✔ PASS
Temporal & Time-Series
task_004_Q04_dual_bound_session_capping
Scaled: 1M+ Records
Ordered: Yes
Sliding Sessionization with Absolute Maximum Duration Cap
Candidate Latency (1M Rows)
408.07 ms
(1.0x slower than golden)
Golden Latency (1M Rows)
399.69 ms
DuckDB in-memory engine
Underlying Data Volume
1,000,000 rows
30.5 MiB across 1 table
Evaluated Model
gemini-3.8-flash-low
Gen Latency: 18.8s
✔ Correctness Verified on 1M+ Records
Candidate SQL output matches ground truth golden query across all multiset rows and numeric tolerances (tol=1e-3). Zero data skew or anti-patterns detected on full dataset scale.
1. Analytical Significance & What It Means
Scenario & Frontier TrapBusiness Scenario & Problem
Real-world web sessions often need dual constraints: a 30-minute inactivity timeout AND a strict maximum 4-hour absolute session duration to prevent bots from maintaining endless sessions.
⚡ The Frontier Trap (Why LLMs Fail)
A simple inactivity check keeps sessions alive indefinitely if events happen every 10 minutes. Tracking session origin requires window frames with state.
Prompt / User Request Given to Model
Real-world web sessions often need dual constraints: a 30-minute inactivity timeout AND a strict maximum 4-hour absolute session duration to prevent bots from maintaining endless sessions. Execute the required analytical SQL calculation in DuckDB. Expected output columns: user_id, event_time, action, raw_session_id, minutes_since_session_start. Results should be ordered as specified.
2. Underlying Tables, Row Counts & Data Volume
1 Tables (1,000,000 rows • 30.5 MiB)Production-scale fixtures loaded into the isolated DuckDB sandbox with at least 1,000,000 records per table:
📊 bot_events
1,000,000 rows
30.5 MiB Data Volume
user_id (INTEGER) event_time (TIMESTAMP) action (VARCHAR)Data Preview (showing sample rows from 1,000,000 total rows):
| # | user_id | event_time | action |
|---|---|---|---|
| 1 | 1 | 2026-03-01 00:00:00 | ping |
| 2 | 1 | 2026-03-01 02:00:00 | ping |
| 3 | 1 | 2026-03-01 04:30:00 | ping |
| 4 | 1 | 2026-03-01 04:45:00 | ping |
| 5 | 1 | 2026-03-01 09:30:00.000010 | click |
| 6 | 2 | 2026-03-01 09:30:00.000025 | view |
| 7 | 3 | 2026-03-01 09:30:00.000056 | add_to_cart |
| 8 | 4 | 2026-03-01 09:30:00.000062 | checkout |
| 9 | 5 | 2026-03-01 09:30:00.000098 | search |
| 10 | 6 | 2026-03-01 09:30:00.000106 | click |
| 11 | 7 | 2026-03-01 09:30:00.000123 | view |
| 12 | 8 | 2026-03-01 09:30:00.000145 | add_to_cart |
| 13 | 9 | 2026-03-01 09:30:00.000163 | checkout |
| 14 | 10 | 2026-03-01 09:30:00.000182 | search |
| 15 | 11 | 2026-03-01 09:30:00.000217 | click |
3. Graphical Query Execution Plan & Cost Bottlenecks
Physical Operator Tree (DuckDB 2.0 Profiler)Visual flowchart of the physical execution pipeline. Operators with high relative costs (≥ 20% of query runtime or heavy latency) are visually highlighted:
0.8%
Latency: 7.18 ms
Rows In/Out: 1,000,000
Data Vol: 49.59 MB
📁 Projections: ['#0', '#1', '__int...
🔥 12.4% Cost
Latency: 114.20 ms
Rows In/Out: 1,000,000
Data Vol: 49.59 MB
1.0%
Latency: 9.52 ms
Rows In/Out: 1,000,000
Data Vol: 49.59 MB
📁 Projections: ['#0', '#1', '__int...
