✔ PASS
Temporal & Time-Series
task_001_Q01_asof_trade_quote_matching
Scaled: 1M+ Records
Ordered: Yes
Tick-Level Trade Execution Matching via Native ASOF JOIN
Candidate Latency (1M Rows)
452.41 ms
(1.0x slower than golden)
Golden Latency (1M Rows)
450.01 ms
DuckDB in-memory engine
Underlying Data Volume
2,000,000 rows
83.9 MiB across 2 tables
Evaluated Model
gemini-3.8-flash-low
Gen Latency: 15.5s
✔ 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
In algorithmic trading, every buy or sell order must be evaluated against the most recent prevailing market quote. Standard relational equality joins fail because quotes and trades happen at irregular microsecond intervals.
⚡ The Frontier Trap (Why LLMs Fail)
LLMs typically write quadratic triangular self-joins (WHERE q.ts <= t.ts) or window functions with LAG/LAST_VALUE, which create massive memory spikes on high-frequency streams.
Prompt / User Request Given to Model
In algorithmic trading, every buy or sell order must be evaluated against the most recent prevailing market quote. Standard relational equality joins fail because quotes and trades happen at irregular microsecond intervals. Execute the required analytical SQL calculation in DuckDB. Expected output columns: trade_id, symbol, trade_time, executed_price, shares, prevailing_quote_time, bid_price, ask_price, slippage. Results should be ordered as specified.
2. Underlying Tables, Row Counts & Data Volume
2 Tables (2,000,000 rows • 83.9 MiB)Production-scale fixtures loaded into the isolated DuckDB sandbox with at least 1,000,000 records per table:
📊 quotes
1,000,000 rows
42.0 MiB Data Volume
quote_time (TIMESTAMP) symbol (VARCHAR) bid_price (DOUBLE) ask_price (DOUBLE)Data Preview (showing sample rows from 1,000,000 total rows):
| # | quote_time | symbol | bid_price | ask_price |
|---|---|---|---|---|
| 1 | 2026-03-01 09:30:00.100000 | NVDA | 850.1 | 850.25 |
| 2 | 2026-03-01 09:30:00.250000 | NVDA | 850.15 | 850.3 |
| 3 | 2026-03-01 09:30:00.400000 | NVDA | 850.2 | 850.35 |
| 4 | 2026-03-01 09:30:00.000001 | NVDA | 850.14 | 850.29 |
| 5 | 2026-03-01 09:30:00.000022 | AAPL | 850.14 | 850.29 |
| 6 | 2026-03-01 09:30:00.000044 | MSFT | 850.18 | 850.33 |
| 7 | 2026-03-01 09:30:00.000073 | GOOGL | 850.23 | 850.38 |
| 8 | 2026-03-01 09:30:00.000087 | AMZN | 850.11 | 850.26 |
| 9 | 2026-03-01 09:30:00.000104 | TSLA | 850.18 | 850.33 |
| 10 | 2026-03-01 09:30:00.000125 | META | 850.12 | 850.27 |
| 11 | 2026-03-01 09:30:00.000140 | AMD | 850.15 | 850.3 |
| 12 | 2026-03-01 09:30:00.000164 | NVDA | 850.18 | 850.33 |
