✔ PASS Warehouse & Statistical task_099_Q99_window_exclude_ties_duplicate_handling Scaled: 1M+ Records Ordered: Yes

Window Frame Ties Exclusion: EXCLUDE TIES for Unbiased Cumulative Totals

Candidate Latency (1M Rows)

98.74 ms

(1.1x faster than golden)

Golden Latency (1M Rows)

109.08 ms

DuckDB in-memory engine

Underlying Data Volume

1,000,000 rows

7.6 MiB across 1 table

Evaluated Model

gemini-3.8-flash-low

Gen Latency: 11.4s

✔ 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 Trap

Business Scenario & Problem

In financial ranking, when multiple entities have the exact same score, evaluating cumulative rank metrics without self-reinforcing duplicate ties prevents tied participants from skewing percentiles.

⚡ The Frontier Trap (Why LLMs Fail)

Tied participants mutually inflate each other's cumulative metrics.

Prompt / User Request Given to Model

In financial ranking, when multiple entities have the exact same score, evaluating cumulative rank metrics without self-reinforcing duplicate ties prevents tied participants from skewing percentiles.

Execute the required analytical SQL calculation in DuckDB.
Expected output columns: player_id, score, cumulative_score_excluding_tied_peers.
Results should be ordered as specified.

2. Underlying Tables, Row Counts & Data Volume

1 Tables (1,000,000 rows • 7.6 MiB)

Production-scale fixtures loaded into the isolated DuckDB sandbox with at least 1,000,000 records per table:

📊 gaming_scores 1,000,000 rows 7.6 MiB Data Volume

player_id (INTEGER) score (INTEGER)

Data Preview (showing sample rows from 1,000,000 total rows):

#	player_id	score
1	1	500
2	2	450
3	3	450
4	4	300
5	4	480
6	5	282
7	6	322
8	7	330
9	8	346
10	9	359
11	10	571
12	11	444
13	12	315
14	13	505
15	14	417

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:

Pipeline Latency Distribution (Total Plan Time: 236.88 ms) Nodes consuming ≥ 20% of query runtime are highlighted with glowing borders

📐 PROJECTION 0.1%

Latency: 0.34 ms

Rows In/Out: 1,000,000

Data Vol: 22.89 MB

📁 Projections: ['#0', 'CAST(#1 AS ...

⏳ ORDER_BY 🔥 20.3% Cost

Latency: 48.03 ms

Rows In/Out: 1,000,000

Data Vol: 20.98 MB

📐 PROJECTION 0.3%

Latency: 0.72 ms

Rows In/Out: 1,000,000

Data Vol: 20.98 MB

📁 Projections: ['#0', 'CAST(#1 AS ...

📐 PROJECTION 0.1%

Latency: 0.13 ms

Rows In/Out: 1,000,000

Data Vol: 22.89 MB

📁 Projections: ['#0', '#1', '#2']

🪟 WINDOW 🔥 78.8% Cost

Latency: 186.65 ms

Rows In/Out: 1,000,000

Data Vol: 22.89 MB

📁 Projections: sum_no_overflow(sco...

🔍 TABLE_SCAN 0.4%

Latency: 1.01 ms

Rows In/Out: 1,000,000

Data Vol: 7.63 MB

📁 memory.main.gaming_scores

Operator	Cost %	Latency	Processed Rows	Data Volume	Details / Table	Status
WINDOW	78.8%	186.65 ms	1,000,000	22.89 MB	Projections: sum_no_overflow(score) OVER (ORDER	🔥 BOTTLENECK
ORDER_BY	20.3%	48.03 ms	1,000,000	20.98 MB	-	🔥 BOTTLENECK
TABLE_SCAN	0.4%	1.01 ms	1,000,000	7.63 MB	memory.main.gaming_scores	Normal
PROJECTION	0.3%	0.72 ms	1,000,000	20.98 MB	Projections: ['#0', 'CAST(#1 AS SMALLINT)', '#2'	Normal
PROJECTION	0.1%	0.34 ms	1,000,000	22.89 MB	Projections: ['#0', 'CAST(#1 AS INTEGER)', '#2']	Normal
PROJECTION	0.1%	0.13 ms	1,000,000	22.89 MB	Projections: ['#0', '#1', '#2']	Normal

