mapbox-web-performance-patterns
Performance optimization patterns for Mapbox GL JS web applications. Covers initialization waterfalls, bundle size, rendering performance, memory management, and web optimization. Prioritized by impact on user experience.
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name: mapbox-web-performance-patterns description: Performance optimization patterns for Mapbox GL JS web applications. Covers initialization waterfalls, bundle size, rendering performance, memory management, and web optimization. Prioritized by impact on user experience.
Mapbox Performance Patterns Skill
This skill provides performance optimization guidance for building fast, efficient Mapbox applications. Patterns are prioritized by impact on user experience, starting with the most critical improvements.
Performance philosophy: These aren't micro-optimizations. They show up as waiting time, jank, and repeat costs that hit every user session.
Priority Levels
Performance issues are prioritized by their impact on user experience:
- 🔴 Critical (Fix First): Directly causes slow initial load or visible jank
- 🟡 High Impact: Noticeable delays or increased resource usage
- 🟢 Optimization: Incremental improvements for polish
🔴 Critical: Eliminate Initialization Waterfalls
Problem: Sequential loading creates cascading delays where each resource waits for the previous one.
Note: Modern bundlers (Vite, Webpack, etc.) and ESM dynamic imports automatically handle code splitting and library loading. The primary waterfall to eliminate is data loading - fetching map data sequentially instead of in parallel with map initialization.
Anti-Pattern: Sequential Data Loading
// ❌ BAD: Data loads AFTER map initializes
async function initMap() {
const map = new mapboxgl.Map({
container: 'map',
accessToken: MAPBOX_TOKEN,
style: 'mapbox://styles/mapbox/streets-v12'
});
// Wait for map to load, THEN fetch data
map.on('load', async () => {
const data = await fetch('/api/data'); // Waterfall!
map.addSource('data', { type: 'geojson', data: await data.json() });
});
}
Timeline: Map init (0.5s) → Data fetch (1s) = 1.5s total
Solution: Parallel Data Loading
// ✅ GOOD: Data fetch starts immediately
async function initMap() {
// Start data fetch immediately (don't wait for map)
const dataPromise = fetch('/api/data').then((r) => r.json());
const map = new mapboxgl.Map({
container: 'map',
accessToken: MAPBOX_TOKEN,
style: 'mapbox://styles/mapbox/streets-v12'
});
// Data is ready when map loads
map.on('load', async () => {
const data = await dataPromise;
map.addSource('data', { type: 'geojson', data });
map.addLayer({
id: 'data-layer',
type: 'circle',
source: 'data'
});
});
}
Timeline: Max(map init, data fetch) = ~1s total
Set Precise Initial Viewport
// ✅ Set exact center/zoom so the map fetches the right tiles immediately
const map = new mapboxgl.Map({
container: 'map',
style: 'mapbox://styles/mapbox/streets-v12',
center: [-122.4194, 37.7749],
zoom: 13
});
// Use 'idle' to know when the initial viewport is fully rendered
// (all tiles, sprites, and other resources are loaded; no transitions in progress)
map.once('idle', () => {
console.log('Initial viewport fully rendered');
});
If you know the exact area users will see first, setting center and zoom upfront avoids the map starting at a default view and then panning/zooming to the target, which wastes tile fetches.
Defer Non-Critical Features
// ✅ Load critical features first, defer others
const map = new mapboxgl.Map({
/* config */
});
map.on('load', () => {
// 1. Add critical layers immediately
addCriticalLayers(map);
// 2. Defer secondary features
// Note: Standard style 3D buildings can be toggled via config:
// map.setConfigProperty('basemap', 'show3dObjects', false);
requestIdleCallback(
() => {
addTerrain(map);
addCustom3DLayers(map); // For classic styles with custom fill-extrusion layers
},
{ timeout: 2000 }
);
// 3. Defer analytics and non-visual features
setTimeout(() => {
initializeAnalytics(map);
}, 3000);
});
Impact: Significant reduction in time-to-interactive, especially when deferring terrain and 3D layers
🔴 Critical: Optimize Initial Bundle Size
Problem: Large bundles delay time-to-interactive on slow networks.
