Skills Development Hex API Performance Tuning Guide

Hex API Performance Tuning Guide

v20260423
hex-performance-tuning
This guide provides techniques to significantly boost performance when integrating with the Hex API. It covers essential optimization strategies such as implementing LRU caching for project lists, running multiple independent jobs in parallel, and adopting adaptive polling intervals to manage API latency and resource usage effectively. Use this when facing slow data retrieval or requiring high-throughput data processing.
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Overview

Hex Performance Tuning

Latency Benchmarks

Operation Typical Duration
ListProjects 200-500ms
RunProject (trigger) 500ms-2s
Project execution 10s-30min (depends on queries)
GetRunStatus (poll) 100-300ms

Instructions

Cache Project Lists

import { LRUCache } from 'lru-cache';
const projectCache = new LRUCache<string, any>({ max: 50, ttl: 300000 }); // 5 min

async function getCachedProjects(client: HexClient) {
  const cached = projectCache.get('projects');
  if (cached) return cached;
  const projects = await client.listProjects();
  projectCache.set('projects', projects);
  return projects;
}

Parallel Independent Runs

// Run independent projects in parallel (respecting rate limits)
async function parallelRuns(client: HexClient, configs: Array<{ id: string; params: any }>) {
  return Promise.allSettled(
    configs.map(c => runWithRetry(client, c.id, c.params))
  );
}

Optimize Poll Interval

// Adaptive polling: start fast, slow down
async function adaptivePoll(client: HexClient, projectId: string, runId: string) {
  let interval = 2000; // Start at 2s
  while (true) {
    const status = await client.getRunStatus(projectId, runId);
    if (['COMPLETED', 'ERRORED', 'KILLED'].includes(status.status)) return status;
    await new Promise(r => setTimeout(r, interval));
    interval = Math.min(interval * 1.5, 30000); // Max 30s
  }
}

Resources

Info
Category Development
Name hex-performance-tuning
Version v20260423
Size 2.08KB
Updated At 2026-04-26
Language