notion-performance-tuning

# Notion Performance Tuning ## Overview Optimize Notion API performance by minimizing API calls, caching responses with TTL-based invalidation, batching block appends, parallelizing requests within rate limits, selecting only needed properties, and implementing incremental sync patterns. Target latency benchmarks: Database Query p50=150ms, Page Create p50=200ms, Search p50=300ms. ## Prerequisites - `@notionhq/client` installed (`npm install @notionhq/client`) - `p-queue` for rate-limited parallelism (`npm install p-queue`) - `lru-cache` for TTL-based caching (`npm install lru-cache`) - Understanding of your access patterns (read-heavy vs write-heavy) - Optional: Redis or `ioredis` for distributed caching across instances ## Instructions ### Step 1: Minimize API Calls and Reduce Payload Avoid N+1 query patterns. Use `page_size: 100` (the maximum) to reduce pagination requests. Select only the properties you need in database queries to shrink response payloads. ```typescript import { Client } from '@notionhq/client'; const notion = new Client({ auth: process.env.NOTION_TOKEN }); // BAD: N+1 pattern — fetching content for every page individually async function fetchAllBad(dbId: string) { const pages = await notion.databases.query({ database_id: dbId }); for (const page of pages.results) { // Each iteration is a separate API call — O(n) requests const content = await notion.blocks.children.list({ block_id: page.id }); } } // GOOD: Use filter_properties to s...