# TL;DR: JSONB Generation Benchmark Results

## Bottom Line

**Your current `jsonb_build_object()` approach is already optimal. No changes needed.**

## Benchmark Results

### Paginated Queries (90% of GraphQL workload)

```
jsonb_build_object:  22.2 TPS ✅ FASTEST (baseline)
to_jsonb:            14.6 TPS ❌ 34% slower
row_to_json:         11.7 TPS ❌ 47% slower
```

### Filtered Queries (WHERE clauses)

```
jsonb_build_object:  474.9 TPS ✅ FASTEST
row_to_json:         473.0 TPS ≈  similar
to_jsonb:            430.9 TPS ⚠️  9% slower
```

### Full Table Scans (rare in GraphQL)

```
to_jsonb:            8.2 TPS ✅ FASTEST (+24%)
jsonb_build_object:  6.6 TPS    baseline
row_to_json:         5.0 TPS ❌ 25% slower
```

## Key Insight

**`jsonb_build_object()` is faster because PostgreSQL applies filters BEFORE building JSONB.**

```sql
-- Your current approach (FAST for paginated/filtered queries)
SELECT jsonb_build_object('id', id, 'name', name)
FROM users WHERE is_active = true LIMIT 100;
-- Execution: Filter 10,000 → 100 rows → Build JSONB for 100 rows

-- to_jsonb alternative (SLOW for paginated/filtered queries)
SELECT to_jsonb(users) FROM users
WHERE is_active = true LIMIT 100;
-- Execution: Build JSONB for 10,000 rows → Filter → Return 100 rows
```

## Recommendations

1. **✅ Keep `jsonb_build_object()` in views** - it's already optimal for real-world usage
2. **✅ Use `to_jsonb()` for Trinity GENERATED columns** - simpler for pre-computed JSONB
3. **✅ Use your existing `field_limit_threshold`** - smart optimization for many fields
4. **🎯 Focus optimization on Rust path** - eliminate Python parsing overhead (see QUERY_EXECUTION_PATH_ANALYSIS.md)

## Field Selection Question Answered

> "What is the most efficient way to just send back the selected fields from the query?"

**Your current approach IS the most efficient:**
- PostgreSQL selects only needed fields with `jsonb_build_object()`
- Rust transforms to camelCase
- For queries with >50 fields, switch to full `data` column + Rust filtering

The slowest part is NOT PostgreSQL JSONB generation - it's the Python parsing after Rust transformation.

## Where the Real Performance Gains Are

From your QUERY_EXECUTION_PATH_ANALYSIS.md, optimize these instead:

1. **Layer 4: JSON Parsing** ❌ `json.loads()` after Rust transform
2. **Layer 5: Type Instantiation** ❌ `User.from_dict()` in resolver
3. **Layer 6: GraphQL Serialization** ❌ Python object → JSON again

**Solution:** Return `RawJSONResult` directly to HTTP layer, skip Python objects entirely.

---

**Benchmark files:**
- Full results: `results/benchmark_20251016_233008.md`
- Detailed analysis: `ANALYSIS.md`
- Setup script: `00_setup.sql`
- Run again: `./run_benchmark.sh [dbname]`
