i18ntk/utils/performance-optimizer.js

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/**
 * Ultra-Performance Optimizer
 * Advanced performance tuning utilities for i18n toolkit
 * Targets sub-40ms processing for 200k keys with <10MB memory
 */

const os = require('os');
const fs = require('fs');
const path = require('path');

class UltraPerformanceOptimizer {
  constructor() {
    this.cpuCores = os.cpus().length;
    this.totalMemory = os.totalmem();
    this.availableMemory = this.totalMemory * 0.8; // Use 80% of system memory
    this.optimalSettings = this.calculateOptimalSettings();
  }

  /**
   * Calculate optimal settings based on system resources
   * @returns {Object} Optimized configuration
   */
  calculateOptimalSettings() {
    const memoryPerKey = 50; // bytes per key (very aggressive)
    const maxKeysInMemory = Math.floor(this.availableMemory / memoryPerKey);
    
    return {
      batchSize: Math.min(2000, Math.floor(maxKeysInMemory / 100)),
      concurrency: Math.min(this.cpuCores * 2, 32),
      memoryLimit: Math.floor(this.availableMemory / 1024 / 1024 * 0.7),
      bufferSize: 64 * 1024,
      cacheStrategy: 'lru',
      compression: 'brotli',
      streaming: true,
      parallelProcessing: true,
      aggressiveGC: true,
      validateOnLoad: false,
      validateOnSave: false,
      skipBackup: true,
      minimalLogging: true
    };
  }

  /**
   * Generate ultra-performance configuration
   * @returns {Object} Ultra-performance config
   */
  generateUltraConfig() {
    return {
      processing: {
        mode: 'ultra-extreme',
        batchSize: this.optimalSettings.batchSize,
        concurrency: this.optimalSettings.concurrency,
        timeout: 5000,
        retryAttempts: 0,
        retryDelay: 0,
        maxFileSize: 1024 * 1024, // 1MB max files
        validateOnSave: false,
        validateOnLoad: false,
        cacheEnabled: true,
        cacheTTL: 300000, // 5 minutes
        autoBackup: false,
        fileFilter: "**/*.json",
        memoryLimit: `${this.optimalSettings.memoryLimit}MB`,
        garbageCollection: true,
        gcInterval: 500
      },
      optimization: {
        memoryLimit: `${this.optimalSettings.memoryLimit}MB`,
        localeOptimizer: true,
        compression: this.optimalSettings.compression,
        parallelProcessing: this.optimalSettings.parallelProcessing,
        streaming: this.optimalSettings.streaming,
        bufferSize: this.optimalSettings.bufferSize,
        aggressiveGC: this.optimalSettings.aggressiveGC,
        minimalLogging: this.optimalSettings.minimalLogging
      },
      filesystem: {
        concurrentReads: this.optimalSettings.concurrency,
        bufferSize: this.optimalSettings.bufferSize,
        cacheDirectory: '.cache-ultra',
        tempDirectory: '.tmp-ultra',
        cleanupInterval: 30000,
        compression: this.optimalSettings.compression
      }
    };
  }

  /**
   * Apply memory-efficient processing strategies
   * @param {Array} keys - Translation keys to process
   * @param {Function} processor - Processing function
   * @returns {Promise<Array>} Processed results
   */
  async processWithMemoryEfficiency(keys, processor) {
    const batchSize = this.optimalSettings.batchSize;
    const results = [];
    
    for (let i = 0; i < keys.length; i += batchSize) {
      const batch = keys.slice(i, i + batchSize);
      const batchResults = await this.processBatch(batch, processor);
      results.push(...batchResults);
      
      // Aggressive memory management
      if (global.gc && i % (batchSize * 10) === 0) {
        global.gc();
      }
    }
    
    return results;
  }

  /**
   * Process a single batch with parallel execution
   * @param {Array} batch - Batch of keys
   * @param {Function} processor - Processing function
   * @returns {Promise<Array>} Batch results
   */
  async processBatch(batch, processor) {
    const chunkSize = Math.ceil(batch.length / this.optimalSettings.concurrency);
    const chunks = [];
    
    for (let i = 0; i < batch.length; i += chunkSize) {
      chunks.push(batch.slice(i, i + chunkSize));
    }
    
    const promises = chunks.map(chunk => this.processChunk(chunk, processor));
    const results = await Promise.all(promises);
    return results.flat();
  }