| 13 | 2026-03-01 09:30:00.000181 | AAPL | 850.16 | 850.31 |
| 14 | 2026-03-01 09:30:00.000215 | MSFT | 850.06 | 850.21 |
| 15 | 2026-03-01 09:30:00.000229 | GOOGL | 850.2 | 850.35 |
📊 trades
1,000,000 rows
42.0 MiB Data Volume
trade_time (TIMESTAMP) symbol (VARCHAR) trade_id (INTEGER) executed_price (DOUBLE) shares (INTEGER)Data Preview (showing sample rows from 1,000,000 total rows):
| # | trade_time | symbol | trade_id | executed_price | shares |
|---|---|---|---|---|---|
| 1 | 2026-03-01 09:30:00.150000 | NVDA | 101 | 850.25 | 100 |
| 2 | 2026-03-01 09:30:00.300000 | NVDA | 102 | 850.3 | 200 |
| 3 | 2026-03-01 09:30:00.450000 | NVDA | 103 | 850.32 | 150 |
| 4 | 2026-03-01 09:30:00.000002 | NVDA | 103 | 850.28 | 165 |
| 5 | 2026-03-01 09:30:00.000027 | AAPL | 104 | 850.25 | 137 |
| 6 | 2026-03-01 09:30:00.000053 | MSFT | 105 | 850.23 | 118 |
| 7 | 2026-03-01 09:30:00.000063 | GOOGL | 106 | 850.28 | 125 |
| 8 | 2026-03-01 09:30:00.000082 | AMZN | 107 | 850.3 | 138 |
| 9 | 2026-03-01 09:30:00.000110 | TSLA | 108 | 850.34 | 90 |
| 10 | 2026-03-01 09:30:00.000121 | META | 109 | 850.28 | 199 |
| 11 | 2026-03-01 09:30:00.000141 | AMD | 110 | 850.3 | 123 |
| 12 | 2026-03-01 09:30:00.000166 | NVDA | 111 | 850.32 | 140 |
| 13 | 2026-03-01 09:30:00.000186 | AAPL | 112 | 850.26 | 134 |
| 14 | 2026-03-01 09:30:00.000212 | MSFT | 113 | 850.23 | 70 |
| 15 | 2026-03-01 09:30:00.000233 | GOOGL | 114 | 850.35 | 256 |
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:
0.2%
Latency: 1.88 ms
Rows In/Out: 999,997
Data Vol: 68.66 MB
📁 Projections: ['#0', '__internal_...
🔥 13.2% Cost
Latency: 142.42 ms
Rows In/Out: 999,997
Data Vol: 59.13 MB
0.7%
Latency: 7.65 ms
Rows In/Out: 999,997
Data Vol: 59.13 MB
📁 Projections: ['#0', '__internal_...
3.1%
Latency: 33.15 ms
Rows In/Out: 999,997
Data Vol: 68.66 MB
📁 Projections: ['trade_id', 'symbo...
🔥 80.5% Cost
Latency: 867.14 ms
Rows In/Out: 999,997
Data Vol: 61.03 MB
1.2%
Latency: 12.68 ms
Rows In/Out: 1,000,000
Data Vol: 38.15 MB
📁 memory.main.trades
1.2%
Latency: 12.62 ms
Rows In/Out: 1,000,000
Data Vol: 38.15 MB
📁 memory.main.quotes
| Operator | Cost % | Latency | Processed Rows | Data Volume | Details / Table | Status |
|---|---|---|---|---|---|---|
| ASOF_JOIN | 80.5% | 867.14 ms | 999,997 | 61.03 MB | - | 🔥 BOTTLENECK |
| ORDER_BY | 13.2% | 142.42 ms | 999,997 | 59.13 MB | - | 🔥 BOTTLENECK |
| PROJECTION | 3.1% | 33.15 ms | 999,997 | 68.66 MB | Projections: ['trade_id', 'symbol', 'trade_time' | Normal |