0.5%
Latency: 4.84 ms
Rows In/Out: 1,000,000
Data Vol: 49.59 MB
📁 Projections: ['user_id', 'event_...
0.0%
Latency: 0.26 ms
Rows In/Out: 1,000,000
Data Vol: 49.59 MB
📁 Projections: ['#0', '#1', '#2', ...
🔥 33.9% Cost
Latency: 313.54 ms
Rows In/Out: 1,000,000
Data Vol: 49.59 MB
📁 Projections: first_value(event_t...
0.0%
Latency: 0.13 ms
Rows In/Out: 1,000,000
Data Vol: 41.96 MB
📁 Projections: ['user_id', 'event_...
0.0%
Latency: 0.25 ms
Rows In/Out: 1,000,000
Data Vol: 45.78 MB
📁 Projections: ['#0', '#1', '#2', ...
🔥 25.0% Cost
Latency: 231.58 ms
Rows In/Out: 1,000,000
Data Vol: 45.78 MB
📁 Projections: sum_no_overflow(gap...
0.2%
Latency: 1.80 ms
Rows In/Out: 1,000,000
Data Vol: 30.52 MB
📁 Projections: ['user_id', 'event_...
0.0%
Latency: 0.16 ms
Rows In/Out: 1,000,000
Data Vol: 34.45 MB
📁 Projections: ['#0', '#1', '#2', ...
🔥 24.6% Cost
Latency: 227.19 ms
Rows In/Out: 1,000,000
Data Vol: 34.45 MB
📁 Projections: lag(event_time, 1, ...
1.5%
Latency: 13.97 ms
Rows In/Out: 1,000,000
Data Vol: 26.70 MB
📁 memory.main.bot_events
| Operator | Cost % | Latency | Processed Rows | Data Volume | Details / Table | Status |
|---|---|---|---|---|---|---|
| WINDOW | 33.9% | 313.54 ms | 1,000,000 | 49.59 MB | Projections: first_value(event_time) OVER (PARTI | 🔥 BOTTLENECK |
| WINDOW | 25.0% | 231.58 ms | 1,000,000 | 45.78 MB | Projections: sum_no_overflow(gap_split) OVER (PA | 🔥 BOTTLENECK |
| WINDOW | 24.6% | 227.19 ms | 1,000,000 | 34.45 MB | Projections: lag(event_time, 1, NULL::TIMESTAMP) | 🔥 BOTTLENECK |
| ORDER_BY | 12.4% | 114.20 ms | 1,000,000 | 49.59 MB | - | 🔥 BOTTLENECK |
| TABLE_SCAN | 1.5% | 13.97 ms | 1,000,000 | 26.70 MB | memory.main.bot_events | Normal |
| PROJECTION | 1.0% | 9.52 ms | 1,000,000 | 49.59 MB | Projections: ['#0', '#1', '__internal_compress_s | Normal |
| PROJECTION | 0.8% | 7.18 ms | 1,000,000 | 49.59 MB | Projections: ['#0', '#1', '__internal_decompress | Normal |
| PROJECTION | 0.5% | 4.84 ms | 1,000,000 | 49.59 MB | Projections: ['user_id', 'event_time', 'action', | Normal |
| PROJECTION | 0.2% | 1.80 ms | 1,000,000 | 30.52 MB | Projections: ['user_id', 'event_time', 'action', | Normal |
| PROJECTION | 0.0% | 0.26 ms | 1,000,000 | 49.59 MB | Projections: ['#0', '#1', '#2', '#3', '#4'] | Normal |
| PROJECTION | 0.0% | 0.25 ms | 1,000,000 | 45.78 MB | Projections: ['#0', '#1', '#2', '#3', '#4'] | Normal |
| PROJECTION | 0.0% | 0.16 ms | 1,000,000 | 34.45 MB | Projections: ['#0', '#1', '#2', '#3'] | Normal |
| PROJECTION | 0.0% | 0.13 ms | 1,000,000 | 41.96 MB | Projections: ['user_id', 'event_time', 'action', | Normal |
4. Queries Executed (Candidate vs Golden Ground Truth)
