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Chapter 16: Performance Tuning and Optimization

Overview

Performance optimization is crucial for Vektagraf applications handling large datasets and high-throughput workloads. This chapter covers performance profiling, bottleneck identification, memory optimization, query tuning, and scaling strategies for maximum efficiency.

Learning Objectives

  • Profile and identify performance bottlenecks in Vektagraf applications
  • Optimize memory usage and garbage collection for large datasets
  • Tune query performance and vector search operations
  • Implement effective caching and indexing strategies
  • Design scalable architectures for high-performance applications

Prerequisites

  • Understanding of Vektagraf core concepts (Chapters 1-3)
  • Knowledge of database operations and vector search (Chapters 4-5)
  • Familiarity with monitoring and observability (Chapter 13)

Core Concepts

Performance Optimization Framework

Vektagraf performance optimization follows a systematic approach:

  1. Measurement: Profile and benchmark current performance
  2. Analysis: Identify bottlenecks and optimization opportunities
  3. Optimization: Apply targeted performance improvements
  4. Validation: Measure improvements and iterate
graph TB
    A[Performance Profiling] --> B[Bottleneck Analysis]
    B --> C[Memory Optimization]
    B --> D[Query Optimization]
    B --> E[Index Optimization]
    B --> F[Caching Strategy]
    
    C --> G[Validation & Benchmarking]
    D --> G
    E --> G
    F --> G
    
    G --> H{Performance Target Met?}
    H -->|No| B
    H -->|Yes| I[Production Deployment]

Performance Metrics and KPIs

Key performance indicators for Vektagraf applications:

  • Throughput: Operations per second (OPS)
  • Latency: Response time percentiles (P50, P95, P99)
  • Memory Usage: Heap utilization and garbage collection
  • CPU Utilization: Processing efficiency
  • I/O Performance: Disk and network throughput

Prac

tical Examples

Performance Profiling and Benchmarking

1. Comprehensive Performance Profiler

import 'package:vektagraf/vektagraf.dart';

// Advanced performance profiler for Vektagraf operations
class VektagrafProfiler {
  final Map<String, ProfilerSession> _sessions = {};
  final List<BenchmarkResult> _benchmarkHistory = [];
  
  ProfilerSession startSession(String name) {
    final session = ProfilerSession(name);
    _sessions[name] = session;
    return session;
  }
  
  void endSession(String name) {
    final session = _sessions.remove(name);
    if (session != null) {
      session.end();
      _benchmarkHistory.add(session.getResult());
    }
  }
  
  Future<BenchmarkSuite> runBenchmarkSuite(
    VektagrafDatabase database,
  ) async {
    final suite = BenchmarkSuite();
    
    // Database operation benchmarks
    await _benchmarkDatabaseOperations(database, suite);
    
    // Vector search benchmarks
    await _benchmarkVectorSearch(database, suite);
    
    // Query optimization benchmarks
    await _benchmarkQueryPerformance(database, suite);
    
    // Memory usage benchmarks
    await _benchmarkMemoryUsage(database, suite);
    
    return suite;
  }
  
  Future<void> _benchmarkDatabaseOperations(
    VektagrafDatabase database,
    BenchmarkSuite suite,
  ) async {
    // Create test data
    final testObjects = _generateTestObjects(1000);
    
    // Benchmark create operations
    final createBenchmark = await _benchmarkOperation(
      'create_operations',
      () async {
        await database.transaction((txn) async {
          for (final obj in testObjects) {
            await txn.save(obj);
          }
        });
      },
    );
    suite.addResult(createBenchmark);
    
    // Benchmark read operations
    final readBenchmark = await _benchmarkOperation(
      'read_operations',
      () async {
        for (final obj in testObjects) {
          await database.findById(obj.id);
        }
      },
    );
    suite.addResult(readBenchmark);
    
    // Benchmark query operations
    final queryBenchmark = await _benchmarkOperation(
      'query_operations',
      () async {
        await database.query((obj) => obj.type == 'TestObject').toList();
      },
    );
    suite.addResult(queryBenchmark);
  }
  
  Future<BenchmarkResult> _benchmarkOperation(
    String name,
    Future<void> Function() operation,
  ) async {
    final iterations = 10;
    final durations = <Duration>[];
    
    // Warm up
    await operation();
    
    // Measure iterations
    for (int i = 0; i < iterations; i++) {
      final stopwatch = Stopwatch()..start();
      await operation();
      stopwatch.stop();
      durations.add(stopwatch.elapsed);
    }
    
    return BenchmarkResult(
      name: name,
      iterations: iterations,
      durations: durations,
      timestamp: DateTime.now(),
    );
  }
}

class ProfilerSession {
  final String name;
  final DateTime startTime;
  final Map<String, dynamic> metrics = {};
  final List<ProfilerEvent> events = [];
  DateTime? endTime;
  
  ProfilerSession(this.name) : startTime = DateTime.now();
  
  void recordEvent(String event, {Map<String, dynamic>? data}) {
    events.add(ProfilerEvent(
      name: event,
      timestamp: DateTime.now(),
      data: data ?? {},
    ));
  }
  
  void recordMetric(String name, dynamic value) {
    metrics[name] = value;
  }
  
  void end() {
    endTime = DateTime.now();
  }
  
  BenchmarkResult getResult() {
    return BenchmarkResult(
      name: name,
      iterations: 1,
      durations: [duration],
      timestamp: startTime,
      metrics: Map.from(metrics),
      events: List.from(events),
    );
  }
  
  Duration get duration => (endTime ?? DateTime.now()).difference(startTime);
}

class ProfilerEvent {
  final String name;
  final DateTime timestamp;
  final Map<String, dynamic> data;
  
  ProfilerEvent({
    required this.name,
    required this.timestamp,
    required this.data,
  });
}

class BenchmarkResult {
  final String name;
  final int iterations;
  final List<Duration> durations;
  final DateTime timestamp;
  final Map<String, dynamic> metrics;
  final List<ProfilerEvent> events;
  
  BenchmarkResult({
    required this.name,
    required this.iterations,
    required this.durations,
    required this.timestamp,
    this.metrics = const {},
    this.events = const [],
  });
  
  Duration get averageDuration {
    if (durations.isEmpty) return Duration.zero;
    final totalMicros = durations.fold<int>(
      0, (sum, d) => sum + d.inMicroseconds);
    return Duration(microseconds: totalMicros ~/ durations.length);
  }
  
  Duration get minDuration => durations.isEmpty 
      ? Duration.zero 
      : durations.reduce((a, b) => a < b ? a : b);
  
  Duration get maxDuration => durations.isEmpty 
      ? Duration.zero 
      : durations.reduce((a, b) => a > b ? a : b);
  
  double get operationsPerSecond => iterations / (averageDuration.inMicroseconds / 1000000.0);
  
  Map<String, dynamic> toJson() {
    return {
      'name': name,
      'iterations': iterations,
      'average_duration_ms': averageDuration.inMilliseconds,
      'min_duration_ms': minDuration.inMilliseconds,
      'max_duration_ms': maxDuration.inMilliseconds,
      'operations_per_second': operationsPerSecond,
      'timestamp': timestamp.toIso8601String(),
      'metrics': metrics,
    };
  }
}

class BenchmarkSuite {
  final List<BenchmarkResult> results = [];
  final DateTime startTime = DateTime.now();
  
  void addResult(BenchmarkResult result) {
    results.add(result);
  }
  
  Map<String, dynamic> getSummary() {
    return {
      'total_benchmarks': results.length,
      'start_time': startTime.toIso8601String(),
      'results': results.map((r) => r.toJson()).toList(),
      'summary_stats': _calculateSummaryStats(),
    };
  }
  
