SQL-FRONTIER Benchmark Deep-Dive / Temporal & Time-Series / task_015_Q15_volume_weighted_average_price_vwap
← Prev: Time-Weighted Average Pri... ⊞ All 120 Queries Next: Chronological Multi-Stage... →
✔ PASS Temporal & Time-Series task_015_Q15_volume_weighted_average_price_vwap Scaled: 1M+ Records Ordered: Yes

Intraday Volume-Weighted Average Price (VWAP) Resetting Daily

Candidate Latency (1M Rows)
448.39 ms
(1.0x slower than golden)
Golden Latency (1M Rows)
434.53 ms
DuckDB in-memory engine
Underlying Data Volume
1,000,000 rows
38.1 MiB across 1 table
Evaluated Model
gemini-3.8-flash-low
Gen Latency: 4.3s
✔ 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

VWAP provides institutional traders the definitive benchmark price weighted by traded volume, resetting to zero at the start of every trading day.

⚡ The Frontier Trap (Why LLMs Fail)

Failing to partition by trading date mixes multi-day volume into the intraday numerator and denominator.

Prompt / User Request Given to Model
VWAP provides institutional traders the definitive benchmark price weighted by traded volume, resetting to zero at the start of every trading day.

Execute the required analytical SQL calculation in DuckDB.
Expected output columns: symbol, trade_time, price, volume, intraday_vwap.
Results should be ordered as specified.

2. Underlying Tables, Row Counts & Data Volume

1 Tables (1,000,000 rows • 38.1 MiB)

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

📊 market_trades 1,000,000 rows 38.1 MiB Data Volume
symbol (VARCHAR) trade_time (TIMESTAMP) price (DOUBLE) volume (INTEGER)
Data Preview (showing sample rows from 1,000,000 total rows):
# symbol trade_time price volume
1 AAPL 2026-03-01 09:35:00 180 1,000
2 AAPL 2026-03-01 09:40:00 181 2,000
3 AAPL 2026-03-02 09:35:00 182 500
4 NVDA 2026-03-01 09:30:00.000003 180.6 786
5 AAPL 2026-03-01 09:30:00.000024 181.44 2,109
6 MSFT 2026-03-01 09:30:00.000050 179.79 486
7 GOOGL 2026-03-01 09:30:00.000068 182.04 1,598
8 AMZN 2026-03-01 09:30:00.000094 182.7 1,874
9 TSLA 2026-03-01 09:30:00.000102 180.77 633
10 META 2026-03-01 09:30:00.000122 181.19 1,483
11 AMD 2026-03-01 09:30:00.000144 180.51 828
12 NVDA 2026-03-01 09:30:00.000164 181.49 1,444
13 AAPL 2026-03-01 09:30:00.000182 181.28 735
14 MSFT 2026-03-01 09:30:00.000200 180.94 1,031
15 GOOGL 2026-03-01 09:30:00.000228 180.01 622