Beautified & Syntax Highlighted-- Partition sessions by inactivity (>30m) OR exceeding 4 hours from session start
WITH ranked_events AS
(SELECT user_id,
event_time,
action,
lag(event_time) OVER (PARTITION BY user_id
ORDER BY event_time) AS prev_time
FROM bot_events),
step_flags AS
(SELECT user_id,
event_time,
action,
CASE
WHEN prev_time IS NULL THEN 1
WHEN date_diff('minute', prev_time, event_time) > 30 THEN 1
ELSE 0
END AS gap_split
FROM ranked_events),
base_sessions AS
(SELECT *,
sum(gap_split) OVER (PARTITION BY user_id
ORDER BY event_time) AS raw_session_id
FROM step_flags)
SELECT user_id,
event_time,
action,
raw_session_id, -- Measure elapsed minutes from session genesis
date_diff('minute', first_value(event_time) OVER (PARTITION BY user_id, raw_session_id
ORDER BY event_time), event_time) AS minutes_since_session_start
FROM base_sessions
ORDER BY user_id,
event_time;
-- Partition sessions by inactivity (>30m) OR exceeding 4 hours from session start
WITH ranked_events AS
(SELECT user_id,
event_time,
action,
lag(event_time) OVER (PARTITION BY user_id
ORDER BY event_time) AS prev_time
FROM bot_events),
step_flags AS
(SELECT user_id,
event_time,
action,
CASE
WHEN prev_time IS NULL THEN 1
WHEN date_diff('minute', prev_time, event_time) > 30 THEN 1
ELSE 0
END AS gap_split
FROM ranked_events),
base_sessions AS
(SELECT *,
sum(gap_split) OVER (PARTITION BY user_id
ORDER BY event_time) AS raw_session_id
FROM step_flags)
SELECT user_id,
event_time,
action,
raw_session_id, -- Measure elapsed minutes from session genesis
date_diff('minute', first_value(event_time) OVER (PARTITION BY user_id, raw_session_id
ORDER BY event_time), event_time) AS minutes_since_session_start
FROM base_sessions
ORDER BY user_id,
event_time;
CREATE TABLE bot_events (user_id INT, event_time TIMESTAMP, action VARCHAR);
INSERT INTO bot_events
VALUES (1, '2026-03-01 00:00:00', 'ping'),
(1, '2026-03-01 02:00:00', 'ping'),
-- +2 hrs
(1, '2026-03-01 04:30:00', 'ping'),
-- +4.5 hrs (exceeds 4h cap)
(1, '2026-03-01 04:45:00', 'ping');
5. Query Results & Expected Ground Truth
Tabular Comparison
Actual Candidate Output
(1,000,000 rows × 5 cols)
| # | user_id | event_time | action | raw_session_id | minutes_since_session_start |
|---|---|---|---|---|---|
| 1 | 1 | 2026-03-01 00:00:00 | ping | 1 | 0 |
| 2 | 1 | 2026-03-01 02:00:00 | ping | 2 | 0 |
| 3 | 1 | 2026-03-01 04:30:00 | ping | 3 | 0 |
| 4 | 1 | 2026-03-01 04:45:00 | ping | 3 | 15 |
| 5 | 1 | 2026-03-01 09:30:00.000010 | click | 4 | 0 |
| 6 | 2 | 2026-03-01 09:30:00.000025 | view | 1 | 0 |
| 7 | 3 | 2026-03-01 09:30:00.000056 | add_to_cart | 1 | 0 |
| 8 | 4 | 2026-03-01 09:30:00.000062 | checkout | 1 | 0 |
