats {
            mean,
            min: sorted[0],
            max: sorted[len - 1],
            p50: sorted[len * 50 / 100],
            p95: sorted[len * 95 / 100],
            p99: sorted[len * 99 / 100],
            count: len as u64,
        }
    }
}

#[derive(Debug, Clone)]
pub struct PerformanceSummary {
    pub latency_stats: LatencyStats,
    pub error_rate: f64,
    pub total_requests: u64,
    pub total_errors: u64,
}

impl Default for PerformanceAnalyzer {
    fn default() -> Self {
        Self::new()
    }
}