66 lines
1.7 KiB
Go
66 lines
1.7 KiB
Go
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// Copyright (c) 2026 Petr Balvín <opensource@petrbalvin.org> (https://petrbalvin.org)
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// SPDX-License-Identifier: MIT
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package io
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// The A/B benchmark for the CSV read path: the legacy encoding/csv
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// reader and the hand-rolled tokenizer side by side, in one process.
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// The two sub-benchmarks alternate within every -count round, so both
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// see the same machine, and the decision reads the medians with 1 to 2
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// percent treated as noise.
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import (
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"bytes"
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"io"
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"testing"
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"sourcedock.dev/petrbalvin/tensor/internal/core"
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)
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// The A/B table: a hundred thousand rows of sixteen float64 values, in
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// the text shape SaveCSV emits, sized so the per-value work dominates
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// everything else.
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const (
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benchCSVABRows = 100000
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benchCSVABCols = 16
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)
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// benchCSVABData renders the A/B table as CSV bytes, once, before the
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// measured loops.
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func benchCSVABData(b *testing.B) []byte {
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b.Helper()
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var buf bytes.Buffer
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if err := SaveCSVWriter(&buf, benchFloats(benchCSVABRows, benchCSVABCols)); err != nil {
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b.Fatal(err)
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}
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return buf.Bytes()
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}
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// BenchmarkLoadCSVReader races the two readers over the same table.
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func BenchmarkLoadCSVReader(b *testing.B) {
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data := benchCSVABData(b)
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impls := []struct {
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name string
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load func(io.Reader, bool) (*core.Array, error)
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}{
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{"old", loadCSVReaderLegacy},
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{"new", LoadCSVReader},
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}
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for _, impl := range impls {
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b.Run(impl.name, func(b *testing.B) {
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r := bytes.NewReader(data)
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b.ReportAllocs()
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for b.Loop() {
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r.Reset(data)
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a, err := impl.load(r, false)
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if err != nil {
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b.Fatal(err)
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}
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if a.Shape()[0] != benchCSVABRows || a.Shape()[1] != benchCSVABCols {
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b.Fatalf("array came back with shape %v", a.Shape())
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}
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}
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})
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}
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}
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