import { query, queryOne, execute, getPool } from './db'

interface ServerTarget {
  target_id: number
  server_name: string
  server_ip: string
  glances_url: string
  is_active: number
  collect_interval: number
}

// 서버별 타이머 관리
const serverTimers = new Map<number, ReturnType<typeof setInterval>>()
// 서버별 API 버전 캐시
const apiVersionCache = new Map<number, string>()
let isRunning = false

// 타임스탬프 생성
function timestamp(): string {
  return new Date().toLocaleString('sv-SE', { timeZone: 'Asia/Seoul' }).replace('T', ' ')
}

// Glances API 호출 (버전 지정)
async function fetchGlancesApi(baseUrl: string, endpoint: string, version: string): Promise<any> {
  try {
    const url = `${baseUrl}/api/${version}/${endpoint}`
    const response = await fetch(url, { 
      signal: AbortSignal.timeout(5000)
    })
    if (!response.ok) return null
    return await response.json()
  } catch (err) {
    return null
  }
}

// API 버전 자동 감지 (v4 우선, 실패 시 v3)
async function detectApiVersion(baseUrl: string, serverName: string): Promise<string | null> {
  const now = timestamp()
  
  // v4 먼저 시도
  console.log(`[${now}] 🔍 [${serverName}] API 버전 감지 중... (v4 시도)`)
  const v4Result = await fetchGlancesApi(baseUrl, 'system', '4')
  if (v4Result && v4Result.os_name) {
    console.log(`[${now}] ✅ [${serverName}] API v4 감지됨`)
    return '4'
  }
  
  // v3 시도
  console.log(`[${now}] 🔍 [${serverName}] API 버전 감지 중... (v3 시도)`)
  const v3Result = await fetchGlancesApi(baseUrl, 'system', '3')
  if (v3Result && v3Result.os_name) {
    console.log(`[${now}] ✅ [${serverName}] API v3 감지됨`)
    return '3'
  }
  
  console.log(`[${now}] ❌ [${serverName}] API 버전 감지 실패`)
  return null
}

// 이상감지 실행
async function detectAnomalies(targetId: number, serverName: string) {
  const now = timestamp()
  
  // 절대값 변화 최소 임계값 (이 값 이하면 무시)
  const MIN_ABSOLUTE_CHANGE = 5
  
  try {
    // === 단기 변화율 감지 ===
    const SHORT_TERM_THRESHOLD = 30
    
    const snapshots = await query<any>(`
      SELECT cpu_percent, memory_percent
      FROM server_snapshots
      WHERE target_id = $1 AND is_online = 1
      ORDER BY collected_at DESC
      LIMIT 20
    `, [targetId])
    
    if (snapshots.length >= 4) {
      const half = Math.floor(snapshots.length / 2)
      const currSnapshots = snapshots.slice(0, half)
      const prevSnapshots = snapshots.slice(half)
      
      const currCpuAvg = currSnapshots.reduce((sum, s) => sum + (s.cpu_percent || 0), 0) / currSnapshots.length
      const prevCpuAvg = prevSnapshots.reduce((sum, s) => sum + (s.cpu_percent || 0), 0) / prevSnapshots.length
      
      // 메모리: memory_percent 직접 사용
      const currMemAvg = currSnapshots.reduce((sum, s) => sum + (s.memory_percent || 0), 0) / currSnapshots.length
      const prevMemAvg = prevSnapshots.reduce((sum, s) => sum + (s.memory_percent || 0), 0) / prevSnapshots.length
      
      const cpuChange = prevCpuAvg > 1 ? ((currCpuAvg - prevCpuAvg) / prevCpuAvg) * 100 : currCpuAvg - prevCpuAvg
      const memChange = prevMemAvg > 1 ? ((currMemAvg - prevMemAvg) / prevMemAvg) * 100 : currMemAvg - prevMemAvg
      
      // 절대값 변화량
      const cpuAbsChange = currCpuAvg - prevCpuAvg
      const memAbsChange = currMemAvg - prevMemAvg
      