  Map<String, dynamic> _calculateSummaryStats() {
    if (results.isEmpty) return {};
    
    final totalOps = results.fold<double>(
      0.0, (sum, r) => sum + r.operationsPerSecond);
    
    return {
      'average_ops_per_second': totalOps / results.length,
      'fastest_operation': results.reduce((a, b) => 
          a.averageDuration < b.averageDuration ? a : b).name,
      'slowest_operation': results.reduce((a, b) => 
          a.averageDuration > b.averageDuration ? a : b).name,
    };
  }
}
```#### 
2. Memory Usage Analysis

```dart
// Memory profiling and optimization tools
class MemoryProfiler {
  final Map<String, MemorySnapshot> _snapshots = {};
  
  MemorySnapshot takeSnapshot(String name) {
    final snapshot = MemorySnapshot(
      name: name,
      timestamp: DateTime.now(),
      heapUsage: _getCurrentHeapUsage(),
      objectCounts: _getObjectCounts(),
    );
    
    _snapshots[name] = snapshot;
    return snapshot;
  }
  
  MemoryAnalysis compareSnapshots(String before, String after) {
    final beforeSnapshot = _snapshots[before];
    final afterSnapshot = _snapshots[after];
    
    if (beforeSnapshot == null || afterSnapshot == null) {
      throw ArgumentError('Snapshot not found');
    }
    
    return MemoryAnalysis(
      before: beforeSnapshot,
      after: afterSnapshot,
    );
  }
  
  Future<MemoryOptimizationReport> analyzeMemoryUsage(
    VektagrafDatabase database,
  ) async {
    final report = MemoryOptimizationReport();
    
    // Analyze object storage efficiency
    await _analyzeObjectStorage(database, report);
    
    // Analyze vector storage efficiency
    await _analyzeVectorStorage(database, report);
    
    // Analyze cache efficiency
    await _analyzeCacheUsage(database, report);
    
    // Analyze garbage collection patterns
    await _analyzeGarbageCollection(report);
    
    return report;
  }
  
  Future<void> _analyzeObjectStorage(
    VektagrafDatabase database,
    MemoryOptimizationReport report,
  ) async {
    final objects = await database.query((_) => true).toList();
    
    int totalSize = 0;
    final typeSizes = <String, int>{};
    
    for (final obj in objects) {
      final size = _estimateObjectSize(obj);
      totalSize += size;
      
      typeSizes[obj.type] = (typeSizes[obj.type] ?? 0) + size;
    }
    
    report.objectStorageAnalysis = ObjectStorageAnalysis(
      totalObjects: objects.length,
      totalSizeBytes: totalSize,
      averageSizeBytes: objects.isNotEmpty ? totalSize ~/ objects.length : 0,
      typeSizes: typeSizes,
    );
  }
  
  int _estimateObjectSize(VektagrafObject obj) {
    // Simplified size estimation
    int size = 100; // Base object overhead
    
    // Add property sizes
    for (final entry in obj.properties.entries) {
      size += entry.key.length * 2; // Key size (UTF-16)
      size += _estimateValueSize(entry.value);
    }
    
    return size;
  }
  
  int _estimateValueSize(dynamic value) {
    if (value == null) return 8;
    if (value is String) return value.length * 2;
    if (value is int) return 8;
    if (value is double) return 8;
    if (value is bool) return 1;
    if (value is List) {
      return value.fold<int>(16, (sum, item) => sum + _estimateValueSize(item));
    }
    if (value is Map) {
      return value.entries.fold<int>(16, (sum, entry) => 
          sum + _estimateValueSize(entry.key) + _estimateValueSize(entry.value));
    }
    return 64; // Default for unknown types
  }
  
  HeapUsage _getCurrentHeapUsage() {
    // Platform-specific implementation would go here
    return HeapUsage(
      used: 50 * 1024 * 1024, // 50MB
      total: 100 * 1024 * 1024, // 100MB
      max: 200 * 1024 * 1024, // 200MB
    );
  }
  
  Map<String, int> _getObjectCounts() {
    // Platform-specific implementation would go here
    return {
      'VektagrafObject': 1000,
      'String': 5000,
      'List': 500,
      'Map': 300,
    };
  }
}

class MemorySnapshot {
  final String name;
  final DateTime timestamp;
  final HeapUsage heapUsage;
  final Map<String, int> objectCounts;
  
  MemorySnapshot({
    required this.name,
    required this.timestamp,
    required this.heapUsage,
    required this.objectCounts,
  });
}

class HeapUsage {
  final int used;
  final int total;
  final int max;
  
  HeapUsage({
    required this.used,
    required this.total,
    required this.max,
  });
  
  double get usageRatio => used / total;
  int get available => total - used;
}

class MemoryAnalysis {
  final MemorySnapshot before;
  final MemorySnapshot after;
  
  MemoryAnalysis({
    required this.before,
    required this.after,
  });
  
  int get heapGrowth => after.heapUsage.used - before.heapUsage.used;
  
  Map<String, int> get objectCountChanges {
    final changes = <String, int>{};
    
    final allTypes = {...before.objectCounts.keys, ...after.objectCounts.keys};
    
    for (final type in allTypes) {
      final beforeCount = before.objectCounts[type] ?? 0;
      final afterCount = after.objectCounts[type] ?? 0;
      changes[type] = afterCount - beforeCount;
    }
    
    return changes;
  }
  
  Map<String, dynamic> toJson() {
    return {
      'heap_growth_bytes': heapGrowth,
      'object_count_changes': objectCountChanges,
      'before_usage_ratio': before.heapUsage.usageRatio,
      'after_usage_ratio': after.heapUsage.usageRatio,
    };
  }
}
```### Qu
ery Optimization

#### 1. Query Performance Analyzer

```dart
// Advanced query optimization and analysis
class QueryOptimizer {
  final VektagrafDatabase _database;
  final Map<String, QueryPlan> _cachedPlans = {};
  final QueryPerformanceTracker _performanceTracker;
  
  QueryOptimizer(this._database) 
      : _performanceTracker = QueryPerformanceTracker();
  
  Future<OptimizedQuery<T>> optimizeQuery<T>(
    VektagrafList<T> query,
  ) async {
    final querySignature = _generateQuerySignature(query);
    
    // Check for cached optimization plan
    final cachedPlan = _cachedPlans[querySignature];
    if (cachedPlan != null && cachedPlan.isValid) {
      return OptimizedQuery<T>(query, cachedPlan);
    }
    
    // Analyze query and create optimization plan
    final plan = await _analyzeAndOptimize(query);
    _cachedPlans[querySignature] = plan;
    
    return OptimizedQuery<T>(query, plan);
  }
  
  Future<QueryPlan> _analyzeAndOptimize<T>(VektagrafList<T> query) async {
    final analysis = await _analyzeQuery(query);
    final optimizations = _identifyOptimizations(analysis);
    
    return QueryPlan(
      signature: _generateQuerySignature(query),
      analysis: analysis,
      optimizations: optimizations,
      createdAt: DateTime.now(),
    );
  }
  
  Future<QueryAnalysis> _analyzeQuery<T>(VektagrafList<T> query) async {
    // Estimate query complexity
    final complexity = _estimateQueryComplexity(query);
    
    // Analyze available indexes
    final indexAnalysis = await _analyzeAvailableIndexes(query);
    
    // Estimate result set size
    final estimatedResults = await _estimateResultSetSize(query);
    
    // Analyze filter selectivity
    final filterAnalysis = _analyzeFilterSelectivity(query);
    
    return QueryAnalysis(
      complexity: complexity,
      indexAnalysis: indexAnalysis,
      estimatedResults: estimatedResults,
      filterAnalysis: filterAnalysis,
    );
  }
  
  List<QueryOptimization> _identifyOptimizations(QueryAnalysis analysis) {
    final optimizations = <QueryOptimization>[];
    
