vending_data_intelligence_report/CONTEXT_HANDOVER_20251211_v2.md

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

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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.

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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):

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

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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

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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

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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?

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Test Command

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

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Success Criteria

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