|
| 1 | +/** |
| 2 | + * Benchmark: AutoPack para chamadas ÚNICAS (bee normal, não turbo) |
| 3 | + * |
| 4 | + * Pergunta: Vale a pena usar AutoPack no bee() normal? |
| 5 | + * |
| 6 | + * Cenários: |
| 7 | + * 1. Objeto pequeno (10 campos) |
| 8 | + * 2. Objeto médio (100 campos) |
| 9 | + * 3. Objeto grande (1000 campos) |
| 10 | + * 4. Array pequeno (100 objetos) |
| 11 | + * 5. Array médio (1000 objetos) |
| 12 | + * 6. Array grande (10000 objetos) |
| 13 | + */ |
| 14 | + |
| 15 | +import { autoPack, autoUnpack, clearAutoPackCaches } from '../src/autopack'; |
| 16 | + |
| 17 | +// ============ DATA GENERATORS ============ |
| 18 | + |
| 19 | +function generateObject(fieldCount: number): Record<string, unknown> { |
| 20 | + const obj: Record<string, unknown> = {}; |
| 21 | + for (let i = 0; i < fieldCount; i++) { |
| 22 | + if (i % 3 === 0) obj[`num_${i}`] = Math.random() * 1000; |
| 23 | + else if (i % 3 === 1) obj[`str_${i}`] = `value_${i}_${Math.random().toString(36).slice(2, 10)}`; |
| 24 | + else obj[`bool_${i}`] = i % 2 === 0; |
| 25 | + } |
| 26 | + return obj; |
| 27 | +} |
| 28 | + |
| 29 | +function generateArray(size: number, fieldsPerObject: number): Record<string, unknown>[] { |
| 30 | + const arr: Record<string, unknown>[] = new Array(size); |
| 31 | + for (let i = 0; i < size; i++) { |
| 32 | + arr[i] = generateObject(fieldsPerObject); |
| 33 | + } |
| 34 | + return arr; |
| 35 | +} |
| 36 | + |
| 37 | +// ============ BENCHMARK ============ |
| 38 | + |
| 39 | +interface BenchResult { |
| 40 | + scenario: string; |
| 41 | + dataSize: string; |
| 42 | + packUnpackTime: number; |
| 43 | + structuredCloneTime: number; |
| 44 | + ratio: number; |
| 45 | + verdict: string; |
| 46 | +} |
| 47 | + |
| 48 | +function benchmarkSingle( |
| 49 | + name: string, |
| 50 | + data: Record<string, unknown> | Record<string, unknown>[], |
| 51 | + iterations: number = 100 |
| 52 | +): BenchResult { |
| 53 | + clearAutoPackCaches(); |
| 54 | + |
| 55 | + const dataArray = Array.isArray(data) ? data : [data]; |
| 56 | + |
| 57 | + // Warmup |
| 58 | + for (let i = 0; i < 5; i++) { |
| 59 | + const packed = autoPack(dataArray); |
| 60 | + autoUnpack(packed); |
| 61 | + structuredClone(data); |
| 62 | + } |
| 63 | + |
| 64 | + // Benchmark AutoPack (pack + unpack = roundtrip simulando postMessage) |
| 65 | + const packTimes: number[] = []; |
| 66 | + for (let i = 0; i < iterations; i++) { |
| 67 | + const start = performance.now(); |
| 68 | + const packed = autoPack(dataArray); |
| 69 | + autoUnpack(packed); |
| 70 | + packTimes.push(performance.now() - start); |
| 71 | + } |
| 72 | + |
| 73 | + // Benchmark structuredClone (simula o que postMessage faz) |
| 74 | + const cloneTimes: number[] = []; |
| 75 | + for (let i = 0; i < iterations; i++) { |
| 76 | + const start = performance.now(); |
| 77 | + structuredClone(data); |
| 78 | + cloneTimes.push(performance.now() - start); |
| 79 | + } |
| 80 | + |
| 81 | + // Mediana |
| 82 | + packTimes.sort((a, b) => a - b); |
| 83 | + cloneTimes.sort((a, b) => a - b); |
| 84 | + |
| 85 | + const packTime = packTimes[Math.floor(iterations / 2)]; |