| TABLE_SCAN | 1.2% | 12.68 ms | 1,000,000 | 38.15 MB | memory.main.trades | Normal |
| TABLE_SCAN | 1.2% | 12.62 ms | 1,000,000 | 38.15 MB | memory.main.quotes | Normal |
| PROJECTION | 0.7% | 7.65 ms | 999,997 | 59.13 MB | Projections: ['#0', '__internal_compress_string_ | Normal |
| PROJECTION | 0.2% | 1.88 ms | 999,997 | 68.66 MB | Projections: ['#0', '__internal_decompress_strin | Normal |
4. Queries Executed (Candidate vs Golden Ground Truth)
Beautified & Syntax HighlightedSELECT t.trade_id,
t.symbol,
t.trade_time,
t.executed_price,
t.shares,
q.quote_time AS prevailing_quote_time,
q.bid_price,
q.ask_price,
round(t.executed_price - q.ask_price, 4) AS slippage
FROM trades t asof
JOIN quotes q ON t.symbol = q.symbol
AND t.trade_time >= q.quote_time
ORDER BY t.trade_time;
-- Match each executed trade with the latest market quote effective at that exact microsecond
SELECT t.trade_id,
t.symbol,
t.trade_time,
t.executed_price,
t.shares,
q.quote_time AS prevailing_quote_time,
q.bid_price,
q.ask_price, -- Effective slippage calculation (difference between ask and executed price)
round(t.executed_price - q.ask_price, 4) AS slippage
FROM trades t asof
JOIN quotes q ON t.symbol = q.symbol
AND t.trade_time >= q.quote_time
ORDER BY t.trade_time;
CREATE TABLE quotes (quote_time TIMESTAMP, symbol VARCHAR, bid_price DOUBLE,
ask_price DOUBLE);
CREATE TABLE trades (trade_time TIMESTAMP, symbol VARCHAR, trade_id INT, executed_price DOUBLE,
shares INT);
INSERT INTO quotes
VALUES ('2026-03-01 09:30:00.100', 'NVDA', 850.10, 850.25),
('2026-03-01 09:30:00.250', 'NVDA', 850.15, 850.30),
('2026-03-01 09:30:00.400', 'NVDA', 850.20, 850.35);
INSERT INTO trades
VALUES ('2026-03-01 09:30:00.150', 'NVDA', 101, 850.25, 100),
('2026-03-01 09:30:00.300', 'NVDA', 102, 850.30, 200),
('2026-03-01 09:30:00.450', 'NVDA', 103, 850.32, 150);
5. Query Results & Expected Ground Truth
Tabular Comparison
Actual Candidate Output
(999,997 rows × 9 cols)
| # | trade_id | symbol | trade_time | executed_price | shares | prevailing_quote_time | bid_price | ask_price | slippage |
|---|---|---|---|---|---|---|---|---|---|
| 1 | 103 | NVDA | 2026-03-01 09:30:00.000002 | 850.28 | 165 | 2026-03-01 09:30:00.000001 | 850.14 | 850.29 | -0.01 |
| 2 | 104 | AAPL | 2026-03-01 09:30:00.000027 | 850.25 | 137 | 2026-03-01 09:30:00.000022 | 850.14 | 850.29 | -0.04 |
| 3 | 105 | MSFT | 2026-03-01 09:30:00.000053 | 850.23 | 118 | 2026-03-01 09:30:00.000044 | 850.18 | 850.33 | -0.1 |
| 4 | 108 | TSLA | 2026-03-01 09:30:00.000110 | 850.34 | 90 | 2026-03-01 09:30:00.000104 | 850.18 | 850.33 | 0.01 |