      // CPU 단기 변화율 체크 (증가만 감지, 절대값 5%p 이상일 때만)
      if (cpuChange >= SHORT_TERM_THRESHOLD && cpuAbsChange >= MIN_ABSOLUTE_CHANGE) {
        const recentExists = await queryOne(`
          SELECT 1 FROM anomaly_logs 
          WHERE target_id = $1 AND detect_type = 'short-term' AND metric = 'CPU'
          AND detected_at::timestamp > NOW() - INTERVAL '1 minute'
          LIMIT 1
        `, [targetId])
        
        if (!recentExists) {
          const level = cpuChange >= 100 ? 'danger' : 'warning'
          const message = `CPU 급증 감지 (${prevCpuAvg.toFixed(1)}% → ${currCpuAvg.toFixed(1)}%)`
          
          await execute(`
            INSERT INTO anomaly_logs (target_id, server_name, detect_type, metric, level, current_value, threshold_value, message)
            VALUES ($1, $2, 'short-term', 'CPU', $3, $4, $5, $6)
          `, [targetId, serverName, level, currCpuAvg, cpuChange, message])
          console.log(`[${now}] 🚨 [${serverName}] 단기변화율 이상감지: CPU +${cpuChange.toFixed(1)}% (${level})`)
        }
      }
      
      // Memory 단기 변화율 체크 (증가만 감지, 절대값 5%p 이상일 때만)
      if (memChange >= SHORT_TERM_THRESHOLD && memAbsChange >= MIN_ABSOLUTE_CHANGE) {
        const recentExists = await queryOne(`
          SELECT 1 FROM anomaly_logs 
          WHERE target_id = $1 AND detect_type = 'short-term' AND metric = 'Memory'
          AND detected_at::timestamp > NOW() - INTERVAL '1 minute'
          LIMIT 1
        `, [targetId])
        
        if (!recentExists) {
          const level = memChange >= 100 ? 'danger' : 'warning'
          const message = `Memory 급증 감지 (${prevMemAvg.toFixed(1)}% → ${currMemAvg.toFixed(1)}%)`
          
          await execute(`
            INSERT INTO anomaly_logs (target_id, server_name, detect_type, metric, level, current_value, threshold_value, message)
            VALUES ($1, $2, 'short-term', 'Memory', $3, $4, $5, $6)
          `, [targetId, serverName, level, currMemAvg, memChange, message])
          console.log(`[${now}] 🚨 [${serverName}] 단기변화율 이상감지: Memory +${memChange.toFixed(1)}% (${level})`)
        }
      }
    }
    
    // === Z-Score 감지 ===
    const WARNING_Z = 2.0
    const DANGER_Z = 3.0
    
    const hourSnapshots = await query<any>(`
      SELECT cpu_percent, memory_percent
      FROM server_snapshots
      WHERE target_id = $1 AND is_online = 1
        AND collected_at::timestamp >= NOW() - INTERVAL '1 hour'
      ORDER BY collected_at DESC
    `, [targetId])
    
    if (hourSnapshots.length >= 10) {
      const current = hourSnapshots[0]
      const currCpu = current.cpu_percent ?? 0
      const currMem = current.memory_percent ?? 0  // memory_percent 직접 사용
      
      const cpuValues = hourSnapshots.map(s => s.cpu_percent ?? 0)
      const memValues = hourSnapshots.map(s => s.memory_percent ?? 0)
      
      const cpuAvg = cpuValues.reduce((a, b) => a + b, 0) / cpuValues.length
      const memAvg = memValues.reduce((a, b) => a + b, 0) / memValues.length
      
      const cpuVariance = cpuValues.reduce((sum, val) => sum + Math.pow(val - cpuAvg, 2), 0) / cpuValues.length
      const memVariance = memValues.reduce((sum, val) => sum + Math.pow(val - memAvg, 2), 0) / memValues.length
      const cpuStd = Math.sqrt(cpuVariance)
      const memStd = Math.sqrt(memVariance)
      
      const cpuZscore = cpuStd > 0.1 ? (currCpu - cpuAvg) / cpuStd : 0
      const memZscore = memStd > 0.1 ? (currMem - memAvg) / memStd : 0
      
      // 절대값 변화량
      const cpuAbsDiff = currCpu - cpuAvg
      const memAbsDiff = currMem - memAvg
      