Note: Modern bundlers (Vite, Webpack, etc.) automatically handle code splitting for framework-based applications. The guidance below is most relevant for optimizing what gets bundled and when.
Style JSON Bundle Impact
// ❌ BAD: Inline massive style JSON (can be 500+ KB)
const style = {
version: 8,
sources: {
/* 100s of lines */
},
layers: [
/* 100s of layers */
]
};
// ✅ GOOD: Reference Mapbox-hosted styles
const map = new mapboxgl.Map({
style: 'mapbox://styles/mapbox/streets-v12' // Fetched on demand
});
// ✅ OR: Store large custom styles externally
const map = new mapboxgl.Map({
style: '/styles/custom-style.json' // Loaded separately
});
Impact: Reduces initial bundle by 30-50% when moving from inlined to hosted styles
🟡 High Impact: Optimize Marker Count
Problem: Too many markers causes slow rendering and interaction lag.
Performance Thresholds
- < 100 markers: HTML markers OK (Marker class)
- 100-10,000 markers: Use symbol layers (GPU-accelerated)
- 10,000+ markers: Clustering recommended
- 100,000+ markers: Vector tiles with server-side clustering
Anti-Pattern: Thousands of HTML Markers
// ❌ BAD: 5,000 HTML markers = 5+ second render, janky pan/zoom
restaurants.forEach((restaurant) => {
const marker = new mapboxgl.Marker()
.setLngLat([restaurant.lng, restaurant.lat])
.setPopup(new mapboxgl.Popup().setHTML(restaurant.name))
.addTo(map);
});
Result: 5,000 DOM elements, slow interactions, high memory
Solution: Use Symbol Layers (GeoJSON)
// ✅ GOOD: GPU-accelerated rendering, smooth at 10,000+ features
map.addSource('restaurants', {
type: 'geojson',
data: {
type: 'FeatureCollection',
features: restaurants.map((r) => ({
type: 'Feature',
geometry: { type: 'Point', coordinates: [r.lng, r.lat] },
properties: { name: r.name, type: r.type }
}))
}
});
map.addLayer({
id: 'restaurants',
type: 'symbol',
source: 'restaurants',
layout: {
'icon-image': 'restaurant',
'icon-size': 0.8,
'text-field': ['get', 'name'],
'text-size': 12,
'text-offset': [0, 1.5],
'text-anchor': 'top'
}
});
// Click handler (one listener for all features)
map.on('click', 'restaurants', (e) => {
const feature = e.features[0];
new mapboxgl.Popup().setLngLat(feature.geometry.coordinates).setHTML(feature.properties.name).addTo(map);
});
Performance: 10,000 features render in <100ms
Solution: Clustering for High Density
// ✅ GOOD: 50,000 markers → ~500 clusters at low zoom
map.addSource('restaurants', {
type: 'geojson',
data: restaurantsGeoJSON,
cluster: true,
clusterMaxZoom: 14, // Stop clustering at zoom 15
clusterRadius: 50 // Radius relative to tile dimensions (512 = full tile width)
});
// Cluster circle layer
map.addLayer({
id: 'clusters',
type: 'circle',
source: 'restaurants',
filter: ['has', 'point_count'],
paint: {
'circle-color': ['step', ['get', 'point_count'], '#51bbd6', 100, '#f1f075', 750, '#f28cb1'],
'circle-radius': ['step', ['get', 'point_count'], 20, 100, 30, 750, 40]
}
});
// Cluster count label
map.addLayer({
id: 'cluster-count',
type: 'symbol',
source: 'restaurants',
filter: ['has', 'point_count'],
layout: {
'text-field': '{point_count_abbreviated}',
'text-size': 12
}
});
// Individual point layer
map.addLayer({
id: 'unclustered-point',
type: 'circle',
source: 'restaurants',
filter: ['!', ['has', 'point_count']],
paint: {
'circle-color': '#11b4da',
'circle-radius': 6
}
});
Impact: 50,000 markers at 60 FPS with smooth interaction
🟡 High Impact: Optimize Data Loading Strategy
Problem: Loading all data upfront wastes bandwidth and slows initial render.