| 5 | 110 | AMD | 2026-03-01 09:30:00.000141 | 850.3 | 123 | 2026-03-01 09:30:00.000140 | 850.15 | 850.3 | 0 |
| 6 | 111 | NVDA | 2026-03-01 09:30:00.000166 | 850.32 | 140 | 2026-03-01 09:30:00.000164 | 850.18 | 850.33 | -0.01 |
| 7 | 112 | AAPL | 2026-03-01 09:30:00.000186 | 850.26 | 134 | 2026-03-01 09:30:00.000181 | 850.16 | 850.31 | -0.05 |
| 8 | 113 | MSFT | 2026-03-01 09:30:00.000212 | 850.23 | 70 | 2026-03-01 09:30:00.000044 | 850.18 | 850.33 | -0.1 |
| 9 | 114 | GOOGL | 2026-03-01 09:30:00.000233 | 850.35 | 256 | 2026-03-01 09:30:00.000229 | 850.2 | 850.35 | 0 |
| 10 | 115 | AMZN | 2026-03-01 09:30:00.000242 | 850.3 | 217 | 2026-03-01 09:30:00.000087 | 850.11 | 850.26 | 0.04 |
| 11 | 116 | TSLA | 2026-03-01 09:30:00.000260 | 850.29 | 110 | 2026-03-01 09:30:00.000104 | 850.18 | 850.33 | -0.04 |
| 12 | 117 | META | 2026-03-01 09:30:00.000285 | 850.31 | 172 | 2026-03-01 09:30:00.000282 | 850.16 | 850.31 | 0 |
| 13 | 118 | AMD | 2026-03-01 09:30:00.000303 | 850.31 | 141 | 2026-03-01 09:30:00.000300 | 850.15 | 850.3 | 0.01 |
| 14 | 119 | NVDA | 2026-03-01 09:30:00.000325 | 850.26 | 60 | 2026-03-01 09:30:00.000321 | 850.14 | 850.29 | -0.03 |
| 15 | 120 | AAPL | 2026-03-01 09:30:00.000344 | 850.31 | 128 | 2026-03-01 09:30:00.000343 | 850.13 | 850.28 | 0.03 |
| 16 | 121 | MSFT | 2026-03-01 09:30:00.000364 | 850.27 | 92 | 2026-03-01 09:30:00.000363 | 850.17 | 850.32 | -0.05 |
| 17 | 122 | GOOGL | 2026-03-01 09:30:00.000383 | 850.31 | 223 | 2026-03-01 09:30:00.000229 | 850.2 | 850.35 | -0.04 |
| 18 | 123 | AMZN | 2026-03-01 09:30:00.000413 | 850.36 | 164 | 2026-03-01 09:30:00.000409 | 850.2 | 850.35 | 0.01 |
| 19 | 124 | TSLA | 2026-03-01 09:30:00.000437 | 850.37 | 227 | 2026-03-01 09:30:00.000427 | 850.11 | 850.26 | 0.11 |
| 20 | 125 | META | 2026-03-01 09:30:00.000442 | 850.28 | 146 | 2026-03-01 09:30:00.000282 | 850.16 | 850.31 | -0.03 |
| 21 | 126 | AMD | 2026-03-01 09:30:00.000460 | 850.29 | 167 | 2026-03-01 09:30:00.000300 | 850.15 | 850.3 | -0.01 |
| 22 | 127 | NVDA | 2026-03-01 09:30:00.000482 | 850.28 | 140 | 2026-03-01 09:30:00.000321 | 850.14 | 850.29 | -0.01 |
| 23 | 128 | AAPL | 2026-03-01 09:30:00.000508 | 850.25 | 94 | 2026-03-01 09:30:00.000502 | 850.13 | 850.28 | -0.03 |
| 24 | 129 | MSFT | 2026-03-01 09:30:00.000528 | 850.33 | 185 | 2026-03-01 09:30:00.000525 | 850.12 | 850.27 | 0.06 |
| 25 | 130 | GOOGL | 2026-03-01 09:30:00.000541 | 850.28 | 180 | 2026-03-01 09:30:00.000385 | 850.12 | 850.27 | 0.01 |
Showing first 25 of 999,997 total rows.
