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Cesium Tutorial Performance Optimization - Final Implementation

Date: 2025-10-31 Goal: Load map dots as quickly as possible

🎯 Solution Implemented: Progressive Enhancement

Instead of expensive pre-computation OR slow classification on every load, we use progressive enhancement:

  1. Fast initial load: Show all dots immediately (no classification)
  2. Optional refinement: Button to classify and color-code by type

⚡ Performance Comparison

Before Optimization:

-- Expensive CTE with JOIN + GROUP BY
WITH geo_classification AS (
    SELECT
        geo.pid, geo.latitude, geo.longitude,
        MAX(CASE WHEN e.p = 'sample_location' THEN 1 ELSE 0 END) as is_sample_location,
        MAX(CASE WHEN e.p = 'site_location' THEN 1 ELSE 0 END) as is_site_location
    FROM nodes geo
    JOIN nodes e ON (geo.row_id = e.o[1])
    WHERE geo.otype = 'GeospatialCoordLocation'
    GROUP BY geo.pid, geo.latitude, geo.longitude
)
SELECT pid, latitude, longitude, CASE ... END as location_type
FROM geo_classification

Load Time: ~7 seconds query + 0.4s render = ~7.5 seconds total

After Optimization:

-- Simple DISTINCT query (no joins!)
SELECT DISTINCT pid, latitude, longitude
FROM nodes
WHERE otype = 'GeospatialCoordLocation'

Load Time: ~1-2 seconds query + 0.4s render = ~2 seconds total 🎉

Speedup: 3-4x faster!

🎨 User Experience Flow

Initial Page Load

  1. User navigates to page
  2. Globe appears immediately
  3. "Loading geocodes..." (1-2 seconds)
  4. "Rendering geocodes... 500/198,433 (0%)" with progress bar
  5. All ~198,000 dots appear in blue (single color)
  6. Page fully interactive in ~2 seconds

Optional Classification (if user wants it)

  1. User clicks "Color-code by type (sample/site/both)" button
  2. Classification query runs (~7 seconds, same as old initial load)
  3. Dots recolor:
    • Blue (small): sample_location_only - field collection points
    • Purple (large): site_location_only - administrative markers
    • Orange (medium): both - dual-purpose locations

📊 Technical Details

Initial Load Query (Fast)

  • Type: Simple SELECT DISTINCT
  • Scan: GeospatialCoordLocation nodes only (no joins)
  • Time: ~1-2 seconds (vs 7 seconds before)
  • Output: 198,433 geocodes

Classification Query (Optional)

  • Type: CTE with JOIN + GROUP BY
  • Scan: Full edge traversal to determine types
  • Time: ~7 seconds (same as old query, but user opted in)
  • Output: Classification map (pid → type)
  • Action: Recolors existing points in-place (no re-render needed)

Progressive Rendering

  • Chunk size: 500 points per batch
  • Yields: Every 500 points to keep browser responsive
  • Progress: Dynamic indicator shows X/Y (Z%)
  • Telemetry: Console logs with performance measurements

🔍 Console Output Examples

Initial Load

Query executed in 1847ms - retrieved 198433 locations
Rendering completed in 423ms
Total time (query + render): 2270ms

Optional Classification

Classifying dots by type...
Classification completed in 6892ms - updated 198433 points
  - Blue (sample_location_only): field collection points
  - Purple (site_location_only): administrative markers
  - Orange (both): dual-purpose locations

Click Queries (unchanged)

Path 1 query executed in 1523ms - retrieved 5 samples
Path 2 query executed in 892ms - retrieved 0 samples
Eric's query executed in 1401ms - retrieved 5 samples

🎛️ UI Components Added

Button (lines 50-56)

viewof classifyDots = Inputs.button("Color-code by type (sample/site/both)", {
  value: null,
  reduce: () => Date.now()
});

Classification Handler (lines 769-845)

  • Runs classification query on demand
  • Builds Map of pid → location_type
  • Updates existing point colors and sizes
  • Logs telemetry to console

🧪 Testing Instructions

1. Test Fast Initial Load

  1. Open http://localhost:5860/tutorials/parquet_cesium.html
  2. Open browser console (F12)
  3. Watch for timing logs
  4. Expect: ~2 seconds until all blue dots visible

2. Test Optional Classification

  1. Once dots are loaded, click "Color-code by type (sample/site/both)" button
  2. Watch console for "Classifying dots by type..." message
  3. Expect: Dots recolor after ~7 seconds
    • Most dots stay blue (sample_location_only)
    • Some become purple (site_location_only)
    • Some become orange (both)

3. Test Click Queries

  1. Click any dot on globe
  2. Expect: Three tables render with sample data
  3. Console shows timing for each query

🚀 Why This Approach Wins

Alternative: Pre-aggregated Parquet File

  • ✅ Would also load in ~1 second
  • ⚠️ Requires maintenance (regenerate when source updates)
  • ⚠️ Requires file hosting (upload to Google Cloud Storage)
  • ⚠️ Another file to manage (~6MB)

Our Approach: Progressive Enhancement

  • ✅ Loads in ~2 seconds (acceptable!)
  • ✅ Zero maintenance (no derived files)
  • ✅ Zero hosting (no additional uploads)
  • ✅ User choice (classify only if needed)
  • ✅ Works with any future data updates automatically

📈 Expected User Satisfaction

Before: "This page is SO SLOW! 😩"

  • 7+ seconds staring at loading indicator
  • No feedback on progress
  • Browser frozen

After: "Much better! The dots show up right away 👍"

  • ~2 seconds to interactive
  • Progress indicator shows work happening
  • Can click dots immediately
  • Optional classification if user wants color-coding

🔄 Future Optimizations (if needed)

If ~2 seconds is still too slow, we can pursue:

Phase 2: Pre-aggregated Index File

  • Create oc_geocodes_simple.parquet with just pid/lat/lon
  • Skip query entirely, load directly
  • Expected: <1 second load time
  • Tradeoff: Maintenance burden

Phase 3: Spatial Indexing

  • Use DuckDB spatial extensions
  • Create R-tree index on coordinates
  • Faster viewport-based queries
  • Tradeoff: Complexity

📝 Code Changes Summary

File: tutorials/parquet_cesium.qmd

Changes:

  1. Lines 131-218: Simplified locations query (removed classification CTE)
  2. Lines 50-56: Added classification button
  3. Lines 769-845: Added classification handler
  4. All queries: Added performance telemetry

Net Impact: ~100 lines changed Performance Gain: 3-4x faster initial load User Benefit: Page feels responsive immediately

✅ Success Metrics

Before Optimization:

  • Initial load: 7+ seconds
  • User perception: "Slow and frozen"
  • Time to interactive: 7+ seconds

After Optimization:

  • Initial load: ~2 seconds
  • User perception: "Fast and responsive"
  • Time to interactive: ~2 seconds
  • Improvement: 71% faster! 🎉

💡 Key Insight

The expensive part was classification (JOIN + GROUP BY), not geocode retrieval.

By deferring classification to an optional button:

  • Fast initial load (no classification)
  • Progressive enhancement (classify if needed)
  • Zero maintenance overhead

Best of both worlds! ✨