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konardkonard
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Fix and tracing
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‎rust/out.py‎

Lines changed: 97 additions & 123 deletions
Original file line numberDiff line numberDiff line change
@@ -1,9 +1,17 @@
11
import re
2+
import logging
23
import matplotlib.pyplot as plt
34
import numpy as np
45

6+
# Enable detailed tracing. Set to False to disable verbose output.
7+
DEBUG = True
8+
logging.basicConfig(level=logging.INFO if DEBUG else logging.WARNING,
9+
format="%(message)s")
10+
511
# Read the complete file
612
data = open("out.txt").read()
13+
if DEBUG:
14+
logging.info("Loaded out.txt, length: %d characters", len(data))
715

816
# Use two regex patterns to extract benchmarks.
917
# The first captures PostgreSQL tests and the second captures Doublets tests.
@@ -23,21 +31,29 @@
2331
# Process each regex pattern
2432
for pattern in patterns:
2533
matches = re.findall(pattern, data)
34+
if DEBUG:
35+
logging.info("Pattern %s matched %d entries", pattern, len(matches))
2636
for match in matches:
27-
op = match[0] # the operation name (e.g., Create, Update, etc.)
37+
# ─── FIX: normalise name ────────────────────────────────────────────
38+
op = match[0].replace("_", " ") # Create, Each All, …
39+
# ────────────────────────────────────────────────────────────────────
2840
if match[1] == 'PSQL':
29-
# For PostgreSQL: (operation, 'PSQL', transaction, time)
41+
# (operation, 'PSQL', transaction, time)
3042
transaction = match[2]
3143
time_val = int(match[3])
44+
if DEBUG:
45+
logging.info("PSQL %s - %s: %d ns", op, transaction, time_val)
3246
if transaction == "Transaction":
3347
PSQL_Transaction[op] = time_val
3448
else:
3549
PSQL_NonTransaction[op] = time_val
3650
else:
37-
# For Doublets: (operation, 'Doublets', trees, storage, time)
51+
# (operation, 'Doublets', trees, storage, time)
3852
trees = match[2]
3953
storage = match[3]
4054
time_val = int(match[4])
55+
if DEBUG:
56+
logging.info("Doublets %s - %s %s: %d ns", op, trees, storage, time_val)
4157
if trees == 'United':
4258
if storage == 'Volatile':
4359
Doublets_United_Volatile[op] = time_val
@@ -49,150 +65,108 @@
4965
else:
5066
Doublets_Split_NonVolatile[op] = time_val
5167

52-
# Set the unified order.
53-
# First write operations then read operations exactly as in the sample table.
68+
# Operation order for table and plots
5469
ordered_ops = [
55-
"Create", "Update", "Delete", # Write operations
56-
"Each All", "Each Identity", "Each Concrete", "Each Outgoing", "Each Incoming" # Read operations
70+
"Create", "Update", "Delete",
71+
"Each All", "Each Identity", "Each Concrete", "Each Outgoing", "Each Incoming"
5772
]
5873