      // CPU Z-Score 체크 (높은 경우만 감지, 절대값 5%p 이상일 때만)
      if (cpuZscore >= WARNING_Z && cpuAbsDiff >= MIN_ABSOLUTE_CHANGE) {
        const recentExists = await queryOne(`
          SELECT 1 FROM anomaly_logs 
          WHERE target_id = $1 AND detect_type = 'zscore' AND metric = 'CPU'
          AND detected_at::timestamp > NOW() - INTERVAL '1 minute'
          LIMIT 1
        `, [targetId])
        
        if (!recentExists) {
          const level = cpuZscore >= DANGER_Z ? 'danger' : 'warning'
          const message = `CPU 평균 대비 ${cpuZscore.toFixed(1)}σ 높음 (평균: ${cpuAvg.toFixed(1)}%, 현재: ${currCpu.toFixed(1)}%)`
          
          await execute(`
            INSERT INTO anomaly_logs (target_id, server_name, detect_type, metric, level, current_value, threshold_value, message)
            VALUES ($1, $2, 'zscore', 'CPU', $3, $4, $5, $6)
          `, [targetId, serverName, level, currCpu, cpuZscore, message])
          console.log(`[${now}] 🚨 [${serverName}] Z-Score 이상감지: CPU Z=${cpuZscore.toFixed(2)} (${level})`)
        }
      }
      
      // Memory Z-Score 체크 (높은 경우만 감지, 절대값 5%p 이상일 때만)
      if (memZscore >= WARNING_Z && memAbsDiff >= MIN_ABSOLUTE_CHANGE) {
        const recentExists = await queryOne(`
          SELECT 1 FROM anomaly_logs 
          WHERE target_id = $1 AND detect_type = 'zscore' AND metric = 'Memory'
          AND detected_at::timestamp > NOW() - INTERVAL '1 minute'
          LIMIT 1
        `, [targetId])
        
        if (!recentExists) {
          const level = memZscore >= DANGER_Z ? 'danger' : 'warning'
          const message = `Memory 평균 대비 ${memZscore.toFixed(1)}σ 높음 (평균: ${memAvg.toFixed(1)}%, 현재: ${currMem.toFixed(1)}%)`
          
          await execute(`
            INSERT INTO anomaly_logs (target_id, server_name, detect_type, metric, level, current_value, threshold_value, message)
            VALUES ($1, $2, 'zscore', 'Memory', $3, $4, $5, $6)
          `, [targetId, serverName, level, currMem, memZscore, message])
          console.log(`[${now}] 🚨 [${serverName}] Z-Score 이상감지: Memory Z=${memZscore.toFixed(2)} (${level})`)
        }
      }
    }

    // === 시간대별 베이스라인 감지 ===
    const DEVIATION_THRESHOLD = 2.0
    const currentHour = new Date().getHours()
    const currentDayOfWeek = new Date().getDay()
    const isWeekend = currentDayOfWeek === 0 || currentDayOfWeek === 6
    const dayType = isWeekend ? 'weekend' : 'weekday'
    
    const baselineData = await query<any>(`
      SELECT cpu_percent, memory_percent
      FROM server_snapshots
      WHERE target_id = $1 AND is_online = 1
        AND collected_at::timestamp >= NOW() - INTERVAL '14 days'
        AND EXTRACT(HOUR FROM collected_at::timestamp) = $2
        AND (
          ($3 = 'weekend' AND EXTRACT(DOW FROM collected_at::timestamp) IN (0, 6))
          OR
          ($3 = 'weekday' AND EXTRACT(DOW FROM collected_at::timestamp) NOT IN (0, 6))
        )
    `, [targetId, currentHour, dayType])
    
    const currentSnapshot = await queryOne<any>(`
      SELECT cpu_percent, memory_percent
      FROM server_snapshots
      WHERE target_id = $1 AND is_online = 1
      ORDER BY collected_at DESC LIMIT 1
    `, [targetId])
    
    if (baselineData.length >= 5 && currentSnapshot) {
      const currCpu = currentSnapshot.cpu_percent ?? 0
      const currMem = currentSnapshot.memory_percent ?? 0  // memory_percent 직접 사용
      
      const cpuValues = baselineData.map(s => s.cpu_percent ?? 0)
      const memValues = baselineData.map(s => s.memory_percent ?? 0)
      
