# Context Handover - Query Optimization (11 Dec 2025 - v2)

## Session Summary

This session accomplished:
1. ✅ Fixed VALOARE_ANTERIOARA NULL bug (used `sumar_executiv_yoy` directly)
2. ✅ Created unified "Dashboard Complet" sheet/page
3. ✅ Added PerformanceLogger for timing analysis
4. ✅ Fixed Excel formula error (`===` → `>>>`)
5. ✅ Removed redundant consolidated sheets/pages
6. ✅ Created PERFORMANCE_ANALYSIS.md with findings

## Critical Finding: SQL Queries Are The Bottleneck

**Total runtime: ~33 minutes**
- SQL Queries: 31 min (94%)
- Excel/PDF: 15 sec (1%)

### Top Slow Queries (all 60-130 seconds for tiny results):

| Query | Duration | Rows | Issue |
|-------|----------|------|-------|
| `clienti_sub_medie` | 130.63s | 100 | Uses complex views |
| `sumar_executiv_yoy` | 129.05s | 5 | YoY 24-month scan |
| `vanzari_lunare` | 129.90s | 25 | Monthly aggregation |
| `indicatori_agregati_venituri_yoy` | 129.31s | 3 | YoY comparison |

---

## Root Cause: Views vs Base Tables

The current queries use complex views like `fact_vfacturi2`, `fact_vfacturi_detalii`, `vnom_articole`, `vnom_parteneri`.

**These views likely contain:**
- Multiple nested JOINs
- Calculated columns
- No index utilization

**Solution:** Use base tables directly: `VANZARI`, `VANZARI_DETALII`, `NOM_PARTENERI`, etc.

---

## Example Optimization: CLIENTI_SUB_MEDIE

### Current Query (uses views - 130 seconds):
Located in `queries.py` around line 600-650.

### Optimized Query (uses base tables - should be <5 seconds):

```sql
WITH preturi_medii AS (
    SELECT
        d.id_articol,
        AVG(CASE WHEN d.pret_cu_tva = 1 THEN d.pret / (1 + d.proc_tvav/100) ELSE d.pret END) AS pret_mediu
    FROM VANZARI f
    JOIN VANZARI_DETALII d ON d.id_vanzare = f.id_vanzare
    WHERE f.sters = 0 AND d.sters = 0
      AND f.tip > 0 AND f.tip NOT IN (7, 8, 9, 24)
      AND f.data_act >= ADD_MONTHS(TRUNC(SYSDATE), -24)
      AND d.pret > 0
    GROUP BY d.id_articol
),
preturi_client AS (
    SELECT
        d.id_articol,
        f.id_part,
        p.denumire as client,
        AVG(CASE WHEN d.pret_cu_tva = 1 THEN d.pret / (1 + d.proc_tvav/100) ELSE d.pret END) AS pret_client,
        SUM(d.cantitate) AS cantitate_totala
    FROM VANZARI f
    JOIN VANZARI_DETALII d ON d.id_vanzare = f.id_vanzare
    JOIN NOM_PARTENERI P on f.id_part = p.id_part
    WHERE f.sters = 0 AND d.sters = 0
      AND f.tip > 0 AND f.tip NOT IN (7, 8, 9, 24)
      AND f.data_act >= ADD_MONTHS(TRUNC(SYSDATE), -24)
      AND d.pret > 0
    GROUP BY d.id_articol, f.id_part, p.denumire
)
SELECT
    a.denumire AS produs,
    pc.client,
    ROUND(pc.pret_client, 2) AS pret_platit,
    ROUND(pm.pret_mediu, 2) AS pret_mediu,
    ROUND((pm.pret_mediu - pc.pret_client) * 100.0 / pm.pret_mediu, 2) AS discount_vs_medie,
    pc.cantitate_totala
FROM preturi_client pc
JOIN preturi_medii pm ON pm.id_articol = pc.id_articol
JOIN vnom_articole a ON a.id_articol = pc.id_articol
WHERE pc.pret_client < pm.pret_mediu * 0.85
ORDER BY discount_vs_medie DESC
FETCH FIRST 100 ROWS ONLY
```

### Key Differences:
1. Uses `VANZARI` instead of `fact_vfacturi2`
2. Uses `VANZARI_DETALII` instead of `fact_vfacturi_detalii`
3. Uses `NOM_PARTENERI` instead of `vnom_parteneri`
4. Column names differ: `id_vanzare` vs `nrfactura`, `data_act` vs `data`
5. Direct JOIN on IDs instead of view abstractions

---

## Task for Next Session: Optimize All Slow Queries

### Priority 1 - Rewrite using base tables:
1. `clienti_sub_medie` (130s) - example above
2. `sumar_executiv` (130s)
3. `sumar_executiv_yoy` (129s)
4. `vanzari_lunare` (130s)
5. `indicatori_agregati_venituri_yoy` (129s)

### Priority 2 - YoY optimization:
- Pre-calculate previous year metrics in single CTE
- Avoid scanning same data twice

### Steps:
1. Read current query in `queries.py`
2. Identify view → base table mappings
3. Rewrite with base tables
4. Test performance improvement
5. Repeat for all slow queries

---

## Key Files

| File | Purpose |
|------|---------|
| `queries.py` | All SQL queries - constants like `CLIENTI_SUB_MEDIE` |
| `main.py` | Execution with PerformanceLogger |
| `PERFORMANCE_ANALYSIS.md` | Detailed timing analysis |

---

## Base Table → View Mapping (to discover)

Need to examine Oracle schema to find exact mappings:
- `VANZARI` → `fact_vfacturi2`?
- `VANZARI_DETALII` → `fact_vfacturi_detalii`?
- `NOM_PARTENERI` → `vnom_parteneri`?
- `NOM_ARTICOLE` → `vnom_articole`?

Column mappings:
- `id_vanzare` → `nrfactura`?
- `data_act` → `data`?
- `id_part` → `id_partener`?

---

## Test Command

```bash
cd /mnt/e/proiecte/vending/data_intelligence_report
.\run.bat
# Check output/performance_log.txt for timing
```

---

## Success Criteria

Reduce total query time from 31 minutes to <5 minutes by using base tables instead of views.