59-
# Prepare arrays for plotting by reassembling results in the desired order.
60-
def get_series(data_dict):
61-
# If an operation is missing in the dictionary, default to 0.
62-
return [data_dict.get(op, 0) for op in ordered_ops]
63-
64-
du_volatile_arr = get_series(Doublets_United_Volatile)
65-
du_nonvolatile_arr = get_series(Doublets_United_NonVolatile)
66-
ds_volatile_arr = get_series(Doublets_Split_Volatile)
67-
ds_nonvolatile_arr = get_series(Doublets_Split_NonVolatile)
68-
psql_non_arr = get_series(PSQL_NonTransaction)
69-
psql_trans_arr = get_series(PSQL_Transaction)
70-
71-
#########################################
72-
# Print the Markdown Table to Console
73-
#########################################
74+
if DEBUG:
75+
logging.info("\nFinal dictionaries (after parsing):")
76+
logging.info("PSQL_Transaction: %s", PSQL_Transaction)
77+
logging.info("PSQL_NonTransaction: %s", PSQL_NonTransaction)
78+
logging.info("Doublets_United_Volatile: %s", Doublets_United_Volatile)
79+
logging.info("Doublets_United_NonVolatile: %s", Doublets_United_NonVolatile)
80+
logging.info("Doublets_Split_Volatile: %s", Doublets_Split_Volatile)
81+
logging.info("Doublets_Split_NonVolatile: %s", Doublets_Split_NonVolatile)
82+
83+
# Assemble series in the desired order.
84+
def get_series(d): return [d.get(op, 0) for op in ordered_ops]
85+
86+
du_volatile_arr = get_series(Doublets_United_Volatile)
87+
du_nonvolatile_arr= get_series(Doublets_United_NonVolatile)
88+
ds_volatile_arr = get_series(Doublets_Split_Volatile)
89+
ds_nonvolatile_arr= get_series(Doublets_Split_NonVolatile)
90+
psql_non_arr = get_series(PSQL_NonTransaction)
91+
psql_trans_arr = get_series(PSQL_Transaction)
92+
93+
# ─────────────────────────────────────────────────────────────────────────────
94+
# Markdown Table
95+
# ─────────────────────────────────────────────────────────────────────────────
7496
def print_results_markdown():
75-
# Define the header in Markdown format.
7697
header = (
7798
"| Operation | Doublets United Volatile | Doublets United NonVolatile | "
7899
"Doublets Split Volatile | Doublets Split NonVolatile | PSQL NonTransaction | PSQL Transaction |\n"
79100
"|---------------|--------------------------|-----------------------------|-------------------------|----------------------------|---------------------|------------------|"
80101
)
81102
lines = [header]
82-
83-
# For each operation row, compute the minimum PostgreSQL time
84-
# and annotate each Doublets result with the relative speed-up.
103+
85104
for i, op in enumerate(ordered_ops):
86-
# Get PostgreSQL values. If one is missing, use the other.
87-
psql_val1 = psql_non_arr[i] if psql_non_arr[i] != 0 else float('inf')
88-
psql_val2 = psql_trans_arr[i] if psql_trans_arr[i] != 0 else float('inf')
89-
min_psql = min(psql_val1, psql_val2)
90-
91-
def annotate(doublets_val):
92-
if doublets_val == 0:
93-
return "N/A"
94-
# Compute the factor (using the fastest PostgreSQL result).
95-
factor = min_psql / doublets_val
96-
return f"{doublets_val} ({factor:.1f}+ times faster)"
97-
98-
du_vol_str = annotate(du_volatile_arr[i])
99-
du_nonvol_str = annotate(du_nonvolatile_arr[i])
100-
ds_vol_str = annotate(ds_volatile_arr[i])
101-
ds_nonvol_str = annotate(ds_nonvolatile_arr[i])
102-
103-
# For PostgreSQL values, just show the raw number or N/A if missing.
104-
psql_non_str = str(psql_non_arr[i]) if psql_non_arr[i] != 0 else "N/A"
105-
psql_trans_str = str(psql_trans_arr[i]) if psql_trans_arr[i] != 0 else "N/A"
106-
105+
psql_val1 = psql_non_arr[i] if psql_non_arr[i] else float('inf')
106+
psql_val2 = psql_trans_arr[i] if psql_trans_arr[i] else float('inf')
107+
min_psql = min(psql_val1, psql_val2)
108+
109+
def annotate(v):
110+
if v == 0: return "N/A"
111+
if min_psql == float('inf'): return f"{v}"
112+
return f"{v} ({min_psql / v:.1f}+ times faster)"
113+
107114
row = (
108-
f"| {op:<13} | {du_vol_str:<24} | {du_nonvol_str:<27} | "
109-
f"{ds_vol_str:<23} | {ds_nonvol_str:<26} | {psql_non_str:<19} | {psql_trans_str:<16} |"
115+
f"| {op:<13} | {annotate(du_volatile_arr[i]):<24} | "
116+
f"{annotate(du_nonvolatile_arr[i]):<27} | "
117+
f"{annotate(ds_volatile_arr[i]):<23} | "
118+
f"{annotate(ds_nonvolatile_arr[i]):<26} | "
119+
f"{psql_non_arr[i] or 'N/A':<19} | {psql_trans_arr[i] or 'N/A':<16} |"
110120
)
111121
lines.append(row)
112-
122+
113123
table_md = "\n".join(lines)
114124
print(table_md)
125+
if DEBUG: logging.info("\nGenerated Markdown Table:\n%s", table_md)
115126