GeoJSON vs Vector Tiles Decision Matrix
| Scenario | Use GeoJSON | Use Vector Tiles | | ------------------------- | ----------- | ---------------- | | < 5 MB data | Yes | No | | 5-20 MB data | Consider | Yes | | > 20 MB data | No | Yes | | Data changes frequently | Yes | No | | Static data, global scale | No | Yes | | Need server-side updates | No | Yes |
Viewport-Based Loading (GeoJSON)
Note: This pattern is applicable when hosting GeoJSON data locally or on external servers. Mapbox-hosted data sources are already optimized for viewport-based loading.
// ✅ Only load data in current viewport
async function loadVisibleData(map) {
const bounds = map.getBounds();
const bbox = [bounds.getWest(), bounds.getSouth(), bounds.getEast(), bounds.getNorth()].join(',');
const data = await fetch(`/api/data?bbox=${bbox}&zoom=${map.getZoom()}`);
map.getSource('data').setData(await data.json());
}
// Update on viewport change (with debounce)
let timeout;
map.on('moveend', () => {
clearTimeout(timeout);
timeout = setTimeout(() => loadVisibleData(map), 300);
});
Important: setData() triggers a full re-parse of the GeoJSON in a web worker. For small datasets updated frequently, consider using source.updateData() (requires dynamic: true on the source) for partial updates. For large datasets, switch to vector tiles.
Progressive Data Loading
Note: This pattern is applicable when hosting GeoJSON data locally or on external servers.
// ✅ Load basic data first, add details progressively
async function loadDataProgressive(map) {
// 1. Load simplified data first (low-res)
const simplified = await fetch('/api/data?detail=low');
map.addSource('data', {
type: 'geojson',
data: await simplified.json()
});
addLayers(map);
// 2. Load full detail in background
const detailed = await fetch('/api/data?detail=high');
map.getSource('data').setData(await detailed.json());
}
Vector Tiles for Large Datasets
Note: The minzoom/maxzoom optimization shown below is primarily for self-hosted vector tilesets. Mapbox-hosted tilesets have built-in optimization via Mapbox Tiling Service (MTS) recipes that handle zoom-level optimizations automatically.
// ✅ Server generates tiles, client loads only visible area (self-hosted tilesets)
map.addSource('large-dataset', {
type: 'vector',
tiles: ['https://api.example.com/tiles/{z}/{x}/{y}.pbf'],
minzoom: 0,
maxzoom: 14
});
map.addLayer({
id: 'large-dataset-layer',
type: 'fill',
source: 'large-dataset',
'source-layer': 'data', // Layer name in .pbf
paint: {
'fill-color': '#088',
'fill-opacity': 0.6
}
});
Impact: 10 MB dataset reduced to ~500 KB per viewport load
🟡 High Impact: Optimize Map Interactions
Problem: Unthrottled event handlers cause performance degradation.
