2026-06-07 22:28 UTC · model: claude-haiku-4-5-20251001
| Table | Rows | Mode | LLM calls | In tokens | Out tokens | Time | Cache |
|---|---|---|---|---|---|---|---|
| customers | 200 | direct | 0 | 0 | 0 | 84.8s | |
| products | 100 | direct | 0 | 0 | 0 | 68.1s | |
| orders | 1,000 | codegen | 5 | 1,923 | 5,624 | 37.6s | MISS |
| reviews | 600 | codegen | 4 | 1,910 | 5,895 | 46.9s | MISS |
| order_items | 2,000 | codegen | 4 | 1,160 | 212 | 1.5s | MISS |
| TOTAL | 3,900 | 13 | 4,993 | 11,731 |
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| Column | Strategy | Calls | In tok | Out tok | Cache | Function |
|---|
5c8b95de36fa0cef
| Column | Strategy | Calls | In tok | Out tok | Cache | Function |
|---|
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| Column | Strategy | Calls | In tok | Out tok | Cache | Function |
|---|---|---|---|---|---|---|
| order_id | Code-gen | 1 | 302 | 88 | MISS | View generated functiondef generate_order_id(row, col_name):
return row.name + 1 |
| order_date | Code-gen | 1 | 302 | 88 | MISS | View generated functiondef generate_order_date(row, col_name):
import random
from datetime import datetime, timedelta
end_date = datetime.now().date()
start_date = end_date - timedelta(days=730)
random_days = random.randint(0, (end_date - start_date).days)
return (start_date + timedelta(days=random_days)).isoformat() |
| status | Code-gen | 1 | 302 | 88 | MISS | View generated functiondef generate_status(row, col_name):
import random
statuses = ['pending', 'processing', 'shipped', 'delivered', 'cancelled']
weights = [0.10, 0.20, 0.25, 0.40, 0.05]
return random.choices(statuses, weights=weights, k=1)[0] |
| total_amount | Code-gen | 1 | 302 | 88 | MISS | View generated functiondef generate_total_amount(row, col_name):
import random
return round(random.uniform(10.0, 10000.0), 2) |
| customer_id | FK sampler | 0 | 0 | 0 | ||
| shipping_method | Semantic LLM | 1 | 715 | 5,272 |
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| Column | Strategy | Calls | In tok | Out tok | Cache | Function |
|---|---|---|---|---|---|---|
| review_id | Code-gen | 1 | 399 | 113 | MISS | View generated functiondef generate_review_id(row, col_name):
return row.name + 1 |
| rating | Code-gen | 1 | 399 | 113 | MISS | View generated functiondef generate_rating(row, col_name):
import random
rand = random.random()
if rand < 0.30:
return 5
elif rand < 0.65:
return 4
elif rand < 0.85:
return 3
elif rand < 0.95:
return 2
else:
return 1 |
| review_date | Code-gen | 1 | 399 | 113 | MISS | View generated functiondef generate_review_date(row, col_name):
from datetime import datetime, timedelta
import random
start_date = datetime(2020, 1, 1)
end_date = datetime(2024, 12, 31)
days_between = (end_date - start_date).days
random_days = random.randint(0, days_between)
review_date = start_date + timedelta(days=random_days)
return review_date.strftime('%Y-%m-%d') |
| customer_id | FK sampler | 0 | 0 | 0 | ||
| product_id | FK sampler | 0 | 0 | 0 | ||
| review_text | Semantic LLM | 1 | 713 | 5,556 |
09b5cb78f1b98db8
| Column | Strategy | Calls | In tok | Out tok | Cache | Function |
|---|---|---|---|---|---|---|
| item_id | Code-gen | 1 | 290 | 53 | MISS | View generated functiondef generate_item_id(row, col_name):
return row.name + 1 |
| quantity | Code-gen | 1 | 290 | 53 | MISS | View generated functiondef generate_quantity(row, col_name):
import random
return random.randint(1, 5) |
| unit_price | Code-gen | 1 | 290 | 53 | MISS | View generated functiondef generate_unit_price(row, col_name):
import random
return round(random.uniform(0.01, 10000.00), 2) |
| discount | Code-gen | 1 | 290 | 53 | MISS | View generated functiondef generate_discount(row, col_name):
import random
return round(random.uniform(0, 20), 2) |
| product_id | FK sampler | 0 | 0 | 0 | ||
| order_id | FK sampler | 0 | 0 | 0 |