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: 1185.57 ms) Nodes consuming ≥ 20% of query runtime are highlighted with glowing borders
📐 PROJECTION 0.1%
Latency: 1.64 ms
Rows In/Out: 1,000,000
Data Vol: 41.96 MB
📁 Projections: ['__internal_decomp...
⏳ ORDER_BY 🔥 9.3% Cost
Latency: 109.72 ms
Rows In/Out: 1,000,000
Data Vol: 32.42 MB
⚠️ Heavy Execution Bottleneck (9.3% of query runtime)
📐 PROJECTION 0.4%
Latency: 4.83 ms
Rows In/Out: 1,000,000
Data Vol: 32.42 MB
📁 Projections: ['__internal_compre...
📐 PROJECTION 0.4%
Latency: 5.11 ms
Rows In/Out: 1,000,000
Data Vol: 41.96 MB
📁 Projections: ['symbol', 'trade_t...
📐 PROJECTION 0.0%
Latency: 0.38 ms
Rows In/Out: 1,000,000
Data Vol: 57.22 MB
📁 Projections: ['#0', '#1', '#2', ...
🪟 WINDOW 🔥 88.7% Cost
Latency: 1051.43 ms
Rows In/Out: 1,000,000
Data Vol: 57.22 MB
📁 Projections: ['sum((price * CAST...
⚠️ Heavy Execution Bottleneck (88.7% of query runtime)
🔍 TABLE_SCAN 1.1%
Latency: 12.47 ms
Rows In/Out: 1,000,000
Data Vol: 34.33 MB
📁 memory.main.market_trades
Operator Cost % Latency Processed Rows Data Volume Details / Table Status
WINDOW 88.7% 1051.43 ms 1,000,000 57.22 MB Projections: ['sum((price * CAST(volume AS DOUBL 🔥 BOTTLENECK
ORDER_BY 9.3% 109.72 ms 1,000,000 32.42 MB - 🔥 BOTTLENECK
TABLE_SCAN 1.1% 12.47 ms 1,000,000 34.33 MB memory.main.market_trades Normal
PROJECTION 0.4% 5.11 ms 1,000,000 41.96 MB Projections: ['symbol', 'trade_time', 'price', ' Normal
PROJECTION 0.4% 4.83 ms 1,000,000 32.42 MB Projections: ['__internal_compress_string_ubigin Normal
PROJECTION 0.1% 1.64 ms 1,000,000 41.96 MB Projections: ['__internal_decompress_string(#0)' Normal
PROJECTION 0.0% 0.38 ms 1,000,000 57.22 MB Projections: ['#0', '#1', '#2', '#3', '#4', '#5' Normal

4. Queries Executed (Candidate vs Golden Ground Truth)

Beautified & Syntax Highlighted
Candidate SQL Executed by gemini-3.8-flash-low (Runtime on 1M Rows: 448.39 ms) 
SELECT symbol,
       trade_time,
       price,
       volume,
       sum(price * volume) OVER (PARTITION BY symbol, cast(trade_time AS DATE)
                                 ORDER BY trade_time ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) / sum(volume) OVER (PARTITION BY symbol, cast(trade_time AS DATE)
                                                                                                                           ORDER BY trade_time ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) AS intraday_vwap
FROM market_trades
ORDER BY symbol,
         trade_time;
Golden Reference Ground Truth SQL (Runtime on 1M Rows: 434.53 ms) 
-- Intraday continuous VWAP calculation

SELECT symbol,
       trade_time,
       price,
       volume,
       round(sum(price * volume) OVER (PARTITION BY symbol, cast(trade_time AS DATE)
                                       ORDER BY trade_time ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) / sum(volume) OVER (PARTITION BY symbol, cast(trade_time AS DATE)
                                                                                                                                 ORDER BY trade_time ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW), 2) AS intraday_vwap
FROM market_trades
ORDER BY symbol,
         trade_time;
DuckDB Fixture Setup DDL & Data Population 
CREATE TABLE market_trades (symbol VARCHAR, trade_time TIMESTAMP, price DOUBLE,
                                                                        volume INT);


INSERT INTO market_trades
VALUES ('AAPL', '2026-03-01 09:35:00', 180.00, 1000),
       ('AAPL', '2026-03-01 09:40:00', 181.00, 2000),
       ('AAPL', '2026-03-02 09:35:00', 182.00, 500); -- Next day reset