    // Index recommendations
    if (analysis.indexAnalysis.missingIndexes.isNotEmpty) {
      optimizations.add(QueryOptimization(
        type: OptimizationType.createIndex,
        description: 'Create indexes for better performance',
        impact: OptimizationImpact.high,
        details: {
          'missing_indexes': analysis.indexAnalysis.missingIndexes,
        },
      ));
    }
    
    // Filter reordering
    if (analysis.filterAnalysis.canReorder) {
      optimizations.add(QueryOptimization(
        type: OptimizationType.reorderFilters,
        description: 'Reorder filters for better selectivity',
        impact: OptimizationImpact.medium,
        details: {
          'optimal_order': analysis.filterAnalysis.optimalOrder,
        },
      ));
    }
    
    // Result limiting
    if (analysis.estimatedResults > 10000) {
      optimizations.add(QueryOptimization(
        type: OptimizationType.addLimit,
        description: 'Add LIMIT clause to reduce result set',
        impact: OptimizationImpact.high,
        details: {
          'recommended_limit': 1000,
        },
      ));
    }
    
    return optimizations;
  }
  
  Future<T> executeOptimized<T>(
    OptimizedQuery<T> optimizedQuery,
    Future<T> Function() executor,
  ) async {
    final stopwatch = Stopwatch()..start();
    
    try {
      final result = await executor();
      stopwatch.stop();
      
      // Record performance metrics
      _performanceTracker.recordExecution(
        optimizedQuery.plan.signature,
        stopwatch.elapsed,
        true,
      );
      
      return result;
    } catch (e) {
      stopwatch.stop();
      
      _performanceTracker.recordExecution(
        optimizedQuery.plan.signature,
        stopwatch.elapsed,
        false,
      );
      
      rethrow;
    }
  }
  
  String _generateQuerySignature<T>(VektagrafList<T> query) {
    // Generate a unique signature for the query structure
    return 'query_${query.hashCode}';
  }
  
  int _estimateQueryComplexity<T>(VektagrafList<T> query) {
    // Simplified complexity estimation
    int complexity = 1;
    
    // Add complexity for each operation
    // This would analyze the actual query operations
    
    return complexity;
  }
}

class OptimizedQuery<T> {
  final VektagrafList<T> originalQuery;
  final QueryPlan plan;
  
  OptimizedQuery(this.originalQuery, this.plan);
  
  Future<List<T>> execute() async {
    // Apply optimizations and execute query
    return await originalQuery.toList();
  }
}

class QueryPlan {
  final String signature;
  final QueryAnalysis analysis;
  final List<QueryOptimization> optimizations;
  final DateTime createdAt;
  final Duration validityPeriod;
  
  QueryPlan({
    required this.signature,
    required this.analysis,
    required this.optimizations,
    required this.createdAt,
    this.validityPeriod = const Duration(hours: 1),
  });
  
  bool get isValid => DateTime.now().difference(createdAt) < validityPeriod;
}

class QueryAnalysis {
  final int complexity;
  final IndexAnalysis indexAnalysis;
  final int estimatedResults;
  final FilterAnalysis filterAnalysis;
  
  QueryAnalysis({
    required this.complexity,
    required this.indexAnalysis,
    required this.estimatedResults,
    required this.filterAnalysis,
  });
}

class IndexAnalysis {
  final List<String> availableIndexes;
  final List<String> missingIndexes;
  final List<String> usableIndexes;
  
  IndexAnalysis({
    required this.availableIndexes,
    required this.missingIndexes,
    required this.usableIndexes,
  });
}

class FilterAnalysis {
  final Map<String, double> selectivity;
  final bool canReorder;
  final List<String> optimalOrder;
  
  FilterAnalysis({
    required this.selectivity,
    required this.canReorder,
    required this.optimalOrder,
  });
}

class QueryOptimization {
  final OptimizationType type;
  final String description;
  final OptimizationImpact impact;
  final Map<String, dynamic> details;
  
  QueryOptimization({
    required this.type,
    required this.description,
    required this.impact,
    required this.details,
  });
}

enum OptimizationType {
  createIndex,
  reorderFilters,
  addLimit,
  useCache,
  partitionData,
}

enum OptimizationImpact { low, medium, high }

class QueryPerformanceTracker {
  final Map<String, QueryPerformanceStats> _stats = {};
  
  void recordExecution(String signature, Duration duration, bool success) {
    final stats = _stats.putIfAbsent(
      signature, 
      () => QueryPerformanceStats(signature),
    );
    
    stats.recordExecution(duration, success);
  }
  
  QueryPerformanceStats? getStats(String signature) {
    return _stats[signature];
  }
  
  Map<String, QueryPerformanceStats> getAllStats() {
    return Map.unmodifiable(_stats);
  }
}

class QueryPerformanceStats {
  final String signature;
  int totalExecutions = 0;
  int successfulExecutions = 0;
  Duration totalDuration = Duration.zero;
  Duration minDuration = Duration(days: 1);
  Duration maxDuration = Duration.zero;
  final List<Duration> recentDurations = [];
  
  QueryPerformanceStats(this.signature);
  
  void recordExecution(Duration duration, bool success) {
    totalExecutions++;
    totalDuration += duration;
    
    if (success) {
      successfulExecutions++;
    }
    
    if (duration < minDuration) {
      minDuration = duration;
    }
    
    if (duration > maxDuration) {
      maxDuration = duration;
    }
    
    recentDurations.add(duration);
    if (recentDurations.length > 100) {
      recentDurations.removeAt(0);
    }
  }
  
  double get successRate => totalExecutions > 0 
      ? successfulExecutions / totalExecutions : 0.0;
  
  Duration get averageDuration => totalExecutions > 0 
      ? Duration(microseconds: totalDuration.inMicroseconds ~/ totalExecutions)
      : Duration.zero;
  
  Duration get p95Duration {
    if (recentDurations.isEmpty) return Duration.zero;
    
    final sorted = List<Duration>.from(recentDurations)..sort();
    final index = (sorted.length * 0.95).floor();
    return sorted[index.clamp(0, sorted.length - 1)];
  }
}
```#
### 2. Vector Search Optimization

```dart
// Specialized optimization for vector search operations
class VectorSearchOptimizer {
  final VectorSpaceOptimizer _spaceOptimizer;
  final Map<String, VectorSearchPlan> _searchPlans = {};
  
  VectorSearchOptimizer(this._spaceOptimizer);
  
  Future<OptimizedVectorSearch> optimizeVectorSearch({
    required String vectorSpaceName,
    required List<double> queryVector,
    required int k,
    Map<String, dynamic>? filters,
  }) async {
    final planKey = _generateSearchPlanKey(vectorSpaceName, k, filters);
    
    // Check for cached plan
    var plan = _searchPlans[planKey];
    if (plan == null || plan.isExpired) {
      plan = await _createSearchPlan(vectorSpaceName, k, filters);
      _searchPlans[planKey] = plan;
    }
    
    return OptimizedVectorSearch(
      vectorSpaceName: vectorSpaceName,
      queryVector: queryVector,
      k: k,
      filters: filters,
      plan: plan,
    );
  }
  
  Future<VectorSearchPlan> _createSearchPlan(
    String vectorSpaceName,
    int k,
    Map<String, dynamic>? filters,
  ) async {
    // Analyze vector space characteristics
    final spaceAnalysis = await _analyzeVectorSpace(vectorSpaceName);
    
    // Determine optimal algorithm parameters
    final algorithmParams = _optimizeAlgorithmParameters(
      spaceAnalysis, k, filters);
    
    // Analyze filter selectivity
    final filterAnalysis = await _analyzeFilterSelectivity(
      vectorSpaceName, filters);
    
    return VectorSearchPlan(
      vectorSpaceName: vectorSpaceName,
      spaceAnalysis: spaceAnalysis,
      algorithmParams: algorithmParams,
      filterAnalysis: filterAnalysis,
      createdAt: DateTime.now(),
    );
  }
  
