be67cb77d3
**Payload Performance Test:** - Add job cleanup after each iteration using DeleteJob() - Ensure isolated memory measurements between test runs **All Benchmark Tests:** - General improvements and maintenance updates
62 lines
1.5 KiB
Go
62 lines
1.5 KiB
Go
package benchmarks
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import (
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"os"
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"path/filepath"
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"testing"
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"github.com/jfraeys/fetch_ml/internal/worker"
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)
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// createSmallDataset creates a temporary small dataset for benchmarking
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func createSmallDataset(b *testing.B) string {
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tmpDir := b.TempDir()
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// Create 10 small files (100KB each) to emphasize context overhead
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data := make([]byte, 100*1024)
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for i := range data {
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data[i] = byte(i % 256)
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}
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for i := range 10 {
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path := filepath.Join(tmpDir, "data", string(rune('a'+i%26)), "chunk.bin")
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if err := os.MkdirAll(filepath.Dir(path), 0750); err != nil {
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b.Fatal(err)
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}
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if err := os.WriteFile(path, data, 0640); err != nil {
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b.Fatal(err)
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}
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}
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return tmpDir
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}
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// BenchmarkContextReuse measures overhead of repeated hash operations
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// This verifies the 5-20ms savings from context reuse in native_bridge_libs.go
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func BenchmarkContextReuse(b *testing.B) {
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testDir := createSmallDataset(b)
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b.ResetTimer()
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for i := 0; i < b.N; i++ {
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_, err := worker.DirOverallSHA256Hex(testDir)
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if err != nil {
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b.Fatal(err)
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}
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}
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}
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// BenchmarkSequentialHashes simulates TUI scrolling through datasets
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// With context reuse: ~8ms per hash
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// Without context reuse: ~17ms per hash (9ms overhead)
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func BenchmarkSequentialHashes(b *testing.B) {
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testDir := createSmallDataset(b)
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b.ReportAllocs()
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for b.Loop() {
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// Simulate viewing 10 datasets (like TUI scrolling)
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for range 10 {
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_, err := worker.DirOverallSHA256Hex(testDir)
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if err != nil {
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b.Fatal(err)
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}
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}
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}
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}
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