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Add new chart to show speedup in seconds #13

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Add new chart to show speedup in seconds #13

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56 changes: 52 additions & 4 deletions scripts/generate-comparison.py
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Original file line number Diff line number Diff line change
Expand Up @@ -23,7 +23,7 @@
def geomean(data):
return np.prod(data) ** (1 / len(data))

def generate_query_speedup_chart(baseline, comparison, label1: str, label2: str, benchmark: str, title: str):
def generate_query_rel_speedup_chart(baseline, comparison, label1: str, label2: str, benchmark: str, title: str):
results = []
for query in range(1, query_count(benchmark)+1):
a = np.median(np.array(baseline[str(query)]))
Expand Down Expand Up @@ -59,7 +59,7 @@ def generate_query_speedup_chart(baseline, comparison, label1: str, label2: str,

# Add title and labels
ax.set_title(label2 + " speedup over " + label1 + " (" + title + ")")
ax.set_ylabel('Speedup (100% speedup = 2x faster)')
ax.set_ylabel('Speedup Percentage (100% speedup = 2x faster)')
ax.set_xlabel('Query')

# Customize the y-axis to handle both positive and negative values better
Expand All @@ -76,8 +76,55 @@ def generate_query_speedup_chart(baseline, comparison, label1: str, label2: str,
ax.yaxis.grid(True)

# Save the plot as an image file
plt.savefig(f'{benchmark}_queries_speedup.png', format='png')
plt.savefig(f'{benchmark}_queries_speedup_rel.png', format='png')

def generate_query_abs_speedup_chart(baseline, comparison, label1: str, label2: str, benchmark: str, title: str):
results = []
for query in range(1, query_count(benchmark)+1):
a = np.median(np.array(baseline[str(query)]))
b = np.median(np.array(comparison[str(query)]))
speedup = a-b
results.append(("q" + str(query), round(speedup, 1)))

results = sorted(results, key=lambda x: -x[1])

queries, speedups = zip(*results)

# Create figure and axis
if benchmark == "tpch":
fig, ax = plt.subplots(figsize=(10, 6))
else:
fig, ax = plt.subplots(figsize=(35, 10))

# Create bar chart
bars = ax.bar(queries, speedups, color='skyblue')

# Add text annotations
for bar, speedup in zip(bars, speedups):
yval = bar.get_height()
if yval >= 0:
ax.text(bar.get_x() + bar.get_width() / 2.0, min(800, yval+5), f'{yval:.1f}', va='bottom', ha='center', fontsize=8,
color='blue', rotation=90)
else:
ax.text(bar.get_x() + bar.get_width() / 2.0, yval, f'{yval:.1f}', va='top', ha='center', fontsize=8,
color='blue', rotation=90)

# Add title and labels
ax.set_title(label2 + " speedup over " + label1 + " (" + title + ")")
ax.set_ylabel('Speedup (in seconds)')
ax.set_xlabel('Query')

# Customize the y-axis to handle both positive and negative values better
ax.axhline(0, color='black', linewidth=0.8)
min_value = min(speedups) * 2
max_value = max(speedups) * 2
ax.set_ylim(min_value, max_value)

# Show grid for better readability
ax.yaxis.grid(True)

# Save the plot as an image file
plt.savefig(f'{benchmark}_queries_speedup_abs.png', format='png')

def generate_query_comparison_chart(results, labels, benchmark: str, title: str):
queries = []
Expand Down Expand Up @@ -160,7 +207,8 @@ def main(files, labels, benchmark: str, title: str):
generate_summary(results, labels, benchmark, title)
generate_query_comparison_chart(results, labels, benchmark, title)
if len(files) == 2:
generate_query_speedup_chart(results[0], results[1], labels[0], labels[1], benchmark, title)
generate_query_abs_speedup_chart(results[0], results[1], labels[0], labels[1], benchmark, title)
generate_query_rel_speedup_chart(results[0], results[1], labels[0], labels[1], benchmark, title)

if __name__ == '__main__':
argparse = argparse.ArgumentParser(description='Generate comparison')
Expand Down