Anti-Pattern: Expensive Operations on Every Event
// ❌ BAD: Runs ~60 times per second during pan (once per render frame)
map.on('move', () => {
updateVisibleFeatures(); // Expensive query
fetchDataFromAPI(); // Network request
updateUI(); // DOM manipulation
});
Solution: Debounce/Throttle Events
// ✅ GOOD: Throttle during interaction, finalize on idle
let throttleTimeout;
// Lightweight updates during move (throttled)
map.on('move', () => {
if (throttleTimeout) return;
throttleTimeout = setTimeout(() => {
updateMapCenter(); // Cheap update
throttleTimeout = null;
}, 100);
});
// Expensive operations after interaction stops
map.on('moveend', () => {
updateVisibleFeatures();
fetchDataFromAPI();
updateUI();
});
Optimize Feature Queries
// ❌ BAD: Query all features (expensive with many layers)
map.on('click', (e) => {
const features = map.queryRenderedFeatures(e.point);
console.log(features); // Could be 100+ features from all layers
});
// ✅ GOOD: Query specific layers only
map.on('click', (e) => {
const features = map.queryRenderedFeatures(e.point, {
layers: ['restaurants', 'shops'] // Only query these layers
});
if (features.length > 0) {
showPopup(features[0]);
}
});
// ✅ For touch targets or fuzzy clicks: Use a bounding box
map.on('click', (e) => {
const bbox = [
[e.point.x - 5, e.point.y - 5],
[e.point.x + 5, e.point.y + 5]
];
const features = map.queryRenderedFeatures(bbox, {
layers: ['restaurants'],
filter: ['==', ['get', 'type'], 'pizza'] // Further narrow results
});
});
Batch DOM Updates
// ❌ BAD: Update DOM for every feature
map.on('mousemove', 'restaurants', (e) => {
e.features.forEach((feature) => {
document.getElementById(feature.id).classList.add('highlight');
});
});
// ✅ GOOD: Batch updates with requestAnimationFrame
let pendingUpdates = new Set();
let rafScheduled = false;
map.on('mousemove', 'restaurants', (e) => {
e.features.forEach((f) => pendingUpdates.add(f.id));
if (!rafScheduled) {
rafScheduled = true;
requestAnimationFrame(() => {
pendingUpdates.forEach((id) => {
document.getElementById(id).classList.add('highlight');
});
pendingUpdates.clear();
rafScheduled = false;
});
}
});
Impact: 60 FPS maintained during interaction vs 15-20 FPS without optimization
🟡 High Impact: Memory Management
Problem: Memory leaks cause browser tabs to become unresponsive over time. In SPAs that create/destroy map instances, this is a common production issue.
Always Clean Up Map Resources
// ✅ Essential cleanup pattern
function cleanupMap(map) {
if (!map) return;
// 1. Remove event listeners
map.off('load', handleLoad);
map.off('move', handleMove);
// 2. Remove layers (if adding/removing dynamically)
if (map.getLayer('dynamic-layer')) {
map.removeLayer('dynamic-layer');
}
// 3. Remove sources (if adding/removing dynamically)
if (map.getSource('dynamic-source')) {
map.removeSource('dynamic-source');
}
// 4. Remove controls
map.removeControl(navigationControl);
// 5. CRITICAL: Remove map instance
map.remove();
}
// React example
useEffect(() => {
const map = new mapboxgl.Map({
/* config */
});
return () => {
cleanupMap(map); // Called on unmount
};
}, []);
Clean Up Popups and Markers
// ❌ BAD: Creates new popup on every click (memory leak)
map.on('click', 'restaurants', (e) => {
new mapboxgl.Popup().setLngLat(e.lngLat).setHTML(e.features[0].properties.name).addTo(map);
// Popup never removed!
});
// ✅ GOOD: Reuse single popup instance
let popup = new mapboxgl.Popup({ closeOnClick: true });
map.on('click', 'restaurants', (e) => {
popup.setLngLat(e.lngLat).setHTML(e.features[0].properties.name).addTo(map);
// Previous popup content replaced, no leak
});
// Cleanup
function cleanup() {
popup.remove();
popup = null;
}
Use Feature State Instead of New Layers
// ❌ BAD: Create new layer for hover (memory overhead, causes re-render)
let hoveredFeatureId = null;
map.on('mousemove', 'restaurants', (e) => {
if (map.getLayer('hover-layer')) {
map.removeLayer('hover-layer');
}
map.addLayer({
id: 'hover-layer',
type: 'circle',
source: 'restaurants',
filter: ['==', ['id'], e.features[0].id],
paint: { 'circle-color': 'yellow' }
});
});
// ✅ GOOD: Use feature state (efficient, no layer creation)
map.on('mousemove', 'restaurants', (e) => {
if (e.features.length > 0) {
// Remove previous hover state
if (hoveredFeatureId !== null) {
map.setFeatureState({ source: 'restaurants', id: hoveredFeatureId }, { hover: false });
}
// Set new hover state
hoveredFeatureId = e.features[0].id;
map.setFeatureState({ source: 'restaurants', id: hoveredFeatureId }, { hover: true });
}
});
// Style uses feature state
map.addLayer({
id: 'restaurants',
type: 'circle',
source: 'restaurants',
paint: {
'circle-color': [
'case',
['boolean', ['feature-state', 'hover'], false],
'#ffff00', // Yellow when hover
'#0000ff' // Blue otherwise
]
}
});
Note: Feature state requires features to have IDs. Use generateId: true on the GeoJSON source to auto-assign IDs, or use promoteId to use an existing property as the feature ID.
