401a63f544
Generates Forth-style command scripts that build a multi-dimensional model and exercise the grid aggregation hot path via repeated export-csv calls. Used for profiling with samply. Usage: python3 bench/gen_workload.py --scale 5 > /tmp/workload.txt cargo build --profile profiling samply record ./target/profiling/improvise script /tmp/workload.txt Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
84 lines
3.0 KiB
Python
84 lines
3.0 KiB
Python
#!/usr/bin/env python3
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"""Generate a profiling workload script for improvise.
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Usage:
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python3 bench/gen_workload.py [--scale N] > bench/large_workload.txt
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cargo build --release
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time ./target/release/improvise script bench/large_workload.txt
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For flamegraph profiling:
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samply record ./target/release/improvise script bench/large_workload.txt
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"""
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import argparse
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import random
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parser = argparse.ArgumentParser()
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parser.add_argument("--scale", type=int, default=1,
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help="Scale factor (1=small, 5=medium, 10=large)")
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parser.add_argument("--density", type=float, default=0.3,
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help="Cell density (0.0-1.0)")
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parser.add_argument("--exports", type=int, default=0,
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help="Number of export passes (0 = one per month)")
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args = parser.parse_args()
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random.seed(42)
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S = args.scale
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n_regions = 5 * S
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n_products = 8 * S
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n_months = 12
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n_channels = 4 + S
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measures = ["Revenue", "Cost", "Units"]
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regions = [f"R{i:03d}" for i in range(n_regions)]
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products = [f"P{i:03d}" for i in range(n_products)]
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months = [f"M{i:02d}" for i in range(1, n_months + 1)]
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channels = [f"Ch{i:02d}" for i in range(n_channels)]
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potential = n_regions * n_products * n_months * n_channels * len(measures)
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print(f"# Scale={S}, Density={args.density}")
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print(f"# {n_regions} regions × {n_products} products × {n_months} months × {n_channels} channels × {len(measures)} measures")
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print(f"# Potential cells: {potential}, Expected: ~{int(potential * args.density)}")
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print()
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for cat in ["Region", "Product", "Month", "Channel", "Measure"]:
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print(f"add-category {cat}")
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for items, cat in [(regions, "Region"), (products, "Product"),
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(months, "Month"), (channels, "Channel"),
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(measures, "Measure")]:
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for item in items:
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print(f"add-item {cat} {item}")
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print("set-axis Region row")
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print("set-axis Product column")
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print("set-axis Month page")
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print("set-axis Channel none")
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print("set-axis Measure none")
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n = 0
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for r in regions:
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for p in products:
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for m in months:
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for c in channels:
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if random.random() < args.density:
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rev = random.randint(100, 10000)
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cost = random.randint(50, rev)
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units = random.randint(1, 500)
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print(f"set-cell {rev} Region/{r} Product/{p} Month/{m} Channel/{c} Measure/Revenue")
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print(f"set-cell {cost} Region/{r} Product/{p} Month/{m} Channel/{c} Measure/Cost")
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print(f"set-cell {units} Region/{r} Product/{p} Month/{m} Channel/{c} Measure/Units")
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n += 3
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print(f"# Total cells: {n}")
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print('add-formula Measure "Profit = Revenue - Cost"')
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print('add-formula Measure "Margin = Profit / Revenue"')
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print('add-formula Measure "AvgPrice = Revenue / Units"')
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n_exports = args.exports if args.exports > 0 else n_months
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for i, m in enumerate(months[:n_exports]):
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print(f"set-page Month {m} . export-csv /tmp/improvise_bench_{i:02d}.csv")
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print("# Done")
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