datapilot-cli/dist/core/performance-presets.d.ts

Enterprise-grade streaming multi-format data analysis with comprehensive statistical insights and intelligent relationship detection - supports CSV, JSON, Excel, TSV, Parquet - memory-efficient, cross-platform

/**
 * Performance Optimization Presets for Large File Processing
 * Optimized configurations for different file sizes and use cases
 */
import type { DataPilotConfig } from './config';
export interface PerformancePreset {
    name: string;
    description: string;
    targetFileSize: string;
    targetMemoryUsage: string;
    expectedPerformance: string;
    config: Partial<DataPilotConfig>;
    optimizations: string[];
    limitations: string[];
}
/**
 * Large File Processing Preset (1-10GB files)
 */
export declare const LARGE_FILE_PRESET: PerformancePreset;
/**
 * Ultra Large File Preset (10-100GB files)
 */
export declare const ULTRA_LARGE_FILE_PRESET: PerformancePreset;
/**
 * Speed Optimized Preset (Fast processing)
 */
export declare const SPEED_OPTIMIZED_PRESET: PerformancePreset;
/**
 * Memory Constrained Preset (Low memory environments)
 */
export declare const MEMORY_CONSTRAINED_PRESET: PerformancePreset;
/**
 * All available performance presets
 */
export declare const PERFORMANCE_PRESETS: Record<string, PerformancePreset>;
/**
 * Automatically select appropriate preset based on file characteristics
 */
export declare function selectOptimalPreset(fileSizeBytes: number, availableMemoryMB: number, userPriority?: 'speed' | 'memory' | 'quality' | 'auto'): PerformancePreset;
/**
 * Apply preset configuration to base config
 */
export declare function applyPerformancePreset(baseConfig: Partial<DataPilotConfig>, preset: PerformancePreset): DataPilotConfig;
/**
 * Get performance recommendations for given file characteristics
 */
export declare function getPerformanceRecommendations(fileSizeBytes: number, availableMemoryMB: number, currentConfig?: Partial<DataPilotConfig>): {
    recommendedPreset: PerformancePreset;
    optimizations: string[];
    warnings: string[];
    estimatedMetrics: {
        processingTimeMinutes: number;
        memoryUsageMB: number;
        qualityScore: number;
    };
};
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