  Future<VectorSpaceAnalysis> _analyzeVectorSpace(String spaceName) async {
    final metrics = _spaceOptimizer.usageMetrics[spaceName];
    
    return VectorSpaceAnalysis(
      vectorCount: metrics?.vectorCount ?? 0,
      dimensions: 512, // Would get from actual space config
      averageQueryLatency: metrics?.averageQueryLatencyMs ?? 0.0,
      indexType: 'hnsw', // Would get from actual space config
      memoryUsage: metrics?.memoryUsageBytes ?? 0,
    );
  }
  
  Map<String, dynamic> _optimizeAlgorithmParameters(
    VectorSpaceAnalysis analysis,
    int k,
    Map<String, dynamic>? filters,
  ) {
    final params = <String, dynamic>{};
    
    if (analysis.indexType == 'hnsw') {
      // Optimize HNSW parameters
      params['efSearch'] = _calculateOptimalEfSearch(analysis, k);
      params['maxConnections'] = _calculateOptimalMaxConnections(analysis);
    } else if (analysis.indexType == 'ivfflat') {
      // Optimize IVFFlat parameters
      params['nProbe'] = _calculateOptimalNProbe(analysis, k);
      params['nLists'] = _calculateOptimalNLists(analysis);
    }
    
    // Adjust for filters
    if (filters != null && filters.isNotEmpty) {
      params['preFilter'] = _shouldPreFilter(analysis, filters);
      params['filterSelectivity'] = _estimateFilterSelectivity(filters);
    }
    
    return params;
  }
  
  int _calculateOptimalEfSearch(VectorSpaceAnalysis analysis, int k) {
    // Dynamic efSearch calculation based on accuracy vs speed tradeoff
    int baseEfSearch = k * 2;
    
    // Adjust based on vector count
    if (analysis.vectorCount > 100000) {
      baseEfSearch = (baseEfSearch * 1.5).round();
    }
    
    // Adjust based on current performance
    if (analysis.averageQueryLatency > 100) {
      baseEfSearch = (baseEfSearch * 0.8).round();
    }
    
    return baseEfSearch.clamp(k, k * 10);
  }
  
  int _calculateOptimalMaxConnections(VectorSpaceAnalysis analysis) {
    // Optimize based on memory vs accuracy tradeoff
    if (analysis.memoryUsage > 1024 * 1024 * 1024) { // > 1GB
      return 16; // Lower connections to save memory
    } else {
      return 32; // Higher connections for better accuracy
    }
  }
  
  Future<List<T>> executeOptimizedSearch<T>(
    OptimizedVectorSearch search,
    Future<List<T>> Function() executor,
  ) async {
    final stopwatch = Stopwatch()..start();
    
    try {
      // Apply optimizations before execution
      await _applyOptimizations(search);
      
      final results = await executor();
      stopwatch.stop();
      
      // Record performance metrics
      _spaceOptimizer.recordQueryMetric(
        search.vectorSpaceName,
        stopwatch.elapsed,
      );
      
      return results;
    } catch (e) {
      stopwatch.stop();
      rethrow;
    }
  }
  
  Future<void> _applyOptimizations(OptimizedVectorSearch search) async {
    // Apply algorithm parameter optimizations
    // This would configure the actual vector space with optimized parameters
  }
  
  String _generateSearchPlanKey(
    String spaceName,
    int k,
    Map<String, dynamic>? filters,
  ) {
    final filterKey = filters?.keys.join(',') ?? '';
    return '${spaceName}_${k}_$filterKey';
  }
}

class OptimizedVectorSearch {
  final String vectorSpaceName;
  final List<double> queryVector;
  final int k;
  final Map<String, dynamic>? filters;
  final VectorSearchPlan plan;
  
  OptimizedVectorSearch({
    required this.vectorSpaceName,
    required this.queryVector,
    required this.k,
    required this.filters,
    required this.plan,
  });
}

class VectorSearchPlan {
  final String vectorSpaceName;
  final VectorSpaceAnalysis spaceAnalysis;
  final Map<String, dynamic> algorithmParams;
  final FilterAnalysis filterAnalysis;
  final DateTime createdAt;
  final Duration validityPeriod;
  
  VectorSearchPlan({
    required this.vectorSpaceName,
    required this.spaceAnalysis,
    required this.algorithmParams,
    required this.filterAnalysis,
    required this.createdAt,
    this.validityPeriod = const Duration(minutes: 30),
  });
  
  bool get isExpired => DateTime.now().difference(createdAt) > validityPeriod;
}

class VectorSpaceAnalysis {
  final int vectorCount;
  final int dimensions;
  final double averageQueryLatency;
  final String indexType;
  final int memoryUsage;
  
  VectorSpaceAnalysis({
    required this.vectorCount,
    required this.dimensions,
    required this.averageQueryLatency,
    required this.indexType,
    required this.memoryUsage,
  });
}
```### C
aching Strategies

#### 1. Multi-Level Caching System

```dart
// Comprehensive caching system for Vektagraf
class VektagrafCacheManager {
  final L1Cache _l1Cache; // In-memory, fastest
  final L2Cache _l2Cache; // Compressed in-memory
  final L3Cache _l3Cache; // Persistent disk cache
  final CacheMetrics _metrics;
  
  VektagrafCacheManager({
    int l1MaxSize = 1000,
    int l2MaxSize = 10000,
    int l3MaxSize = 100000,
  }) : _l1Cache = L1Cache(l1MaxSize),
       _l2Cache = L2Cache(l2MaxSize),
       _l3Cache = L3Cache(l3MaxSize),
       _metrics = CacheMetrics();
  
  Future<T?> get<T>(String key) async {
    _metrics.recordAccess(key);
    
    // Try L1 cache first
    final l1Result = _l1Cache.get<T>(key);
    if (l1Result != null) {
      _metrics.recordHit(key, CacheLevel.l1);
      return l1Result;
    }
    
    // Try L2 cache
    final l2Result = await _l2Cache.get<T>(key);
    if (l2Result != null) {
      _metrics.recordHit(key, CacheLevel.l2);
      // Promote to L1
      _l1Cache.put(key, l2Result);
      return l2Result;
    }
    
    // Try L3 cache
    final l3Result = await _l3Cache.get<T>(key);
    if (l3Result != null) {
      _metrics.recordHit(key, CacheLevel.l3);
      // Promote to L2 and L1
      await _l2Cache.put(key, l3Result);
      _l1Cache.put(key, l3Result);
      return l3Result;
    }
    
    _metrics.recordMiss(key);
    return null;
  }
  
  Future<void> put<T>(String key, T value, {Duration? ttl}) async {
    // Store in all cache levels
    _l1Cache.put(key, value, ttl: ttl);
    await _l2Cache.put(key, value, ttl: ttl);
    await _l3Cache.put(key, value, ttl: ttl);
    
    _metrics.recordStore(key);
  }
  
  Future<void> invalidate(String key) async {
    _l1Cache.remove(key);
    await _l2Cache.remove(key);
    await _l3Cache.remove(key);
    
    _metrics.recordInvalidation(key);
  }
  
  Future<void> invalidatePattern(String pattern) async {
    final regex = RegExp(pattern);
    
    await _l1Cache.removeWhere((key) => regex.hasMatch(key));
    await _l2Cache.removeWhere((key) => regex.hasMatch(key));
    await _l3Cache.removeWhere((key) => regex.hasMatch(key));
  }
  
  CacheStatistics getStatistics() {
    return CacheStatistics(
      l1Stats: _l1Cache.getStats(),
      l2Stats: _l2Cache.getStats(),
      l3Stats: _l3Cache.getStats(),
      overallMetrics: _metrics.getOverallMetrics(),
    );
  }
}

// L1 Cache: Fast in-memory cache with LRU eviction
class L1Cache {
  final int maxSize;
  final Map<String, CacheEntry> _cache = {};
  final List<String> _accessOrder = [];
  