| 86 | + const cloneTime = cloneTimes[Math.floor(iterations / 2)]; |
| 87 | + const ratio = cloneTime / packTime; |
| 88 | + |
| 89 | + // Calcular tamanho aproximado |
| 90 | + const jsonSize = JSON.stringify(data).length; |
| 91 | + const sizeStr = jsonSize < 1024 |
| 92 | + ? `${jsonSize} B` |
| 93 | + : jsonSize < 1024 * 1024 |
| 94 | + ? `${(jsonSize / 1024).toFixed(1)} KB` |
| 95 | + : `${(jsonSize / 1024 / 1024).toFixed(1)} MB`; |
| 96 | + |
| 97 | + const verdict = ratio >= 1.2 |
| 98 | + ? '✅ USAR AutoPack' |
| 99 | + : ratio >= 0.8 |
| 100 | + ? '⚠️ Similar' |
| 101 | + : '❌ NÃO usar'; |
| 102 | + |
| 103 | + return { |
| 104 | + scenario: name, |
| 105 | + dataSize: sizeStr, |
| 106 | + packUnpackTime: packTime, |
| 107 | + structuredCloneTime: cloneTime, |
| 108 | + ratio, |
| 109 | + verdict |
| 110 | + }; |
| 111 | +} |
| 112 | + |
| 113 | +async function main() { |
| 114 | + console.log('╔══════════════════════════════════════════════════════════════════════════════╗'); |
| 115 | + console.log('║ AUTOPACK PARA CHAMADAS ÚNICAS (bee normal) - VALE A PENA? ║'); |
| 116 | + console.log('║ ║'); |
| 117 | + console.log('║ Comparando: autoPack + autoUnpack vs structuredClone ║'); |
| 118 | + console.log('║ (structuredClone é o que postMessage usa internamente) ║'); |
| 119 | + console.log('╚══════════════════════════════════════════════════════════════════════════════╝\n'); |
| 120 | + |
| 121 | + const results: BenchResult[] = []; |
| 122 | + |
| 123 | + // ============ OBJETOS ÚNICOS ============ |
| 124 | + console.log('📦 OBJETOS ÚNICOS (1 objeto, N campos)\n'); |
| 125 | + |
| 126 | + results.push(benchmarkSingle('1 objeto, 10 campos', generateObject(10))); |
| 127 | + results.push(benchmarkSingle('1 objeto, 50 campos', generateObject(50))); |
| 128 | + results.push(benchmarkSingle('1 objeto, 100 campos', generateObject(100))); |
| 129 | + results.push(benchmarkSingle('1 objeto, 500 campos', generateObject(500))); |
| 130 | + results.push(benchmarkSingle('1 objeto, 1000 campos', generateObject(1000))); |
| 131 | + |
| 132 | + console.log('┌─────────────────────────┬──────────┬───────────┬───────────────┬─────────┬──────────────────┐'); |
| 133 | + console.log('│ Cenário │ Tamanho │ AutoPack │ structClone │ Ratio │ Veredicto │'); |
| 134 | + console.log('├─────────────────────────┼──────────┼───────────┼───────────────┼─────────┼──────────────────┤'); |
| 135 | + |
| 136 | + for (const r of results.slice(0, 5)) { |
| 137 | + const scenario = r.scenario.padEnd(23); |
| 138 | + const size = r.dataSize.padStart(8); |
| 139 | + const pack = `${r.packUnpackTime.toFixed(3)}ms`.padStart(9); |
| 140 | + const clone = `${r.structuredCloneTime.toFixed(3)}ms`.padStart(13); |
| 141 | + const ratio = `${r.ratio.toFixed(2)}x`.padStart(7); |
| 142 | + const verdict = r.verdict.padEnd(16); |
| 143 | + console.log(`│ ${scenario} │ ${size} │ ${pack} │ ${clone} │ ${ratio} │ ${verdict} │`); |
| 144 | + } |
| 145 | + console.log('└─────────────────────────┴──────────┴───────────┴───────────────┴─────────┴──────────────────┘\n'); |
| 146 | + |
| 147 | + // ============ ARRAYS DE OBJETOS ============ |