      const cpuAvg = cpuValues.reduce((a, b) => a + b, 0) / cpuValues.length
      const memAvg = memValues.reduce((a, b) => a + b, 0) / memValues.length
      
      const cpuVariance = cpuValues.reduce((sum, val) => sum + Math.pow(val - cpuAvg, 2), 0) / cpuValues.length
      const memVariance = memValues.reduce((sum, val) => sum + Math.pow(val - memAvg, 2), 0) / memValues.length
      const cpuStd = Math.sqrt(cpuVariance)
      const memStd = Math.sqrt(memVariance)
      
      const cpuDeviation = cpuStd > 0.1 ? (currCpu - cpuAvg) / cpuStd : 0
      const memDeviation = memStd > 0.1 ? (currMem - memAvg) / memStd : 0
      
      // 절대값 변화량
      const cpuBaseAbsDiff = currCpu - cpuAvg
      const memBaseAbsDiff = currMem - memAvg
      
      // CPU 베이스라인 체크 (높은 경우만 감지, 절대값 5%p 이상일 때만)
      if (cpuDeviation >= DEVIATION_THRESHOLD && cpuBaseAbsDiff >= MIN_ABSOLUTE_CHANGE) {
        const recentExists = await queryOne(`
          SELECT 1 FROM anomaly_logs 
          WHERE target_id = $1 AND detect_type = 'baseline' AND metric = 'CPU'
          AND detected_at::timestamp > NOW() - INTERVAL '1 minute'
          LIMIT 1
        `, [targetId])
        
        if (!recentExists) {
          const level = cpuDeviation >= 3.0 ? 'danger' : 'warning'
          const dayLabel = isWeekend ? '주말' : '평일'
          const message = `CPU ${dayLabel} ${currentHour}시 베이스라인 대비 ${cpuDeviation.toFixed(1)}σ 높음`
          
          await execute(`
            INSERT INTO anomaly_logs (target_id, server_name, detect_type, metric, level, current_value, threshold_value, message)
            VALUES ($1, $2, 'baseline', 'CPU', $3, $4, $5, $6)
          `, [targetId, serverName, level, currCpu, cpuDeviation, message])
          console.log(`[${now}] 🚨 [${serverName}] 베이스라인 이상감지: CPU σ=${cpuDeviation.toFixed(2)} (${level})`)
        }
      }
      
      // Memory 베이스라인 체크 (높은 경우만 감지, 절대값 5%p 이상일 때만)
      if (memDeviation >= DEVIATION_THRESHOLD && memBaseAbsDiff >= MIN_ABSOLUTE_CHANGE) {
        const recentExists = await queryOne(`
          SELECT 1 FROM anomaly_logs 
          WHERE target_id = $1 AND detect_type = 'baseline' AND metric = 'Memory'
          AND detected_at::timestamp > NOW() - INTERVAL '1 minute'
          LIMIT 1
        `, [targetId])
        
        if (!recentExists) {
          const level = memDeviation >= 3.0 ? 'danger' : 'warning'
          const dayLabel = isWeekend ? '주말' : '평일'
          const message = `Memory ${dayLabel} ${currentHour}시 베이스라인 대비 ${memDeviation.toFixed(1)}σ 높음`
          
          await execute(`
            INSERT INTO anomaly_logs (target_id, server_name, detect_type, metric, level, current_value, threshold_value, message)
            VALUES ($1, $2, 'baseline', 'Memory', $3, $4, $5, $6)
          `, [targetId, serverName, level, currMem, memDeviation, message])
          console.log(`[${now}] 🚨 [${serverName}] 베이스라인 이상감지: Memory σ=${memDeviation.toFixed(2)} (${level})`)
        }
      }
    }
    
    // === 추세 분석 감지 ===
    const SLOPE_THRESHOLD = 0.5
    const WINDOW_MINUTES = 30
    
    const trendSnapshots = await query<any>(`
      SELECT cpu_percent, memory_percent
      FROM server_snapshots
      WHERE target_id = $1 AND is_online = 1
        AND collected_at::timestamp >= NOW() - INTERVAL '${WINDOW_MINUTES} minutes'
      ORDER BY collected_at ASC
    `, [targetId])
    
    if (trendSnapshots.length >= 10) {
      const n = trendSnapshots.length
      const currCpu = trendSnapshots[n - 1].cpu_percent ?? 0
      const currMem = trendSnapshots[n - 1].memory_percent ?? 0
      