Impact: Prevents memory growth from continuous layer churn over long sessions
🟢 Optimization: Mobile Performance
Problem: Mobile devices have limited resources (CPU, GPU, memory, battery).
Mobile-Specific Optimizations
// Detect mobile device
const isMobile = /iPhone|iPad|iPod|Android/i.test(navigator.userAgent);
const map = new mapboxgl.Map({
container: 'map',
style: 'mapbox://styles/mapbox/streets-v12',
// Mobile optimizations
...(isMobile && {
// Limit max zoom to reduce tile fetching at extreme zoom levels
maxZoom: 18,
// fadeDuration controls symbol collision fade animation only
// Reducing it makes label transitions snappier
fadeDuration: 0
})
});
// Load simpler layers on mobile
map.on('load', () => {
if (isMobile) {
// Circle layers are cheaper than symbol layers (no collision detection,
// no texture atlas, no text shaping)
map.addLayer({
id: 'markers-mobile',
type: 'circle',
source: 'data',
paint: {
'circle-radius': 8,
'circle-color': '#007cbf'
}
});
} else {
// Rich desktop rendering with icons and labels
map.addLayer({
id: 'markers-desktop',
type: 'symbol',
source: 'data',
layout: {
'icon-image': 'marker',
'icon-size': 1,
'text-field': ['get', 'name'],
'text-size': 12,
'text-offset': [0, 1.5]
}
});
}
});
Touch Interaction Optimization
// ✅ Simplify touch gestures
map.touchZoomRotate.disableRotation(); // Disable rotation (simpler gestures, fewer accidental rotations)
// Debounce expensive operations during touch
let touchTimeout;
map.on('touchmove', () => {
if (touchTimeout) clearTimeout(touchTimeout);
touchTimeout = setTimeout(() => {
updateVisibleData();
}, 500); // Wait for touch to settle
});
Performance-Sensitive Constructor Options
// These options have real GPU/performance costs -- only enable when needed
const map = new mapboxgl.Map({
container: 'map',
style: 'mapbox://styles/mapbox/streets-v12',
// Default false -- only set true if you need map.getCanvas().toDataURL()
// Costs: prevents GPU buffer optimization
preserveDrawingBuffer: false,
// Default false -- only set true if you need smooth diagonal lines
// Costs: enables MSAA which increases GPU memory and fill cost
antialias: false
});
🟢 Optimization: Layer and Style Performance
Consolidate Layers
// ❌ BAD: 20 separate layers for restaurant types
restaurantTypes.forEach((type) => {
map.addLayer({
id: `restaurants-${type}`,
type: 'symbol',
source: 'restaurants',
filter: ['==', ['get', 'type'], type],
layout: { 'icon-image': `${type}-icon` }
});
});
// ✅ GOOD: Single layer with data-driven styling
map.addLayer({
id: 'restaurants',
type: 'symbol',
source: 'restaurants',
layout: {
'icon-image': [
'match',
['get', 'type'],
'pizza',
'pizza-icon',
'burger',
'burger-icon',
'sushi',
'sushi-icon',
'default-icon' // fallback
]
}
});
Impact: Fewer layers means less rendering overhead. Each layer has fixed per-layer cost regardless of feature count.
Simplify Expressions for Large Datasets
For datasets with 100,000+ features, simpler expressions reduce per-feature evaluation cost. For smaller datasets, the expression engine is fast enough that this won't be noticeable.