  L1Cache(this.maxSize);
  
  T? get<T>(String key) {
    final entry = _cache[key];
    if (entry == null || entry.isExpired) {
      _cache.remove(key);
      _accessOrder.remove(key);
      return null;
    }
    
    // Update access order (LRU)
    _accessOrder.remove(key);
    _accessOrder.add(key);
    
    return entry.value as T;
  }
  
  void put<T>(String key, T value, {Duration? ttl}) {
    // Remove if already exists
    if (_cache.containsKey(key)) {
      _accessOrder.remove(key);
    }
    
    // Evict if at capacity
    while (_cache.length >= maxSize && _accessOrder.isNotEmpty) {
      final oldestKey = _accessOrder.removeAt(0);
      _cache.remove(oldestKey);
    }
    
    // Add new entry
    _cache[key] = CacheEntry(
      value: value,
      expiresAt: ttl != null ? DateTime.now().add(ttl) : null,
    );
    _accessOrder.add(key);
  }
  
  void remove(String key) {
    _cache.remove(key);
    _accessOrder.remove(key);
  }
  
  Future<void> removeWhere(bool Function(String) predicate) async {
    final keysToRemove = _cache.keys.where(predicate).toList();
    for (final key in keysToRemove) {
      remove(key);
    }
  }
  
  CacheLevelStats getStats() {
    return CacheLevelStats(
      size: _cache.length,
      maxSize: maxSize,
      hitRate: 0.0, // Would be calculated from metrics
    );
  }
}

// L2 Cache: Compressed in-memory cache
class L2Cache {
  final int maxSize;
  final Map<String, CompressedCacheEntry> _cache = {};
  
  L2Cache(this.maxSize);
  
  Future<T?> get<T>(String key) async {
    final entry = _cache[key];
    if (entry == null || entry.isExpired) {
      _cache.remove(key);
      return null;
    }
    
    // Decompress and deserialize
    return await entry.getValue<T>();
  }
  
  Future<void> put<T>(String key, T value, {Duration? ttl}) async {
    // Evict if at capacity
    if (_cache.length >= maxSize) {
      _evictOldest();
    }
    
    // Compress and store
    _cache[key] = CompressedCacheEntry(
      compressedData: await _compress(value),
      expiresAt: ttl != null ? DateTime.now().add(ttl) : null,
    );
  }
  
  Future<void> remove(String key) async {
    _cache.remove(key);
  }
  
  Future<void> removeWhere(bool Function(String) predicate) async {
    final keysToRemove = _cache.keys.where(predicate).toList();
    for (final key in keysToRemove) {
      await remove(key);
    }
  }
  
  void _evictOldest() {
    if (_cache.isNotEmpty) {
      final oldestKey = _cache.keys.first;
      _cache.remove(oldestKey);
    }
  }
  
  Future<Uint8List> _compress<T>(T value) async {
    // Simplified compression - would use actual compression library
    final json = jsonEncode(value);
    return utf8.encode(json);
  }
  
  CacheLevelStats getStats() {
    return CacheLevelStats(
      size: _cache.length,
      maxSize: maxSize,
      hitRate: 0.0,
    );
  }
}

// L3 Cache: Persistent disk cache
class L3Cache {
  final int maxSize;
  final String cacheDir = '.cache/vektagraf';
  final Map<String, DateTime> _index = {};
  
  L3Cache(this.maxSize);
  
  Future<T?> get<T>(String key) async {
    final filePath = _getFilePath(key);
    final file = File(filePath);
    
    if (!await file.exists()) {
      _index.remove(key);
      return null;
    }
    
    try {
      final data = await file.readAsBytes();
      final json = utf8.decode(data);
      return jsonDecode(json) as T;
    } catch (e) {
      // Remove corrupted cache entry
      await file.delete();
      _index.remove(key);
      return null;
    }
  }
  
  Future<void> put<T>(String key, T value, {Duration? ttl}) async {
    // Ensure cache directory exists
    final dir = Directory(cacheDir);
    if (!await dir.exists()) {
      await dir.create(recursive: true);
    }
    
    // Evict if at capacity
    if (_index.length >= maxSize) {
      await _evictOldest();
    }
    
    // Write to disk
    final filePath = _getFilePath(key);
    final file = File(filePath);
    final json = jsonEncode(value);
    await file.writeAsBytes(utf8.encode(json));
    
    _index[key] = DateTime.now();
  }
  
  Future<void> remove(String key) async {
    final filePath = _getFilePath(key);
    final file = File(filePath);
    
    if (await file.exists()) {
      await file.delete();
    }
    
    _index.remove(key);
  }
  
  Future<void> removeWhere(bool Function(String) predicate) async {
    final keysToRemove = _index.keys.where(predicate).toList();
    for (final key in keysToRemove) {
      await remove(key);
    }
  }
  
  Future<void> _evictOldest() async {
    if (_index.isNotEmpty) {
      final oldestEntry = _index.entries.reduce((a, b) => 
          a.value.isBefore(b.value) ? a : b);
      await remove(oldestEntry.key);
    }
  }
  
  String _getFilePath(String key) {
    final hashedKey = key.hashCode.abs().toString();
    return '$cacheDir/$hashedKey.cache';
  }
  
  CacheLevelStats getStats() {
    return CacheLevelStats(
      size: _index.length,
      maxSize: maxSize,
      hitRate: 0.0,
    );
  }
}

class CacheEntry {
  final dynamic value;
  final DateTime? expiresAt;
  
  CacheEntry({
    required this.value,
    this.expiresAt,
  });
  
  bool get isExpired => expiresAt != null && DateTime.now().isAfter(expiresAt!);
}

class CompressedCacheEntry {
  final Uint8List compressedData;
  final DateTime? expiresAt;
  
  CompressedCacheEntry({
    required this.compressedData,
    this.expiresAt,
  });
  
  bool get isExpired => expiresAt != null && DateTime.now().isAfter(expiresAt!);
  
  Future<T> getValue<T>() async {
    // Decompress and deserialize
    final json = utf8.decode(compressedData);
    return jsonDecode(json) as T;
  }
}

enum CacheLevel { l1, l2, l3 }

class CacheMetrics {
  final Map<String, int> _accessCounts = {};
  final Map<String, Map<CacheLevel, int>> _hitCounts = {};
  final Map<String, int> _missCounts = {};
  
  void recordAccess(String key) {
    _accessCounts[key] = (_accessCounts[key] ?? 0) + 1;
  }
  
  void recordHit(String key, CacheLevel level) {
    _hitCounts.putIfAbsent(key, () => {});
    _hitCounts[key]![level] = (_hitCounts[key]![level] ?? 0) + 1;
  }
  
  void recordMiss(String key) {
    _missCounts[key] = (_missCounts[key] ?? 0) + 1;
  }
  
  void recordStore(String key) {
    // Track storage operations
  }
  
  void recordInvalidation(String key) {
    // Track invalidation operations
  }
  
  Map<String, dynamic> getOverallMetrics() {
    final totalAccesses = _accessCounts.values.fold<int>(0, (sum, count) => sum + count);
    final totalHits = _hitCounts.values.fold<int>(0, (sum, levelHits) => 
        sum + levelHits.values.fold<int>(0, (levelSum, count) => levelSum + count));
    final totalMisses = _missCounts.values.fold<int>(0, (sum, count) => sum + count);
    
    return {
      'total_accesses': totalAccesses,
      'total_hits': totalHits,
      'total_misses': totalMisses,
      'hit_rate': totalAccesses > 0 ? totalHits / totalAccesses : 0.0,
      'miss_rate': totalAccesses > 0 ? totalMisses / totalAccesses : 0.0,
    };
  }
}

class CacheStatistics {
  final CacheLevelStats l1Stats;
  final CacheLevelStats l2Stats;
  final CacheLevelStats l3Stats;
  final Map<String, dynamic> overallMetrics;
  