  /**
   * Process a chunk of keys
   * @param {Array} chunk - Chunk of keys
   * @param {Function} processor - Processing function
   * @returns {Promise<Array>} Chunk results
   */
  async processChunk(chunk, processor) {
    return chunk.map(processor);
  }

  /**
   * Generate performance report
   * @param {Object} metrics - Performance metrics
   * @returns {Object} Formatted report
   */
  generateReport(metrics) {
    return {
      timestamp: new Date().toISOString(),
      system: {
        cpuCores: this.cpuCores,
        totalMemory: `${Math.floor(this.totalMemory / 1024 / 1024)}MB`,
        platform: os.platform(),
        nodeVersion: process.version
      },
      optimization: {
        batchSize: this.optimalSettings.batchSize,
        concurrency: this.optimalSettings.concurrency,
        memoryLimit: this.optimalSettings.memoryLimit,
        compression: this.optimalSettings.compression
      },
      performance: {
        processingTime: metrics.processingTime,
        memoryUsage: metrics.memoryUsage,
        throughput: metrics.throughput,
        efficiency: metrics.efficiency
      },
      recommendations: this.generateRecommendations(metrics)
    };
  }

  /**
   * Generate performance recommendations
   * @param {Object} metrics - Performance metrics
   * @returns {Array} Recommendations
   */
  generateRecommendations(metrics) {
    const recommendations = [];
    
    if (metrics.processingTime > 40) {
      recommendations.push('Consider reducing batch size for better memory locality');
    }
    
    if (metrics.memoryUsage > 15) {
      recommendations.push('Enable more aggressive garbage collection');
    }
    
    if (metrics.throughput < 4000000) {
      recommendations.push('Increase concurrency if CPU cores available');
    }
    
    return recommendations;
  }

  /**
   * Benchmark current system capabilities
   * @returns {Promise<Object>} Benchmark results
   */
  async benchmarkSystem() {
    const testKeys = Array.from({ length: 10000 }, (_, i) => `key_${i}`);
    const startTime = process.hrtime.bigint();
    const startMemory = process.memoryUsage();
    
    const results = await this.processWithMemoryEfficiency(testKeys, key => ({
      key,
      processed: true,
      timestamp: Date.now()
    }));
    
    const endTime = process.hrtime.bigint();
    const endMemory = process.memoryUsage();
    
    const processingTime = Number(endTime - startTime) / 1000000; // Convert to ms
    const memoryDelta = (endMemory.heapUsed - startMemory.heapUsed) / 1024 / 1024;
    const throughput = testKeys.length / (processingTime / 1000);
    
    return {
      processingTime,
      memoryUsage: Math.max(0, memoryDelta),
      throughput,
      efficiency: testKeys.length / processingTime * 1000
    };
  }
}

module.exports = UltraPerformanceOptimizer;

// CLI usage
if (require.main === module) {
  const optimizer = new UltraPerformanceOptimizer();
  optimizer.benchmarkSystem().then(metrics => {
    const report = optimizer.generateReport(metrics);
    console.log('🚀 Ultra-Performance Analysis');
    console.log('================================');
    console.log(`Processing Time: ${metrics.processingTime.toFixed(2)}ms`);
    console.log(`Memory Usage: ${metrics.memoryUsage.toFixed(2)}MB`);
    console.log(`Throughput: ${(metrics.throughput / 1000000).toFixed(2)}M keys/sec`);
    console.log(`Efficiency: ${metrics.efficiency.toFixed(0)} keys/ms`);
    
    console.log('\n⚙️  Optimal Settings:');
    console.log(JSON.stringify(optimizer.optimalSettings, null, 2));
    
    console.log('\n📊 Recommendations:');
    report.recommendations.forEach(rec => console.log(`- ${rec}`));
  });
}