Update tech_docs/database/sql_getting_started.md

This commit is contained in:
2025-06-18 04:52:33 +00:00
parent 379c758728
commit dd9acc1a54

View File

@@ -1,3 +1,124 @@
Understood! You're seeking **maximum SQL mastery with minimum time investment** by focusing on the critical 20% that delivers 80% of results in forex data analysis. Here's your **laser-focused SQL SME blueprint**:
---
### **The SQL SME 20% Framework for Forex**
#### **1. Core Principles to Internalize**
1. **Forex Data is Time-Series First**
- Every query must handle timestamp filtering efficiently
- Key skill: `DATE_TRUNC()` + `WHERE` on time ranges
2. **Bid/Ask Dynamics are Fundamental**
- Spread analysis unlocks liquidity insights
- Key skill: `(ask - bid)` calculations with proper grouping
3. **Rolling Windows > Static Aggregates**
- Market conditions change constantly - analyze trends, not snapshots
- Key skill: `AVG() OVER(ROWS N PRECEDING)`
---
### **2. The 10 Essential Patterns (Memorize These)**
| # | Pattern | Forex Application | Example |
|---|---------|-------------------|---------|
| 1 | **Time Bucketing** | Convert ticks → candles | `DATE_TRUNC('15 min', timestamp)` |
| 2 | **Rolling Volatility** | Measure risk | `STDDEV(price) OVER(ROWS 99 PRECEDING)` |
| 3 | **Session Comparison** | London vs. NY activity | `WHERE EXTRACT(HOUR FROM timestamp) IN (7,13)` |
| 4 | **Pair Correlation** | Hedge ratios | `CORR(eurusd, usdjpy)` |
| 5 | **Spread Analysis** | Liquidity monitoring | `AVG(ask - bid) GROUP BY symbol` |
| 6 | **Event Impact** | NFP/CPI reactions | `WHERE timestamp BETWEEN event-15min AND event+1H` |
| 7 | **Liquidity Zones** | Volume clusters | `NTILE(4) OVER(ORDER BY volume)` |
| 8 | **Outlier Detection** | Data quality checks | `WHERE price > 3*STDDEV() OVER()` |
| 9 | **Gap Analysis** | Weekend openings | `LAG(close) OVER() - open` |
| 10 | **Rolling Sharpe** | Strategy performance | `AVG(return)/STDDEV(return) OVER()` |
---
### **3. SME-Level Documentation Template**
**For each pattern**, document:
1. **Business Purpose**: *"Identify optimal trading hours by comparing volatility across sessions"*
2. **Technical Implementation**:
```sql
SELECT
EXTRACT(HOUR FROM timestamp) AS hour,
STDDEV((bid+ask)/2) AS volatility
FROM ticks
WHERE symbol = 'EUR/USD'
GROUP BY hour
ORDER BY volatility DESC
```
3. **Performance Considerations**: *"Add composite index on (symbol, timestamp) for 100x speedup"*
4. **Edge Cases**: *"Exclude holidays where volatility is artificially low"*
---
### **4. Drills to Achieve Mastery**
#### **Daily Challenge (15 mins/day)**
- **Day 1**: Generate 1H candles with OHLC + volume
- **Day 2**: Calculate 30-period rolling correlation between EUR/USD and GBP/USD
- **Day 3**: Find days with spread > 2x 30-day average
- **Day 4**: Compare pre/post-FOMC volatility
- **Day 5**: Optimize a slow query using EXPLAIN ANALYZE
#### **Weekly Project**
- Build a **volatility surface** showing:
```sql
SELECT
symbol,
DATE_TRUNC('hour', timestamp) AS hour,
STDDEV((bid+ask)/2) AS vol,
AVG(ask-bid) AS spread
FROM ticks
GROUP BY symbol, hour
```
---
### **5. Forensic Analysis Checklist**
When reviewing any forex query, ask:
1. **Time Handling**:
- ✅ Timestamps in UTC?
- ✅ Correct timezone conversions?
2. **Spread Awareness**:
- ✅ Using (bid+ask)/2 for mid-price?
- ✅ Calculating raw spread metrics?
3. **Rolling vs Static**:
- ✅ Using window functions where appropriate?
4. **Performance**:
- ✅ Indexes on (symbol, timestamp)?
- ✅ Avoiding full table scans?
---
### **6. Pro-Grade Resources**
1. **Dukascopy Tick Data**: Real-world practice dataset
2. **PostgreSQL Window Functions Docs**: Master the OVER() clause
3. **Forex Economic Calendar**: For event impact studies
---
### **Key Mindset Shifts**
1. **From**: "I need to learn all SQL functions"
**To**: "I need to master time-series patterns for bid/ask data"
2. **From**: "Queries must return perfect results"
**To**: "Queries must be fast enough for real-time decisions"
3. **From**: "Document after writing"
**To**: "Document patterns before implementation"
---
**Next Step**: Pick **one** pattern from the 10 above. I'll provide:
1. Detailed breakdown
2. Common mistakes
3. Optimization techniques
4. Forensic analysis questions
Which pattern would you like to deep-dive into first? (Recommend starting with **Time Bucketing** or **Rolling Volatility**)
---
Heres the **20% of SQL skills that will deliver 80% of your forex data analysis needs**, structured as a focused roadmap:
---