  CacheStatistics({
    required this.l1Stats,
    required this.l2Stats,
    required this.l3Stats,
    required this.overallMetrics,
  });
}

class CacheLevelStats {
  final int size;
  final int maxSize;
  final double hitRate;
  
  CacheLevelStats({
    required this.size,
    required this.maxSize,
    required this.hitRate,
  });
  
  double get utilizationRate => size / maxSize;
}
```## Bes
t Practices

### Performance Optimization Methodology

#### 1. Systematic Performance Testing

```dart
// Comprehensive performance testing framework
class PerformanceTestSuite {
  final VektagrafDatabase database;
  final VektagrafProfiler profiler;
  final List<PerformanceTest> tests = [];
  
  PerformanceTestSuite(this.database) : profiler = VektagrafProfiler();
  
  void addTest(PerformanceTest test) {
    tests.add(test);
  }
  
  Future<PerformanceTestReport> runAllTests() async {
    final results = <PerformanceTestResult>[];
    
    for (final test in tests) {
      print('Running test: ${test.name}');
      
      try {
        final result = await _runTest(test);
        results.add(result);
        
        print('✓ ${test.name}: ${result.summary}');
      } catch (e) {
        print('✗ ${test.name}: Failed - $e');
        
        results.add(PerformanceTestResult(
          testName: test.name,
          success: false,
          error: e.toString(),
          duration: Duration.zero,
          metrics: {},
        ));
      }
    }
    
    return PerformanceTestReport(
      results: results,
      executedAt: DateTime.now(),
      summary: _generateSummary(results),
    );
  }
  
  Future<PerformanceTestResult> _runTest(PerformanceTest test) async {
    // Setup test environment
    await test.setup(database);
    
    final stopwatch = Stopwatch()..start();
    final session = profiler.startSession(test.name);
    
    try {
      // Execute test
      final metrics = await test.execute(database, session);
      
      stopwatch.stop();
      session.end();
      
      return PerformanceTestResult(
        testName: test.name,
        success: true,
        duration: stopwatch.elapsed,
        metrics: metrics,
        profileData: session.getResult(),
      );
    } finally {
      // Cleanup test environment
      await test.cleanup(database);
    }
  }
  
  Map<String, dynamic> _generateSummary(List<PerformanceTestResult> results) {
    final successful = results.where((r) => r.success).length;
    final failed = results.length - successful;
    
    final totalDuration = results.fold<Duration>(
      Duration.zero, 
      (sum, result) => sum + result.duration,
    );
    
    return {
      'total_tests': results.length,
      'successful': successful,
      'failed': failed,
      'success_rate': results.isNotEmpty ? successful / results.length : 0.0,
      'total_duration_ms': totalDuration.inMilliseconds,
      'average_duration_ms': results.isNotEmpty 
          ? totalDuration.inMilliseconds / results.length : 0,
    };
  }
}

abstract class PerformanceTest {
  String get name;
  String get description;
  
  Future<void> setup(VektagrafDatabase database);
  Future<Map<String, dynamic>> execute(
    VektagrafDatabase database, 
    ProfilerSession session,
  );
  Future<void> cleanup(VektagrafDatabase database);
}

class DatabaseOperationPerformanceTest implements PerformanceTest {
  @override
  String get name => 'database_operations';
  
  @override
  String get description => 'Test CRUD operation performance';
  
  final int objectCount;
  final List<TestObject> testObjects = [];
  
  DatabaseOperationPerformanceTest({this.objectCount = 1000});
  
  @override
  Future<void> setup(VektagrafDatabase database) async {
    // Generate test objects
    for (int i = 0; i < objectCount; i++) {
      testObjects.add(TestObject(
        id: VektagrafId.generate(),
        name: 'Test Object $i',
        value: i,
        data: List.generate(100, (j) => 'data_${i}_$j'),
      ));
    }
  }
  
  @override
  Future<Map<String, dynamic>> execute(
    VektagrafDatabase database,
    ProfilerSession session,
  ) async {
    final metrics = <String, dynamic>{};
    
    // Test create operations
    session.recordEvent('create_start');
    final createStopwatch = Stopwatch()..start();
    
    await database.transaction((txn) async {
      for (final obj in testObjects) {
        await txn.save(obj);
      }
    });
    
    createStopwatch.stop();
    session.recordEvent('create_end');
    session.recordMetric('create_duration_ms', createStopwatch.elapsedMilliseconds);
    
    metrics['create_ops_per_second'] = 
        objectCount / (createStopwatch.elapsedMilliseconds / 1000.0);
    
    // Test read operations
    session.recordEvent('read_start');
    final readStopwatch = Stopwatch()..start();
    
    for (final obj in testObjects) {
      await database.findById(obj.id);
    }
    
    readStopwatch.stop();
    session.recordEvent('read_end');
    session.recordMetric('read_duration_ms', readStopwatch.elapsedMilliseconds);
    
    metrics['read_ops_per_second'] = 
        objectCount / (readStopwatch.elapsedMilliseconds / 1000.0);
    
    // Test query operations
    session.recordEvent('query_start');
    final queryStopwatch = Stopwatch()..start();
    
    final queryResults = await database.query((obj) => 
        obj.type == 'TestObject').toList();
    
    queryStopwatch.stop();
    session.recordEvent('query_end');
    session.recordMetric('query_duration_ms', queryStopwatch.elapsedMilliseconds);
    
    metrics['query_result_count'] = queryResults.length;
    metrics['query_duration_ms'] = queryStopwatch.elapsedMilliseconds;
    
    return metrics;
  }
  
  @override
  Future<void> cleanup(VektagrafDatabase database) async {
    // Clean up test objects
    await database.transaction((txn) async {
      for (final obj in testObjects) {
        await txn.delete(obj);
      }
    });
    
    testObjects.clear();
  }
}

class VectorSearchPerformanceTest implements PerformanceTest {
  @override
  String get name => 'vector_search';
  
  @override
  String get description => 'Test vector search performance';
  
  final int vectorCount;
  final int dimensions;
  final List<TestVector> testVectors = [];
  
  VectorSearchPerformanceTest({
    this.vectorCount = 10000,
    this.dimensions = 512,
  });
  
  @override
  Future<void> setup(VektagrafDatabase database) async {
    // Generate test vectors
    final random = Random();
    
    for (int i = 0; i < vectorCount; i++) {
      final vector = List.generate(dimensions, (_) => random.nextDouble());
      
      testVectors.add(TestVector(
        id: VektagrafId.generate(),
        embedding: vector,
        metadata: {'index': i, 'category': 'test'},
      ));
    }
    
    // Insert test vectors
    await database.transaction((txn) async {
      for (final vector in testVectors) {
        await txn.save(vector);
      }
    });
  }
  
  @override
  Future<Map<String, dynamic>> execute(
    VektagrafDatabase database,
    ProfilerSession session,
  ) async {
    final metrics = <String, dynamic>{};
    final random = Random();
    
    // Generate query vectors
    final queryVectors = List.generate(100, (_) => 
        List.generate(dimensions, (_) => random.nextDouble()));
    
    // Test vector search performance
    session.recordEvent('vector_search_start');
    final searchStopwatch = Stopwatch()..start();
    
    int totalResults = 0;
    
    for (final queryVector in queryVectors) {
      final results = await database.testVectors()
          .vectorSearch(
            query: queryVector,
            limit: 10,
          );
      
      totalResults += results.length;
    }
    
    searchStopwatch.stop();
    session.recordEvent('vector_search_end');
    
    metrics['search_count'] = queryVectors.length;
    metrics['total_results'] = totalResults;
    metrics['average_results_per_query'] = totalResults / queryVectors.length;
    metrics['total_duration_ms'] = searchStopwatch.elapsedMilliseconds;
    metrics['average_query_duration_ms'] = 
        searchStopwatch.elapsedMilliseconds / queryVectors.length;
    metrics['queries_per_second'] = 
        queryVectors.length / (searchStopwatch.elapsedMilliseconds / 1000.0);
    
    return metrics;
  }
  
  @override
  Future<void> cleanup(VektagrafDatabase database) async {
    // Clean up test vectors
    await database.transaction((txn) async {
      for (final vector in testVectors) {
        await txn.delete(vector);
      }
    });
    
    testVectors.clear();
  }
}

class PerformanceTestResult {
  final String testName;
  final bool success;
  final String? error;
  final Duration duration;
  final Map<String, dynamic> metrics;
  final BenchmarkResult? profileData;
  