| 148 | + console.log('📦 ARRAYS DE OBJETOS (N objetos, 10 campos cada)\n'); |
| 149 | + |
| 150 | + results.push(benchmarkSingle('10 objetos', generateArray(10, 10))); |
| 151 | + results.push(benchmarkSingle('50 objetos', generateArray(50, 10))); |
| 152 | + results.push(benchmarkSingle('100 objetos', generateArray(100, 10))); |
| 153 | + results.push(benchmarkSingle('500 objetos', generateArray(500, 10))); |
| 154 | + results.push(benchmarkSingle('1000 objetos', generateArray(1000, 10))); |
| 155 | + results.push(benchmarkSingle('5000 objetos', generateArray(5000, 10))); |
| 156 | + results.push(benchmarkSingle('10000 objetos', generateArray(10000, 10))); |
| 157 | + |
| 158 | + console.log('┌─────────────────────────┬──────────┬───────────┬───────────────┬─────────┬──────────────────┐'); |
| 159 | + console.log('│ Cenário │ Tamanho │ AutoPack │ structClone │ Ratio │ Veredicto │'); |
| 160 | + console.log('├─────────────────────────┼──────────┼───────────┼───────────────┼─────────┼──────────────────┤'); |
| 161 | + |
| 162 | + for (const r of results.slice(5)) { |
| 163 | + const scenario = r.scenario.padEnd(23); |
| 164 | + const size = r.dataSize.padStart(8); |
| 165 | + const pack = `${r.packUnpackTime.toFixed(3)}ms`.padStart(9); |
| 166 | + const clone = `${r.structuredCloneTime.toFixed(3)}ms`.padStart(13); |
| 167 | + const ratio = `${r.ratio.toFixed(2)}x`.padStart(7); |
| 168 | + const verdict = r.verdict.padEnd(16); |
| 169 | + console.log(`│ ${scenario} │ ${size} │ ${pack} │ ${clone} │ ${ratio} │ ${verdict} │`); |
| 170 | + } |
| 171 | + console.log('└─────────────────────────┴──────────┴───────────┴───────────────┴─────────┴──────────────────┘\n'); |
| 172 | + |
| 173 | + // ============ CONCLUSÃO ============ |
| 174 | + console.log('╔══════════════════════════════════════════════════════════════════════════════╗'); |
| 175 | + console.log('║ CONCLUSÃO ║'); |
| 176 | + console.log('╠══════════════════════════════════════════════════════════════════════════════╣'); |
| 177 | + console.log('║ ║'); |
| 178 | + console.log('║ Para bee() NORMAL (chamadas únicas): ║'); |
| 179 | + console.log('║ ║'); |
| 180 | + console.log('║ ❌ NÃO usar AutoPack para: ║'); |
| 181 | + console.log('║ - Objetos pequenos (< 100 campos) ║'); |
| 182 | + console.log('║ - Arrays pequenos (< 100 objetos) ║'); |
| 183 | + console.log('║ - Qualquer dado < 10KB ║'); |
| 184 | + console.log('║ ║'); |
| 185 | + console.log('║ ✅ USAR AutoPack para: ║'); |
| 186 | + console.log('║ - Arrays com 500+ objetos ║'); |
| 187 | + console.log('║ - Objetos com 500+ campos ║'); |
| 188 | + console.log('║ - Qualquer dado > 50KB ║'); |
| 189 | + console.log('║ ║'); |
| 190 | + console.log('║ 📌 RECOMENDAÇÃO: ║'); |
| 191 | + console.log('║ - bee() normal: NÃO usar AutoPack (overhead não compensa) ║'); |
| 192 | + console.log('║ - turbo(): USAR AutoPack (arrays grandes, ganho significativo) ║'); |
| 193 | + console.log('║ ║'); |
| 194 | + console.log('╚══════════════════════════════════════════════════════════════════════════════╝'); |
| 195 | +} |
| 196 | + |
| 197 | +main().catch(console.error); |
| 198 | + |
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