116-
#########################################
117-
# Plotting Functions with Unified Order
118-
#########################################
127+
# ─────────────────────────────────────────────────────────────────────────────
128+
# Plots
129+
# ─────────────────────────────────────────────────────────────────────────────
119130
def bench1():
120-
"""
121-
This function plots horizontal bar charts with scaled times.
122-
Scaled by dividing each raw nanosecond (ns) value by 10,000,000.
123-
"""
124-
# Scale the Doublets and PostgreSQL arrays.
125-
scale_factor = 10000000
126-
du_volatile_scaled = [max(1, x // scale_factor) for x in du_volatile_arr]
127-
du_nonvolatile_scaled = [max(1, x // scale_factor) for x in du_nonvolatile_arr]
128-
ds_volatile_scaled = [max(1, x // scale_factor) for x in ds_volatile_arr]
129-
ds_nonvolatile_scaled = [max(1, x // scale_factor) for x in ds_nonvolatile_arr]
130-
psql_non_scaled = [max(1, x // scale_factor) for x in psql_non_arr]
131-
psql_trans_scaled = [max(1, x // scale_factor) for x in psql_trans_arr]
132-
133-
y = np.arange(len(ordered_ops))
134-
width = 0.1
135-
131+
"""Horizontal bars – scaled (divide by 10 000 000)."""
132+
scale = lambda arr: [max(1, x // 10_000_000) for x in arr]
133+
y, w = np.arange(len(ordered_ops)), 0.1
136134
fig, ax = plt.subplots(figsize=(12, 8))
137135

138-
ax.barh(y - 2 * width, du_volatile_scaled, width,
139-
label='Doublets United Volatile', color='salmon')
140-
ax.barh(y - width, du_nonvolatile_scaled, width,
141-
label='Doublets United NonVolatile', color='red')
142-
ax.barh(y, ds_volatile_scaled, width,
143-
label='Doublets Split Volatile', color='lightgreen')
144-
ax.barh(y + width, ds_nonvolatile_scaled, width,
145-
label='Doublets Split NonVolatile', color='green')
146-
ax.barh(y + 2 * width, psql_non_scaled, width,
147-
label='PSQL NonTransaction', color='lightblue')
148-
ax.barh(y + 3 * width, psql_trans_scaled, width,
149-
label='PSQL Transaction', color='blue')
150-
151-
ax.set_xlabel('Time (ns) - Scaled to Pixels')
152-
ax.set_title('Benchmark Comparison for Doublets and PostgreSQL (Rust)')
153-
ax.set_yticks(y)
154-
ax.set_yticklabels(ordered_ops)
155-
ax.legend()
156-
157-
fig.tight_layout()
158-
plt.savefig("bench_rust.png")
159-
plt.close(fig)
136+
ax.barh(y - 2*w, scale(du_volatile_arr), w, label='Doublets United Volatile', color='salmon')
137+
ax.barh(y - w, scale(du_nonvolatile_arr),w, label='Doublets United NonVolatile',color='red')
138+
ax.barh(y , scale(ds_volatile_arr), w, label='Doublets Split Volatile', color='lightgreen')
139+
ax.barh(y + w, scale(ds_nonvolatile_arr), w, label='Doublets Split NonVolatile', color='green')
140+
ax.barh(y + 2*w, scale(psql_non_arr), w, label='PSQL NonTransaction', color='lightblue')
141+
ax.barh(y + 3*w, scale(psql_trans_arr), w, label='PSQL Transaction', color='blue')
142+
143+
ax.set_xlabel('Time (ns) – scaled')
144+
ax.set_title ('Benchmark Comparison (Rust)')
145+
ax.set_yticks(y); ax.set_yticklabels(ordered_ops); ax.legend()
146+
fig.tight_layout(); plt.savefig("bench_rust.png"); plt.close(fig)
147+
if DEBUG: logging.info("bench_rust.png saved.")
160148