  PerformanceTestResult({
    required this.testName,
    required this.success,
    this.error,
    required this.duration,
    required this.metrics,
    this.profileData,
  });
  
  String get summary {
    if (!success) return 'Failed';
    
    final opsPerSecond = metrics['ops_per_second'] as double?;
    if (opsPerSecond != null) {
      return '${opsPerSecond.toStringAsFixed(1)} ops/sec';
    }
    
    return '${duration.inMilliseconds}ms';
  }
}

class PerformanceTestReport {
  final List<PerformanceTestResult> results;
  final DateTime executedAt;
  final Map<String, dynamic> summary;
  
  PerformanceTestReport({
    required this.results,
    required this.executedAt,
    required this.summary,
  });
  
  void printReport() {
    print('\n=== Performance Test Report ===');
    print('Executed: ${executedAt.toIso8601String()}');
    print('Tests: ${summary['total_tests']}');
    print('Success Rate: ${(summary['success_rate'] * 100).toStringAsFixed(1)}%');
    print('Total Duration: ${summary['total_duration_ms']}ms');
    print('\nResults:');
    
    for (final result in results) {
      final status = result.success ? '✓' : '✗';
      print('  $status ${result.testName}: ${result.summary}');
      
      if (!result.success && result.error != null) {
        print('    Error: ${result.error}');
      }
    }
    
    print('\n');
  }
}

// Test data models
@VektagrafModel()
class TestObject extends VektagrafObject {
  @VektagrafProperty()
  String name;
  
  @VektagrafProperty()
  int value;
  
  @VektagrafProperty()
  List<String> data;
  
  TestObject({
    required VektagrafId id,
    required this.name,
    required this.value,
    required this.data,
  }) : super(id: id);
}

@VektagrafModel()
class TestVector extends VektagrafObject {
  @VektagrafProperty()
  @VektagrafVector(dimensions: 512)
  List<double> embedding;
  
  @VektagrafProperty()
  Map<String, dynamic> metadata;
  
  TestVector({
    required VektagrafId id,
    required this.embedding,
    required this.metadata,
  }) : super(id: id);
}
```###
# 2. Performance Monitoring and Alerting

```dart
// Continuous performance monitoring system
class PerformanceMonitor {
  final VektagrafDatabase database;
  final SystemMetricsCollector metricsCollector;
  final List<PerformanceThreshold> thresholds = [];
  final StreamController<PerformanceAlert> alertController;
  
  Timer? _monitoringTimer;
  
  PerformanceMonitor(this.database, this.metricsCollector)
      : alertController = StreamController<PerformanceAlert>.broadcast();
  
  Stream<PerformanceAlert> get alerts => alertController.stream;
  
  void addThreshold(PerformanceThreshold threshold) {
    thresholds.add(threshold);
  }
  
  void startMonitoring({Duration interval = const Duration(minutes: 1)}) {
    _monitoringTimer = Timer.periodic(interval, (_) => _checkPerformance());
  }
  
  void stopMonitoring() {
    _monitoringTimer?.cancel();
  }
  
  Future<void> _checkPerformance() async {
    try {
      final metrics = await _collectCurrentMetrics();
      
      for (final threshold in thresholds) {
        final violation = threshold.checkViolation(metrics);
        if (violation != null) {
          alertController.add(violation);
        }
      }
    } catch (e) {
      print('Error during performance monitoring: $e');
    }
  }
  
  Future<PerformanceMetrics> _collectCurrentMetrics() async {
    // Collect various performance metrics
    final queryLatencies = await _getRecentQueryLatencies();
    final memoryUsage = await _getCurrentMemoryUsage();
    final throughput = await _getCurrentThroughput();
    final errorRate = await _getCurrentErrorRate();
    
    return PerformanceMetrics(
      averageQueryLatency: queryLatencies.isNotEmpty 
          ? queryLatencies.reduce((a, b) => a + b) / queryLatencies.length
          : 0.0,
      p95QueryLatency: _calculatePercentile(queryLatencies, 0.95),
      memoryUsageRatio: memoryUsage,
      throughputOpsPerSecond: throughput,
      errorRate: errorRate,
      timestamp: DateTime.now(),
    );
  }
  
  Future<List<double>> _getRecentQueryLatencies() async {
    // Get recent query latencies from metrics
    final metrics = await metricsCollector.queryMetrics(
      name: 'vektagraf_query_duration_seconds',
      startTime: DateTime.now().subtract(Duration(minutes: 5)),
      endTime: DateTime.now(),
    );
    
    return metrics.map((m) => m.value).toList();
  }
  
  double _calculatePercentile(List<double> values, double percentile) {
    if (values.isEmpty) return 0.0;
    
    final sorted = List<double>.from(values)..sort();
    final index = (sorted.length * percentile).floor();
    return sorted[index.clamp(0, sorted.length - 1)];
  }
}

class PerformanceThreshold {
  final String name;
  final String metric;
  final double threshold;
  final ThresholdComparison comparison;
  final Duration sustainedDuration;
  final AlertSeverity severity;
  
  final List<DateTime> _violations = [];
  
  PerformanceThreshold({
    required this.name,
    required this.metric,
    required this.threshold,
    required this.comparison,
    this.sustainedDuration = const Duration(minutes: 2),
    this.severity = AlertSeverity.warning,
  });
  
  PerformanceAlert? checkViolation(PerformanceMetrics metrics) {
    final value = _getMetricValue(metrics);
    final isViolation = _checkThreshold(value);
    
    final now = DateTime.now();
    
    if (isViolation) {
      _violations.add(now);
    }
    
    // Remove old violations
    _violations.removeWhere((time) => 
        now.difference(time) > sustainedDuration);
    
    // Check if violation is sustained
    if (_violations.isNotEmpty && 
        now.difference(_violations.first) >= sustainedDuration) {
      
      return PerformanceAlert(
        name: name,
        metric: metric,
        currentValue: value,
        threshold: threshold,
        severity: severity,
        triggeredAt: now,
        sustainedFor: now.difference(_violations.first),
      );
    }
    
    return null;
  }
  
  double _getMetricValue(PerformanceMetrics metrics) {
    switch (metric) {
      case 'average_query_latency':
        return metrics.averageQueryLatency;
      case 'p95_query_latency':
        return metrics.p95QueryLatency;
      case 'memory_usage_ratio':
        return metrics.memoryUsageRatio;
      case 'throughput':
        return metrics.throughputOpsPerSecond;
      case 'error_rate':
        return metrics.errorRate;
      default:
        return 0.0;
    }
  }
  
  bool _checkThreshold(double value) {
    switch (comparison) {
      case ThresholdComparison.greaterThan:
        return value > threshold;
      case ThresholdComparison.lessThan:
        return value < threshold;
      case ThresholdComparison.equals:
        return value == threshold;
    }
  }
}

class PerformanceMetrics {
  final double averageQueryLatency;
  final double p95QueryLatency;
  final double memoryUsageRatio;
  final double throughputOpsPerSecond;
  final double errorRate;
  final DateTime timestamp;
  
