✔ PASS Temporal & Time-Series task_011_Q11_exclude_ties_ranking Scaled: 1M+ Records Ordered: Yes

Excluding Ties in Percentile Ranks via EXCLUDE TIES

Candidate Latency (1M Rows)

124.91 ms

(1.0x slower than golden)

Golden Latency (1M Rows)

124.23 ms

DuckDB in-memory engine

Underlying Data Volume

1,000,000 rows

19.1 MiB across 1 table

Evaluated Model

gemini-3.8-flash-low

Gen Latency: 13.7s

✔ 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

When evaluating employee sales performance, ties should not inflate the percentile score against colleagues who achieved the exact same result.

⚡ The Frontier Trap (Why LLMs Fail)

Using standard RANK() causes tied individuals to push each other's percentiles higher or lower inconsistently.

Prompt / User Request Given to Model

When evaluating employee sales performance, ties should not inflate the percentile score against colleagues who achieved the exact same result.

Execute the required analytical SQL calculation in DuckDB.
Expected output columns: rep_id, sales_quota_achieved, cumulative_sales_exclusive_of_ties.
Results should be ordered as specified.

2. Underlying Tables, Row Counts & Data Volume

1 Tables (1,000,000 rows • 19.1 MiB)

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

📊 rep_sales 1,000,000 rows 19.1 MiB Data Volume

rep_id (INTEGER) sales_quota_achieved (DECIMAL(5,2))

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

#	rep_id	sales_quota_achieved
1	1	120
2	2	115
3	3	115
4	4	95
5	4	131.03
6	5	117.46
7	6	112.5
8	7	100.03
9	8	107.69
10	9	111.91
11	10	131.52
12	11	116.64
13	12	104.59
14	13	125.12
15	14	101.89

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: 267.14 ms) Nodes consuming ≥ 20% of query runtime are highlighted with glowing borders

⏳ ORDER_BY 🔥 29.3% Cost

Latency: 78.15 ms

Rows In/Out: 1,000,000

Data Vol: 22.89 MB

📐 PROJECTION 0.1%

Latency: 0.14 ms

Rows In/Out: 1,000,000

Data Vol: 22.89 MB

📁 Projections: ['#0', '#1', '#2']

🪟 WINDOW 🔥 70.3% Cost

Latency: 187.81 ms

Rows In/Out: 1,000,000

Data Vol: 22.89 MB

📁 Projections: sum_no_overflow(sal...

🔍 TABLE_SCAN 0.4%

Latency: 1.03 ms

Rows In/Out: 1,000,000

Data Vol: 7.63 MB

📁 memory.main.rep_sales

Operator	Cost %	Latency	Processed Rows	Data Volume	Details / Table	Status
WINDOW	70.3%	187.81 ms	1,000,000	22.89 MB	Projections: sum_no_overflow(sales_quota_achieve	🔥 BOTTLENECK
ORDER_BY	29.3%	78.15 ms	1,000,000	22.89 MB	-	🔥 BOTTLENECK
TABLE_SCAN	0.4%	1.03 ms	1,000,000	7.63 MB	memory.main.rep_sales	Normal
PROJECTION	0.1%	0.14 ms	1,000,000	22.89 MB	Projections: ['#0', '#1', '#2']	Normal

4. Queries Executed (Candidate vs Golden Ground Truth)

Beautified & Syntax Highlighted

SELECT rep_id,
       sales_quota_achieved,
       sum(sales_quota_achieved) OVER (
                                       ORDER BY sales_quota_achieved DESC RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW exclude ties) AS cumulative_sales_exclusive_of_ties
FROM rep_sales
ORDER BY sales_quota_achieved DESC,
         rep_id;

-- Compute cumulative sales sum excluding tied peers in current row calculation

SELECT rep_id,
       sales_quota_achieved,
       sum(sales_quota_achieved) OVER (
                                       ORDER BY sales_quota_achieved DESC RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW exclude ties) AS cumulative_sales_exclusive_of_ties
FROM rep_sales
ORDER BY sales_quota_achieved DESC,
         rep_id;

CREATE TABLE rep_sales (rep_id INT, sales_quota_achieved decimal(5, 2));


INSERT INTO rep_sales
VALUES (1, 120.00),
       (2, 115.00),
       (3, 115.00),
       -- Tie
 (4, 95.00);

5. Query Results & Expected Ground Truth

Tabular Comparison

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

#	rep_id	sales_quota_achieved	cumulative_sales_exclusive_of_ties
1	814,234	162.05	162.05
2	593,667	161.21	323.26
3	775,185	159.87	483.13
4	419,683	159.82	642.95
5	880,050	158.35	801.3
6	213,542	158.34	959.64
7	44,600	158.17	1,117.81
8	654,559	157.88	1,275.69
9	754,964	157.66	1,433.35
10	89,090	157.62	1,590.97
11	219,193	157.6	1,748.57
12	396,664	157.48	1,906.05
13	88,824	157.4	2,063.45
14	396,388	157.33	2,220.78
15	226,014	157.16	2,377.94
16	587,083	157	2,534.94
17	704,525	156.85	2,691.79
18	427,376	156.82	2,848.61
19	384,977	156.76	3,005.37
20	920,396	156.63	3,162
21	750,480	156.49	3,318.49
22	505,177	156.26	3,474.75
23	418,422	156.11	3,630.86
24	841,268	156.03	3,786.89
25	233,920	156.01	3,942.9

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

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

#	rep_id	sales_quota_achieved	cumulative_sales_exclusive_of_ties
1	814,234	162.05	162.05
2	593,667	161.21	323.26
3	775,185	159.87	483.13
4	419,683	159.82	642.95
5	880,050	158.35	801.3
6	213,542	158.34	959.64
7	44,600	158.17	1,117.81
8	654,559	157.88	1,275.69
9	754,964	157.66	1,433.35
10	89,090	157.62	1,590.97
11	219,193	157.6	1,748.57
12	396,664	157.48	1,906.05
13	88,824	157.4	2,063.45
14	396,388	157.33	2,220.78
15	226,014	157.16	2,377.94
16	587,083	157	2,534.94
17	704,525	156.85	2,691.79
18	427,376	156.82	2,848.61
19	384,977	156.76	3,005.37
20	920,396	156.63	3,162
21	750,480	156.49	3,318.49
22	505,177	156.26	3,474.75
23	418,422	156.11	3,630.86
24	841,268	156.03	3,786.89
25	233,920	156.01	3,942.9

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

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