// Zoom-dependent paint properties MUST use step or interpolate, not comparisons
// ❌ WRONG: Cannot use comparison operators on ['zoom'] in paint properties
// paint: { 'fill-extrusion-height': ['case', ['>', ['zoom'], 16], ...] }
// ✅ CORRECT: Use step for discrete zoom breakpoints
map.addLayer({
id: 'buildings',
type: 'fill-extrusion',
source: 'buildings',
paint: {
'fill-extrusion-color': ['interpolate', ['linear'], ['get', 'height'], 0, '#dedede', 50, '#a0a0a0', 100, '#606060'],
'fill-extrusion-height': [
'step',
['zoom'],
['get', 'height'], // Default: use raw height
16,
['*', ['get', 'height'], 1.5] // At zoom 16+: scale up
]
}
});
For very large GeoJSON datasets, pre-computing static property derivations (like color categories) into the source data can reduce per-feature expression work:
// ✅ Pre-compute STATIC derivations for large datasets (100K+ features)
const buildingsWithColor = {
type: 'FeatureCollection',
features: buildings.features.map((f) => ({
...f,
properties: {
...f.properties,
heightColor: getColorForHeight(f.properties.height) // Pre-computed once
}
}))
};
map.addSource('buildings', { type: 'geojson', data: buildingsWithColor });
map.addLayer({
id: 'buildings',
type: 'fill-extrusion',
source: 'buildings',
paint: {
'fill-extrusion-color': ['get', 'heightColor'], // Simple property lookup
'fill-extrusion-height': ['get', 'height']
}
});
Use Zoom-Based Layer Visibility
// ✅ Only render layers at appropriate zoom levels
map.addLayer({
id: 'building-details',
type: 'fill',
source: 'buildings',
minzoom: 15, // Render at zoom 15 and above
paint: { 'fill-color': '#aaa' }
});
map.addLayer({
id: 'poi-labels',
type: 'symbol',
source: 'pois',
minzoom: 12, // Hide at low zoom levels where labels would overlap heavily
layout: {
'text-field': ['get', 'name'],
visibility: 'visible'
}
});
Note: minzoom is inclusive (layer visible at that zoom), maxzoom is exclusive (layer hidden at that zoom). A layer with maxzoom: 16 is visible up to but not including zoom 16.
Impact: Reduces GPU work at zoom levels where layers aren't useful
Summary: Performance Checklist
When building a Mapbox application, verify these optimizations in order:
🔴 Critical (Do First)
- [ ] Load map library and data in parallel (eliminate waterfalls)
- [ ] Use dynamic imports for map code (reduce initial bundle)
- [ ] Defer non-critical features (terrain, custom 3D layers, analytics)
- [ ] Use symbol layers for > 100 markers (not HTML markers)
- [ ] Implement viewport-based data loading for large datasets
🟡 High Impact
- [ ] Debounce/throttle map event handlers
- [ ] Optimize queryRenderedFeatures with layers filter and bounding box
- [ ] Use GeoJSON for < 5 MB, vector tiles for > 20 MB
- [ ] Always call map.remove() on cleanup in SPAs
- [ ] Reuse popup instances (don't create on every interaction)
- [ ] Use feature state instead of dynamic layers for hover/selection
🟢 Optimization
- [ ] Consolidate multiple layers with data-driven styling
- [ ] Add mobile-specific optimizations (circle layers, disabled rotation)
- [ ] Set minzoom/maxzoom on layers to avoid rendering at irrelevant zoom levels
- [ ] Avoid enabling preserveDrawingBuffer or antialias unless needed
Measurement
// Measure initial load time
console.time('map-load');
map.on('load', () => {
console.timeEnd('map-load');
// isStyleLoaded() returns true when style, sources, tiles, sprites, and models are all loaded
console.log('Style loaded:', map.isStyleLoaded());
});
// Monitor frame rate
let frameCount = 0;
map.on('render', () => frameCount++);
setInterval(() => {
console.log('FPS:', frameCount);
frameCount = 0;
}, 1000);
// Check memory usage (Chrome DevTools -> Performance -> Memory)
Target metrics:
- Time to Interactive: < 2 seconds on 3G
- Frame Rate: 60 FPS during pan/zoom
- Memory Growth: < 10 MB per hour of usage
- Bundle Size: < 500 KB initial (map lazy-loaded)
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