4. Queries Executed (Candidate vs Golden Ground Truth)

Beautified & Syntax Highlighted

SELECT player_id,
       score,
       sum(score) OVER (
                        ORDER BY score DESC RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW exclude ties) AS cumulative_score_excluding_tied_peers
FROM gaming_scores
ORDER BY score DESC,
         player_id;

-- Calculate cumulative score excluding tied peers at the current rank

SELECT player_id,
       score,
       sum(score) OVER (
                        ORDER BY score DESC RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW exclude ties) AS cumulative_score_excluding_tied_peers
FROM gaming_scores
ORDER BY score DESC,
         player_id;

CREATE TABLE gaming_scores (player_id INT, score INT);


INSERT INTO gaming_scores
VALUES (1, 500),
       (2, 450),
       (3, 450),
       -- Tie
 (4, 300);

5. Query Results & Expected Ground Truth

Tabular Comparison

Actual Candidate Output (1,000,000 rows × 3 cols)

#	player_id	score	cumulative_score_excluding_tied_peers
1	568,164	835	835
2	327,804	824	1,659
3	732,572	817	2,476
4	535,833	813	3,289
5	892,445	811	4,100
6	409,880	803	4,903
7	23,940	800	5,703
8	251,918	797	6,500
9	908,613	793	7,293
10	62,078	789	8,082
11	206,628	788	8,870
12	985,463	788	8,870
13	282,897	787	10,445
14	195,133	786	11,231
15	892,873	786	11,231
16	293,670	784	12,801
17	351,391	783	13,584
18	69,527	775	14,359
19	360,269	775	14,359
20	486,002	771	15,905
21	952,400	771	15,905
22	863,798	770	17,446
23	144,795	769	18,215
24	854,631	769	18,215
25	20,336	768	19,752

Showing first 25 of 1,000,000 total rows.

Expected Golden Output (1,000,000 rows × 3 cols)

#	player_id	score	cumulative_score_excluding_tied_peers
1	568,164	835	835
2	327,804	824	1,659
3	732,572	817	2,476
4	535,833	813	3,289
5	892,445	811	4,100
6	409,880	803	4,903
7	23,940	800	5,703
8	251,918	797	6,500
9	908,613	793	7,293
10	62,078	789	8,082
11	206,628	788	8,870
12	985,463	788	8,870
13	282,897	787	10,445
14	195,133	786	11,231
15	892,873	786	11,231
16	293,670	784	12,801
17	351,391	783	13,584
18	69,527	775	14,359
19	360,269	775	14,359
20	486,002	771	15,905
21	952,400	771	15,905
22	863,798	770	17,446
23	144,795	769	18,215
24	854,631	769	18,215
25	20,336	768	19,752

Showing first 25 of 1,000,000 total rows.

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#	player_id	score
1	1	500
2	2	450
3	3	450
4	4	300
5	4	480
6	5	282
7	6	322
8	7	330
9	8	346
10	9	359
11	10	571
12	11	444
13	12	315
14	13	505
15	14	417

#	player_id	score
1	1	500
2	2	450
3	3	450
4	4	300
5	4	480
6	5	282
7	6	322
8	7	330
9	8	346
10	9	359
11	10	571
12	11	444
13	12	315
14	13	505
15	14	417

#	player_id	score
1	1	500
2	2	450
3	3	450
4	4	300
5	4	480
6	5	282
7	6	322
8	7	330
9	8	346
10	9	359
11	10	571
12	11	444
13	12	315
14	13	505
15	14	417