      // 선형 회귀 계산
      function calcSlope(values: number[]): { slope: number, r2: number } {
        const n = values.length
        let sumX = 0, sumY = 0, sumXY = 0, sumX2 = 0
        for (let i = 0; i < n; i++) {
          sumX += i; sumY += values[i]; sumXY += i * values[i]; sumX2 += i * i
        }
        const slope = (n * sumXY - sumX * sumY) / (n * sumX2 - sumX * sumX)
        const yMean = sumY / n
        let ssTotal = 0, ssResidual = 0
        for (let i = 0; i < n; i++) {
          const yPred = slope * i + (sumY - slope * sumX) / n
          ssTotal += Math.pow(values[i] - yMean, 2)
          ssResidual += Math.pow(values[i] - yPred, 2)
        }
        const r2 = ssTotal > 0 ? 1 - (ssResidual / ssTotal) : 0
        return { slope: (slope * n) / WINDOW_MINUTES, r2 }
      }
      
      const cpuResult = calcSlope(trendSnapshots.map(s => s.cpu_percent ?? 0))
      const memResult = calcSlope(trendSnapshots.map(s => s.memory_percent ?? 0))
      
      if (cpuResult.slope >= SLOPE_THRESHOLD && cpuResult.r2 >= 0.3) {
        const recentExists = await queryOne(`
          SELECT 1 FROM anomaly_logs 
          WHERE target_id = $1 AND detect_type = 'trend' AND metric = 'CPU'
          AND detected_at::timestamp > NOW() - INTERVAL '1 minute'
          LIMIT 1
        `, [targetId])
        
        if (!recentExists) {
          const level = cpuResult.slope >= 1.0 ? 'danger' : 'warning'
          const message = `CPU 지속 상승 중 (분당 +${cpuResult.slope.toFixed(2)}%, R²=${cpuResult.r2.toFixed(2)})`
          
          await execute(`
            INSERT INTO anomaly_logs (target_id, server_name, detect_type, metric, level, current_value, threshold_value, message)
            VALUES ($1, $2, 'trend', 'CPU', $3, $4, $5, $6)
          `, [targetId, serverName, level, currCpu, cpuResult.slope, message])
          console.log(`[${now}] 🚨 [${serverName}] 추세 이상감지: CPU +${cpuResult.slope.toFixed(2)}/분 (${level})`)
        }
      }
      
      if (memResult.slope >= SLOPE_THRESHOLD && memResult.r2 >= 0.3) {
        const recentExists = await queryOne(`
          SELECT 1 FROM anomaly_logs 
          WHERE target_id = $1 AND detect_type = 'trend' AND metric = 'Memory'
          AND detected_at::timestamp > NOW() - INTERVAL '1 minute'
          LIMIT 1
        `, [targetId])
        
        if (!recentExists) {
          const level = memResult.slope >= 1.0 ? 'danger' : 'warning'
          const message = `Memory 지속 상승 중 (분당 +${memResult.slope.toFixed(2)}%, R²=${memResult.r2.toFixed(2)})`
          
          await execute(`
            INSERT INTO anomaly_logs (target_id, server_name, detect_type, metric, level, current_value, threshold_value, message)
            VALUES ($1, $2, 'trend', 'Memory', $3, $4, $5, $6)
          `, [targetId, serverName, level, currMem, memResult.slope, message])
          console.log(`[${now}] 🚨 [${serverName}] 추세 이상감지: Memory +${memResult.slope.toFixed(2)}/분 (${level})`)
        }
      }
    }
    
  } catch (err) {
    console.error(`[${now}] ❌ [${serverName}] 이상감지 에러:`, err)
  }
}