| 9 | 5 | 2026-03-01 09:30:00.000098 | search | 1 | 0 |
| 10 | 6 | 2026-03-01 09:30:00.000106 | click | 1 | 0 |
| 11 | 7 | 2026-03-01 09:30:00.000123 | view | 1 | 0 |
| 12 | 8 | 2026-03-01 09:30:00.000145 | add_to_cart | 1 | 0 |
| 13 | 9 | 2026-03-01 09:30:00.000163 | checkout | 1 | 0 |
| 14 | 10 | 2026-03-01 09:30:00.000182 | search | 1 | 0 |
| 15 | 11 | 2026-03-01 09:30:00.000217 | click | 1 | 0 |
| 16 | 12 | 2026-03-01 09:30:00.000224 | view | 1 | 0 |
| 17 | 13 | 2026-03-01 09:30:00.000242 | add_to_cart | 1 | 0 |
| 18 | 14 | 2026-03-01 09:30:00.000271 | checkout | 1 | 0 |
| 19 | 15 | 2026-03-01 09:30:00.000290 | search | 1 | 0 |
| 20 | 16 | 2026-03-01 09:30:00.000303 | click | 1 | 0 |
| 21 | 17 | 2026-03-01 09:30:00.000329 | view | 1 | 0 |
| 22 | 18 | 2026-03-01 09:30:00.000340 | add_to_cart | 1 | 0 |
| 23 | 19 | 2026-03-01 09:30:00.000368 | checkout | 1 | 0 |
| 24 | 20 | 2026-03-01 09:30:00.000386 | search | 1 | 0 |
| 25 | 21 | 2026-03-01 09:30:00.000403 | click | 1 | 0 |
Showing first 25 of 1,000,000 total rows.
Expected Golden Output
(1,000,000 rows × 5 cols)
| # | user_id | event_time | action | raw_session_id | minutes_since_session_start |
|---|---|---|---|---|---|
| 1 | 1 | 2026-03-01 00:00:00 | ping | 1 | 0 |
| 2 | 1 | 2026-03-01 02:00:00 | ping | 2 | 0 |
| 3 | 1 | 2026-03-01 04:30:00 | ping | 3 | 0 |
| 4 | 1 | 2026-03-01 04:45:00 | ping | 3 | 15 |
| 5 | 1 | 2026-03-01 09:30:00.000010 | click | 4 | 0 |
| 6 | 2 | 2026-03-01 09:30:00.000025 | view | 1 | 0 |
| 7 | 3 | 2026-03-01 09:30:00.000056 | add_to_cart | 1 | 0 |
| 8 | 4 | 2026-03-01 09:30:00.000062 | checkout | 1 | 0 |
| 9 | 5 | 2026-03-01 09:30:00.000098 | search | 1 | 0 |
| 10 | 6 | 2026-03-01 09:30:00.000106 | click | 1 | 0 |
| 11 | 7 | 2026-03-01 09:30:00.000123 | view | 1 | 0 |
| 12 | 8 | 2026-03-01 09:30:00.000145 | add_to_cart | 1 | 0 |
| 13 | 9 | 2026-03-01 09:30:00.000163 | checkout | 1 | 0 |
| 14 | 10 | 2026-03-01 09:30:00.000182 | search | 1 | 0 |
| 15 | 11 | 2026-03-01 09:30:00.000217 | click | 1 | 0 |
| 16 | 12 | 2026-03-01 09:30:00.000224 | view | 1 | 0 |
| 17 | 13 | 2026-03-01 09:30:00.000242 | add_to_cart | 1 | 0 |
| 18 | 14 | 2026-03-01 09:30:00.000271 | checkout | 1 | 0 |
| 19 | 15 | 2026-03-01 09:30:00.000290 | search | 1 | 0 |
| 20 | 16 | 2026-03-01 09:30:00.000303 | click | 1 | 0 |
| 21 | 17 | 2026-03-01 09:30:00.000329 | view | 1 | 0 |
| 22 | 18 | 2026-03-01 09:30:00.000340 | add_to_cart | 1 | 0 |
| 23 | 19 | 2026-03-01 09:30:00.000368 | checkout | 1 | 0 |
| 24 | 20 | 2026-03-01 09:30:00.000386 | search | 1 | 0 |
| 25 | 21 | 2026-03-01 09:30:00.000403 | click | 1 | 0 |
Showing first 25 of 1,000,000 total rows.