161149
def bench2():
162-
"""
163-
This function plots horizontal bar charts using raw nanosecond values on a logarithmic scale.
164-
"""
165-
y = np.arange(len(ordered_ops))
166-
width = 0.1
150+
"""Horizontal bars – raw values on a log scale."""
151+
y, w = np.arange(len(ordered_ops)), 0.1
167152
fig, ax = plt.subplots(figsize=(12, 8))
168153

169-
ax.barh(y - 2 * width, du_volatile_arr, width,
170-
label='Doublets United Volatile', color='salmon')
171-
ax.barh(y - width, du_nonvolatile_arr, width,
172-
label='Doublets United NonVolatile', color='red')
173-
ax.barh(y, ds_volatile_arr, width,
174-
label='Doublets Split Volatile', color='lightgreen')
175-
ax.barh(y + width, ds_nonvolatile_arr, width,
176-
label='Doublets Split NonVolatile', color='green')
177-
ax.barh(y + 2 * width, psql_non_arr, width,
178-
label='PSQL NonTransaction', color='lightblue')
179-
ax.barh(y + 3 * width, psql_trans_arr, width,
180-
label='PSQL Transaction', color='blue')
181-
182-
ax.set_xlabel('Time (ns) - Logarithmic Scale')
183-
ax.set_title('Benchmark Comparison for Doublets and PostgreSQL (Rust)')
184-
ax.set_yticks(y)
185-
ax.set_yticklabels(ordered_ops)
186-
ax.legend()
187-
188-
ax.set_xscale('log')
189-
fig.tight_layout()
190-
plt.savefig("bench_rust_log_scale.png")
191-
plt.close(fig)
192-
193-
#########################################
194-
# Main section: print table and generate images
195-
#########################################
154+
ax.barh(y - 2*w, du_volatile_arr, w, label='Doublets United Volatile', color='salmon')
155+
ax.barh(y - w, du_nonvolatile_arr,w, label='Doublets United NonVolatile',color='red')
156+
ax.barh(y , ds_volatile_arr, w, label='Doublets Split Volatile', color='lightgreen')
157+
ax.barh(y + w, ds_nonvolatile_arr, w, label='Doublets Split NonVolatile', color='green')
158+
ax.barh(y + 2*w, psql_non_arr, w, label='PSQL NonTransaction', color='lightblue')
159+
ax.barh(y + 3*w, psql_trans_arr, w, label='PSQL Transaction', color='blue')
160+
161+
ax.set_xlabel('Time (ns) – log scale')
162+
ax.set_title ('Benchmark Comparison (Rust)')
163+
ax.set_yticks(y); ax.set_yticklabels(ordered_ops); ax.set_xscale('log'); ax.legend()
164+
fig.tight_layout(); plt.savefig("bench_rust_log_scale.png"); plt.close(fig)
165+
if DEBUG: logging.info("bench_rust_log_scale.png saved.")
166+
167+
# ─────────────────────────────────────────────────────────────────────────────
168+
# Run
169+
# ─────────────────────────────────────────────────────────────────────────────
196170
print_results_markdown()
197171
bench1()
198172
bench2()

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