// 서버 데이터 수집
async function collectServerData(target: ServerTarget) {
  const now = timestamp()
  
  console.log(`[${now}] 📡 [${target.server_name}] 수집 시작... (${target.glances_url})`)
  
  try {
    // API 버전 확인 (캐시 또는 자동 감지)
    let apiVersion = apiVersionCache.get(target.target_id)
    
    if (!apiVersion) {
      apiVersion = await detectApiVersion(target.glances_url, target.server_name)
      if (apiVersion) {
        apiVersionCache.set(target.target_id, apiVersion)
      }
    }
    
    if (!apiVersion) {
      console.log(`[${now}] ❌ [${target.server_name}] 연결 실패 - Offline 기록`)
      await execute(`
        INSERT INTO server_snapshots (target_id, is_online, collected_at)
        VALUES ($1, 0, $2)
      `, [target.target_id, now])
      return
    }
    
    console.log(`[${now}] 📡 [${target.server_name}] Glances API v${apiVersion} 호출 중...`)
    
    // 병렬로 API 호출
    const [system, cpu, mem, memswap, fs, docker, network, quicklook, uptime, sensors, load] = await Promise.all([
      fetchGlancesApi(target.glances_url, 'system', apiVersion),
      fetchGlancesApi(target.glances_url, 'cpu', apiVersion),
      fetchGlancesApi(target.glances_url, 'mem', apiVersion),
      fetchGlancesApi(target.glances_url, 'memswap', apiVersion),
      fetchGlancesApi(target.glances_url, 'fs', apiVersion),
      fetchGlancesApi(target.glances_url, 'containers', apiVersion),
      fetchGlancesApi(target.glances_url, 'network', apiVersion),
      fetchGlancesApi(target.glances_url, 'quicklook', apiVersion),
      fetchGlancesApi(target.glances_url, 'uptime', apiVersion),
      fetchGlancesApi(target.glances_url, 'sensors', apiVersion),
      fetchGlancesApi(target.glances_url, 'load', apiVersion)
    ])

    const isOnline = system !== null
    
    if (!isOnline) {
      // 캐시 클리어 후 재시도 위해
      apiVersionCache.delete(target.target_id)
      console.log(`[${now}] ❌ [${target.server_name}] 연결 실패 - Offline 기록`)
      await execute(`
        INSERT INTO server_snapshots (target_id, is_online, collected_at)
        VALUES ($1, 0, $2)
      `, [target.target_id, now])
      return
    }
    
    console.log(`[${now}] ✅ [${target.server_name}] 연결 성공 - 데이터 저장 중...`)

    // CPU 온도 추출 (sensors 배열에서)
    let cpuTemp: number | null = null
    if (Array.isArray(sensors)) {
      const tempSensor = sensors.find((s: any) => 
        s.label?.toLowerCase().includes('cpu') || 
        s.label?.toLowerCase().includes('core') ||
        s.type === 'temperature_core'
      )
      cpuTemp = tempSensor?.value ?? null
    }

    // server_snapshots INSERT
    console.log(`[${now}] 💾 [${target.server_name}] snapshot 저장 (API v${apiVersion}, CPU: ${cpu?.total?.toFixed(1) || 0}%, MEM: ${mem?.percent?.toFixed(1) || 0}%, TEMP: ${cpuTemp ?? 'N/A'}°C, LOAD: ${quicklook?.load?.toFixed(1) ?? 'N/A'}%)`)
    
    await execute(`
      INSERT INTO server_snapshots (
        target_id, os_name, os_version, host_name, uptime_seconds, uptime_str, ip_address,
        cpu_name, cpu_count, cpu_percent, memory_total, memory_used, memory_free, memory_percent,
        swap_total, swap_used, swap_percent, is_online, api_version, cpu_temp,
        load_1, load_5, load_15, load_percent, collected_at
      ) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10, $11, $12, $13, $14, $15, $16, $17, $18, $19, $20, $21, $22, $23, $24, $25)
    `, [
      target.target_id,
      system?.os_name || system?.linux_distro || null,
      system?.os_version || null,
      system?.hostname || null,
      null,
      typeof uptime === 'string' ? uptime : null,
      target.glances_url.match(/https?:\/\/([^:\/]+)/)?.[1] || null,
      quicklook?.cpu_name || null,
      quicklook?.cpu_number || quicklook?.cpu_log_core || cpu?.cpucore || null,
      cpu?.total ?? quicklook?.cpu ?? null,
      mem?.total || null,
      mem?.total && mem?.percent ? (mem.total * mem.percent / 100) : null,  // memory_used = total × percent / 100
      mem?.free || null,
      mem?.percent || null,
      memswap?.total || null,
      memswap?.used || null,
      memswap?.percent || null,
      isOnline ? 1 : 0,
      apiVersion,
      cpuTemp,
      load?.min1 ?? null,
      load?.min5 ?? null,
      load?.min15 ?? null,
      quicklook?.load ?? null,
      now
    ])
    