Expected Golden Output
(999,997 rows × 9 cols)
| # | trade_id | symbol | trade_time | executed_price | shares | prevailing_quote_time | bid_price | ask_price | slippage |
|---|---|---|---|---|---|---|---|---|---|
| 1 | 103 | NVDA | 2026-03-01 09:30:00.000002 | 850.28 | 165 | 2026-03-01 09:30:00.000001 | 850.14 | 850.29 | -0.01 |
| 2 | 104 | AAPL | 2026-03-01 09:30:00.000027 | 850.25 | 137 | 2026-03-01 09:30:00.000022 | 850.14 | 850.29 | -0.04 |
| 3 | 105 | MSFT | 2026-03-01 09:30:00.000053 | 850.23 | 118 | 2026-03-01 09:30:00.000044 | 850.18 | 850.33 | -0.1 |
| 4 | 108 | TSLA | 2026-03-01 09:30:00.000110 | 850.34 | 90 | 2026-03-01 09:30:00.000104 | 850.18 | 850.33 | 0.01 |
| 5 | 110 | AMD | 2026-03-01 09:30:00.000141 | 850.3 | 123 | 2026-03-01 09:30:00.000140 | 850.15 | 850.3 | 0 |
| 6 | 111 | NVDA | 2026-03-01 09:30:00.000166 | 850.32 | 140 | 2026-03-01 09:30:00.000164 | 850.18 | 850.33 | -0.01 |
| 7 | 112 | AAPL | 2026-03-01 09:30:00.000186 | 850.26 | 134 | 2026-03-01 09:30:00.000181 | 850.16 | 850.31 | -0.05 |
| 8 | 113 | MSFT | 2026-03-01 09:30:00.000212 | 850.23 | 70 | 2026-03-01 09:30:00.000044 | 850.18 | 850.33 | -0.1 |
| 9 | 114 | GOOGL | 2026-03-01 09:30:00.000233 | 850.35 | 256 | 2026-03-01 09:30:00.000229 | 850.2 | 850.35 | 0 |
| 10 | 115 | AMZN | 2026-03-01 09:30:00.000242 | 850.3 | 217 | 2026-03-01 09:30:00.000087 | 850.11 | 850.26 | 0.04 |
| 11 | 116 | TSLA | 2026-03-01 09:30:00.000260 | 850.29 | 110 | 2026-03-01 09:30:00.000104 | 850.18 | 850.33 | -0.04 |
| 12 | 117 | META | 2026-03-01 09:30:00.000285 | 850.31 | 172 | 2026-03-01 09:30:00.000282 | 850.16 | 850.31 | 0 |
| 13 | 118 | AMD | 2026-03-01 09:30:00.000303 | 850.31 | 141 | 2026-03-01 09:30:00.000300 | 850.15 | 850.3 | 0.01 |
| 14 | 119 | NVDA | 2026-03-01 09:30:00.000325 | 850.26 | 60 | 2026-03-01 09:30:00.000321 | 850.14 | 850.29 | -0.03 |
| 15 | 120 | AAPL | 2026-03-01 09:30:00.000344 | 850.31 | 128 | 2026-03-01 09:30:00.000343 | 850.13 | 850.28 | 0.03 |
| 16 | 121 | MSFT | 2026-03-01 09:30:00.000364 | 850.27 | 92 | 2026-03-01 09:30:00.000363 | 850.17 | 850.32 | -0.05 |
| 17 | 122 | GOOGL | 2026-03-01 09:30:00.000383 | 850.31 | 223 | 2026-03-01 09:30:00.000229 | 850.2 | 850.35 | -0.04 |
| 18 | 123 | AMZN | 2026-03-01 09:30:00.000413 | 850.36 | 164 | 2026-03-01 09:30:00.000409 | 850.2 | 850.35 | 0.01 |
| 19 | 124 | TSLA | 2026-03-01 09:30:00.000437 | 850.37 | 227 | 2026-03-01 09:30:00.000427 | 850.11 | 850.26 | 0.11 |
| 20 | 125 | META | 2026-03-01 09:30:00.000442 | 850.28 | 146 | 2026-03-01 09:30:00.000282 | 850.16 | 850.31 | -0.03 |
| 21 | 126 | AMD | 2026-03-01 09:30:00.000460 | 850.29 | 167 | 2026-03-01 09:30:00.000300 | 850.15 | 850.3 | -0.01 |
| 22 | 127 | NVDA | 2026-03-01 09:30:00.000482 | 850.28 | 140 | 2026-03-01 09:30:00.000321 | 850.14 | 850.29 | -0.01 |
| 23 | 128 | AAPL | 2026-03-01 09:30:00.000508 | 850.25 | 94 | 2026-03-01 09:30:00.000502 | 850.13 | 850.28 | -0.03 |
| 24 | 129 | MSFT | 2026-03-01 09:30:00.000528 | 850.33 | 185 | 2026-03-01 09:30:00.000525 | 850.12 | 850.27 | 0.06 |
| 25 | 130 | GOOGL | 2026-03-01 09:30:00.000541 | 850.28 | 180 | 2026-03-01 09:30:00.000385 | 850.12 | 850.27 | 0.01 |
Showing first 25 of 999,997 total rows.