5. Query Results & Expected Ground Truth

Tabular Comparison
Actual Candidate Output (1,000,000 rows × 5 cols)
# symbol trade_time price volume intraday_vwap
1 AAPL 2026-03-01 09:30:00.000024 181.44 2,109 181.44
2 AAPL 2026-03-01 09:30:00.000182 181.28 735 181.3986
3 AAPL 2026-03-01 09:30:00.000342 181.27 2,869 181.334
4 AAPL 2026-03-01 09:30:00.000501 181.08 1,481 181.2817
5 AAPL 2026-03-01 09:30:00.000675 182.93 1,635 181.587
6 AAPL 2026-03-01 09:30:00.000822 180.69 516 181.5374
7 AAPL 2026-03-01 09:30:00.000985 180.39 609 181.4672
8 AAPL 2026-03-01 09:30:00.001152 182.44 2,869 181.6849
9 AAPL 2026-03-01 09:30:00.001303 181.44 2,165 181.6495
10 AAPL 2026-03-01 09:30:00.001479 178.62 1 181.6493
11 AAPL 2026-03-01 09:30:00.001627 180.07 1,535 181.5026
12 AAPL 2026-03-01 09:30:00.001781 180.81 180 181.4951
13 AAPL 2026-03-01 09:30:00.001946 180.29 602 181.4532
14 AAPL 2026-03-01 09:30:00.002129 184.57 2,647 181.8667
15 AAPL 2026-03-01 09:30:00.002261 180.92 1,520 181.7997
16 AAPL 2026-03-01 09:30:00.002423 180.58 1,417 181.7242
17 AAPL 2026-03-01 09:30:00.002588 181.95 1,749 181.7402
18 AAPL 2026-03-01 09:30:00.002748 181.98 1,771 181.7563
19 AAPL 2026-03-01 09:30:00.002903 180.67 1,541 181.6964
20 AAPL 2026-03-01 09:30:00.003066 181.76 1,437 181.6995
21 AAPL 2026-03-01 09:30:00.003223 180.57 463 181.682
22 AAPL 2026-03-01 09:30:00.003394 182.78 1,975 181.7501
23 AAPL 2026-03-01 09:30:00.003546 180.21 443 181.729
24 AAPL 2026-03-01 09:30:00.003701 181.16 1,314 181.7067
25 AAPL 2026-03-01 09:30:00.003866 180.24 1,608 181.6397
Showing first 25 of 1,000,000 total rows.
Expected Golden Output (1,000,000 rows × 5 cols)
# symbol trade_time price volume intraday_vwap
1 AAPL 2026-03-01 09:30:00.000024 181.44 2,109 181.44
2 AAPL 2026-03-01 09:30:00.000182 181.28 735 181.4
3 AAPL 2026-03-01 09:30:00.000342 181.27 2,869 181.33
4 AAPL 2026-03-01 09:30:00.000501 181.08 1,481 181.28
5 AAPL 2026-03-01 09:30:00.000675 182.93 1,635 181.59
6 AAPL 2026-03-01 09:30:00.000822 180.69 516 181.54
7 AAPL 2026-03-01 09:30:00.000985 180.39 609 181.47
8 AAPL 2026-03-01 09:30:00.001152 182.44 2,869 181.68
9 AAPL 2026-03-01 09:30:00.001303 181.44 2,165 181.65
10 AAPL 2026-03-01 09:30:00.001479 178.62 1 181.65
11 AAPL 2026-03-01 09:30:00.001627 180.07 1,535 181.5
12 AAPL 2026-03-01 09:30:00.001781 180.81 180 181.5
13 AAPL 2026-03-01 09:30:00.001946 180.29 602 181.45
14 AAPL 2026-03-01 09:30:00.002129 184.57 2,647 181.87
15 AAPL 2026-03-01 09:30:00.002261 180.92 1,520 181.8
16 AAPL 2026-03-01 09:30:00.002423 180.58 1,417 181.72
17 AAPL 2026-03-01 09:30:00.002588 181.95 1,749 181.74
18 AAPL 2026-03-01 09:30:00.002748 181.98 1,771 181.76
19 AAPL 2026-03-01 09:30:00.002903 180.67 1,541 181.7
20 AAPL 2026-03-01 09:30:00.003066 181.76 1,437 181.7
21 AAPL 2026-03-01 09:30:00.003223 180.57 463 181.68
22 AAPL 2026-03-01 09:30:00.003394 182.78 1,975 181.75
23 AAPL 2026-03-01 09:30:00.003546 180.21 443 181.73
24 AAPL 2026-03-01 09:30:00.003701 181.16 1,314 181.71
25 AAPL 2026-03-01 09:30:00.003866 180.24 1,608 181.64
Showing first 25 of 1,000,000 total rows.
← Prev: Time-Weighted Average Pri... ⊞ Back to Benchmark Dashboard Next: Chronological Multi-Stage... →