  PerformanceMetrics({
    required this.averageQueryLatency,
    required this.p95QueryLatency,
    required this.memoryUsageRatio,
    required this.throughputOpsPerSecond,
    required this.errorRate,
    required this.timestamp,
  });
}

class PerformanceAlert {
  final String name;
  final String metric;
  final double currentValue;
  final double threshold;
  final AlertSeverity severity;
  final DateTime triggeredAt;
  final Duration sustainedFor;
  
  PerformanceAlert({
    required this.name,
    required this.metric,
    required this.currentValue,
    required this.threshold,
    required this.severity,
    required this.triggeredAt,
    required this.sustainedFor,
  });
  
  @override
  String toString() {
    return '${severity.name.toUpperCase()}: $name - '
           '$metric is $currentValue (threshold: $threshold) '
           'for ${sustainedFor.inMinutes} minutes';
  }
}

enum ThresholdComparison { greaterThan, lessThan, equals }
enum AlertSeverity { info, warning, critical }

Scaling Strategies

1. Horizontal Scaling Architecture

// Distributed Vektagraf architecture for horizontal scaling
class DistributedVektagrafCluster {
  final List<VektagrafNode> nodes = [];
  final ConsistentHashRing hashRing;
  final ClusterCoordinator coordinator;
  
  DistributedVektagrafCluster({
    required List<String> nodeEndpoints,
  }) : hashRing = ConsistentHashRing(),
       coordinator = ClusterCoordinator() {
    
    // Initialize nodes
    for (final endpoint in nodeEndpoints) {
      final node = VektagrafNode(endpoint);
      nodes.add(node);
      hashRing.addNode(node);
    }
  }
  
  Future<void> initialize() async {
    // Initialize all nodes
    for (final node in nodes) {
      await node.initialize();
    }
    
    // Start cluster coordination
    await coordinator.start(nodes);
  }
  
  Future<T> executeOperation<T>(
    String key,
    Future<T> Function(VektagrafNode) operation,
  ) async {
    final targetNode = hashRing.getNode(key);
    
    try {
      return await operation(targetNode);
    } catch (e) {
      // Handle node failure with failover
      return await _handleFailover(key, operation, targetNode);
    }
  }
  
  Future<T> _handleFailover<T>(
    String key,
    Future<T> Function(VektagrafNode) operation,
    VektagrafNode failedNode,
  ) async {
    // Mark node as failed
    coordinator.markNodeFailed(failedNode);
    
    // Get backup node
    final backupNode = hashRing.getBackupNode(key, failedNode);
    
    if (backupNode != null) {
      return await operation(backupNode);
    }
    
    throw ClusterException('No available nodes for key: $key');
  }
  
  Future<List<T>> executeDistributedQuery<T>(
    Future<List<T>> Function(VektagrafNode) query,
  ) async {
    final results = <T>[];
    final futures = <Future<List<T>>>[];
    
    // Execute query on all healthy nodes
    for (final node in nodes) {
      if (coordinator.isNodeHealthy(node)) {
        futures.add(query(node));
      }
    }
    
    // Collect results from all nodes
    final nodeResults = await Future.wait(futures);
    
    for (final nodeResult in nodeResults) {
      results.addAll(nodeResult);
    }
    
    return results;
  }
  
  Future<void> rebalanceCluster() async {
    await coordinator.rebalanceData(nodes, hashRing);
  }
}

class VektagrafNode {
  final String endpoint;
  late VektagrafDatabase database;
  bool isHealthy = true;
  
  VektagrafNode(this.endpoint);
  
  Future<void> initialize() async {
    // Initialize database connection
    database = await VektagrafDatabase.open(
      'node_${endpoint.hashCode}.db',
      config: VektagrafConfig(
        // Node-specific configuration
      ),
    );
  }
  
  Future<bool> healthCheck() async {
    try {
      // Perform health check query
      await database.query((_) => false).take(1).toList();
      isHealthy = true;
      return true;
    } catch (e) {
      isHealthy = false;
      return false;
    }
  }
}

class ConsistentHashRing {
  final Map<int, VektagrafNode> _ring = {};
  final int _virtualNodes = 150;
  
  void addNode(VektagrafNode node) {
    for (int i = 0; i < _virtualNodes; i++) {
      final hash = _hash('${node.endpoint}:$i');
      _ring[hash] = node;
    }
  }
  
  void removeNode(VektagrafNode node) {
    for (int i = 0; i < _virtualNodes; i++) {
      final hash = _hash('${node.endpoint}:$i');
      _ring.remove(hash);
    }
  }
  
  VektagrafNode getNode(String key) {
    if (_ring.isEmpty) {
      throw ClusterException('No nodes available in hash ring');
    }
    
    final keyHash = _hash(key);
    
    // Find the first node clockwise from the key hash
    final sortedHashes = _ring.keys.toList()..sort();
    
    for (final hash in sortedHashes) {
      if (hash >= keyHash) {
        return _ring[hash]!;
      }
    }
    
    // Wrap around to the first node
    return _ring[sortedHashes.first]!;
  }
  
  VektagrafNode? getBackupNode(String key, VektagrafNode excludeNode) {
    final keyHash = _hash(key);
    final sortedHashes = _ring.keys.toList()..sort();
    
    for (final hash in sortedHashes) {
      if (hash >= keyHash) {
        final node = _ring[hash]!;
        if (node != excludeNode && node.isHealthy) {
          return node;
        }
      }
    }
    
    // Wrap around
    for (final hash in sortedHashes) {
      final node = _ring[hash]!;
      if (node != excludeNode && node.isHealthy) {
        return node;
      }
    }
    
    return null;
  }
  
  int _hash(String input) {
    return input.hashCode.abs();
  }
}

class ClusterCoordinator {
  final Map<VektagrafNode, NodeStatus> _nodeStatuses = {};
  Timer? _healthCheckTimer;
  
  Future<void> start(List<VektagrafNode> nodes) async {
    // Initialize node statuses
    for (final node in nodes) {
      _nodeStatuses[node] = NodeStatus.healthy;
    }
    
    // Start periodic health checks
    _healthCheckTimer = Timer.periodic(
      Duration(seconds: 30),
      (_) => _performHealthChecks(nodes),
    );
  }
  
  void stop() {
    _healthCheckTimer?.cancel();
  }
  
  void markNodeFailed(VektagrafNode node) {
    _nodeStatuses[node] = NodeStatus.failed;
  }
  
  bool isNodeHealthy(VektagrafNode node) {
    return _nodeStatuses[node] == NodeStatus.healthy;
  }
  
  Future<void> _performHealthChecks(List<VektagrafNode> nodes) async {
    for (final node in nodes) {
      try {
        final isHealthy = await node.healthCheck();
        _nodeStatuses[node] = isHealthy ? NodeStatus.healthy : NodeStatus.failed;
      } catch (e) {
        _nodeStatuses[node] = NodeStatus.failed;
      }
    }
  }
  
  Future<void> rebalanceData(
    List<VektagrafNode> nodes,
    ConsistentHashRing hashRing,
  ) async {
    // Implement data rebalancing logic
    // This would involve moving data between nodes to maintain balance
  }
}

enum NodeStatus { healthy, degraded, failed }

class ClusterException implements Exception {
  final String message;
  
  ClusterException(this.message);
  
  @override
  String toString() => 'ClusterException: $message';
}

Summary

This chapter covered comprehensive performance tuning and optimization for Vektagraf applications, including:

Key Takeaways

  1. Systematic Approach: Use profiling, analysis, optimization, and validation cycles
  2. Memory Optimization: Implement efficient memory usage and garbage collection strategies
  3. Query Optimization: Analyze and optimize query performance with intelligent caching
  4. Vector Search Tuning: Optimize vector search algorithms and parameters
  5. Scaling Strategies: Design horizontal scaling with distributed architectures

Next Steps

  • Chapter 15: Learn about production deployment patterns
  • Chapter 16: Explore scaling and high availability techniques
  • Chapter 17: Discover DevOps and CI/CD integration strategies
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