    // server_disks INSERT (배열)
    if (Array.isArray(fs) && fs.length > 0) {
      console.log(`[${now}] 💾 [${target.server_name}] disk 저장 (${fs.length}개 파티션)`)
      for (const disk of fs) {
        await execute(`
          INSERT INTO server_disks (
            target_id, device_name, mount_point, fs_type,
            disk_total, disk_used, disk_percent, collected_at
          ) VALUES ($1, $2, $3, $4, $5, $6, $7, $8)
        `, [
          target.target_id,
          disk.device_name || null,
          disk.mnt_point || null,
          disk.fs_type || null,
          disk.size || null,
          disk.used || null,
          disk.percent || null,
          now
        ])
      }
    }

    // server_containers INSERT (배열)
    if (Array.isArray(docker) && docker.length > 0) {
      console.log(`[${now}] 🐳 [${target.server_name}] container 저장 (${docker.length}개 컨테이너)`)
      for (const container of docker) {
        // CPU 값 추출 로직
        const cpuPercent = container.cpu?.total ?? container.cpu_percent ?? null
        const memoryUsage = container.memory?.usage || container.memory_usage || null
        const memoryLimit = container.memory?.limit || container.memory_limit || null
        const memoryPercent = container.memory?.usage && container.memory?.limit 
          ? (container.memory.usage / container.memory.limit * 100) 
          : container.memory_percent ?? null
        
        // 각 컨테이너별 상세 로그
        console.log(`[${now}] 🐳   - ${container.name}: CPU=${cpuPercent?.toFixed(2) ?? 'null'}%, MEM=${memoryPercent?.toFixed(2) ?? 'null'}%`)
        
        // CPU가 null인 경우 상세 디버깅
        if (cpuPercent === null) {
          console.warn(`[${now}] ⚠️   - ${container.name}: CPU 값 null! 원본:`, JSON.stringify({
            'cpu.total': container.cpu?.total,
            'cpu_percent': container.cpu_percent,
            'cpu': container.cpu
          }))
        }
        
        await execute(`
          INSERT INTO server_containers (
            target_id, docker_id, container_name, container_image,
            container_status, cpu_percent, memory_usage, memory_limit,
            memory_percent, uptime, network_rx, network_tx, collected_at
          ) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10, $11, $12, $13)
        `, [
          target.target_id,
          container.id || null,
          container.name || null,
          Array.isArray(container.image) ? container.image.join(', ') : container.image || null,
          container.status || null,
          cpuPercent,
          memoryUsage,
          memoryLimit,
          memoryPercent,
          container.uptime || null,
          container.network?.rx ?? container.network_rx ?? null,
          container.network?.tx ?? container.network_tx ?? null,
          now
        ])
      }
    }
    
    // server_networks INSERT (배열)
    if (Array.isArray(network) && network.length > 0) {
      console.log(`[${now}] 🌐 [${target.server_name}] network 저장 (${network.length}개 인터페이스)`)
      for (const iface of network) {
        await execute(`
          INSERT INTO server_networks (
            target_id, interface_name, bytes_recv, bytes_sent,
            packets_recv, packets_sent, speed_recv, speed_sent,
            is_up, collected_at
          ) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10)
        `, [
          target.target_id,
          iface.interface_name || null,
          iface.bytes_recv || iface.cumulative_rx || null,
          iface.bytes_sent || iface.cumulative_tx || null,
          iface.packets_recv || null,
          iface.packets_sent || null,
          iface.bytes_recv_rate_per_sec || iface.rx || iface.bytes_recv_rate || null,
          iface.bytes_sent_rate_per_sec || iface.tx || iface.bytes_sent_rate || null,
          iface.is_up ? 1 : 0,
          now
        ])
      }
    }

    console.log(`[${now}] ✅ [${target.server_name}] 수집 완료!`)
    
    // 이상감지 실행
    await detectAnomalies(target.target_id, target.server_name)
    
  } catch (err) {
    console.error(`[${now}] ❌ [${target.server_name}] 수집 에러:`, err)
    
    // 캐시 클리어
    apiVersionCache.delete(target.target_id)
    
    // 오프라인 기록
    await execute(`
      INSERT INTO server_snapshots (target_id, is_online, collected_at)
      VALUES ($1, 0, $2)
    `, [target.target_id, now])
  }
}


// 서버별 타이머 시작
function startServerTimer(target: ServerTarget) {
  const now = timestamp()
  
  // 기존 타이머 제거
  stopServerTimer(target.target_id)
  
  console.log(`[${now}] ⏰ [${target.server_name}] 타이머 등록 (주기: ${target.collect_interval}초)`)
  
  // 즉시 한 번 실행
  collectServerData(target)
  
  // 주기적 실행
  const intervalMs = (target.collect_interval || 60) * 1000
  const timer = setInterval(() => {
    collectServerData(target)
  }, intervalMs)
  
  serverTimers.set(target.target_id, timer)
}

// 서버별 타이머 중지
function stopServerTimer(targetId: number) {
  const timer = serverTimers.get(targetId)
  if (timer) {
    clearInterval(timer)
    serverTimers.delete(targetId)
    apiVersionCache.delete(targetId)
    console.log(`[${timestamp()}] ⏹️ 타이머 중지 (target_id: ${targetId})`)
  }
}

// 스케줄러 시작 (모든 활성 서버)
export async function startServerScheduler() {
  const now = timestamp()
  
  if (isRunning) {
    console.log(`[${now}] ⚠️ [Server Scheduler] 이미 실행 중`)
    return
  }
  
  console.log(`[${now}] 🚀 [Server Scheduler] ========== 스케줄러 시작 ==========`)
  
  const targets = await query<ServerTarget>(`
    SELECT * FROM server_targets WHERE is_active = 1
  `)
  
  console.log(`[${now}] 📋 [Server Scheduler] 활성 서버: ${targets.length}개`)
  
  for (const target of targets) {
    console.log(`[${now}] 📋 [Server Scheduler] - ${target.server_name} (${target.glances_url}) / ${target.collect_interval}초`)
    startServerTimer(target)
  }
  
  isRunning = true
  console.log(`[${now}] ✅ [Server Scheduler] ========== 스케줄러 시작 완료 ==========`)
}

// 스케줄러 중지 (모든 서버)
export function stopServerScheduler() {
  const now = timestamp()
  
  console.log(`[${now}] 🛑 [Server Scheduler] ========== 스케줄러 중지 ==========`)
  
  for (const [targetId] of serverTimers) {
    stopServerTimer(targetId)
  }
  
  isRunning = false
  console.log(`[${now}] ✅ [Server Scheduler] ========== 스케줄러 중지 완료 ==========`)
}

// 스케줄러 상태
export async function getServerSchedulerStatus() {
  const activeServers = serverTimers.size
  const targets = await query<ServerTarget>(`
    SELECT * FROM server_targets WHERE is_active = 1
  `)
  
  return {
    is_running: isRunning,
    active_timers: activeServers,
    total_targets: targets.length,
    targets: targets.map(t => ({
      target_id: t.target_id,
      server_name: t.server_name,
      glances_url: t.glances_url,
      collect_interval: t.collect_interval,
      has_timer: serverTimers.has(t.target_id),
      api_version: apiVersionCache.get(t.target_id) || null
    }))
  }
}

// 특정 서버 타이머 갱신 (설정 변경 시)
export async function refreshServerTimer(targetId: number) {
  const now = timestamp()
  const target = await queryOne<ServerTarget>(`
    SELECT * FROM server_targets WHERE target_id = $1 AND is_active = 1
  `, [targetId])
  
  if (target && isRunning) {
    console.log(`[${now}] 🔄 [${target.server_name}] 타이머 갱신`)
    apiVersionCache.delete(targetId) // 버전 재감지
    startServerTimer(target)
  } else {
    stopServerTimer(targetId)
  }
}