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batch-processing批处理

Agent Skill

batch-processing 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

10,453

周安装

427

GitHub Stars

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下载量

3,348
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:batch-processing(批处理)
来源仓库:https://github.com/qwe123sddfsdfs/batch-processing
安装命令:
openclaw skills install batch-processing
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install batch-processing

简介

DataLoader模式用于批处理,解决N+1查询问题。通过批处理和缓存将数据库/API 调用从 N+1 减少到 2。

SKILL.md

name
batch-processing
description
DataLoader pattern for batch processing to solve N+1 query problems. Reduces database/API calls from N+1 to 2 by batching and caching.

Batch Processing with DataLoader

Solve N+1 query problems using the DataLoader pattern. This skill provides utilities for batching database queries, API calls, or any expensive operations.

Problem: N+1 Query

// BAD: N+1 queries (1 for list + N for each item)
const users = await db.query('SELECT * FROM users');
for (const user of users) {
  const posts = await db.query('SELECT * FROM posts WHERE user_id = ?', [user.id]);
  user.posts = posts;
}
// Total queries: 1 + N (where N = number of users)

Solution: DataLoader Pattern

// GOOD: 2 queries total using batching
const DataLoader = require('./batch-processing/dataloader.js');

const userLoader = new DataLoader(async (userIds) => {
  // Batch load all users in one query
  const users = await db.query('SELECT * FROM users WHERE id IN (?)', [userIds]);
  return userIds.map(id => users.find(u => u.id === id));
});

const postLoader = new DataLoader(async (userIdss) => {
  // Batch load posts for multiple users
  const allPosts = await db.query('SELECT * FROM posts WHERE user_id IN (?)', [userIdss.flat()]);
  return userIdss.map(ids => allPosts.filter(p => ids.includes(p.user_id)));
});

// Usage - automatically batches concurrent requests
const users = await Promise.all(userIds.map(id => userLoader.load(id)));
const posts = await Promise.all(userIds.map(id => postLoader.load(id)));
// Total queries: 2 (regardless of N)

Core API

DataLoader Constructor

const loader = new DataLoader(batchLoadFn, options);

batchLoadFn: async (keys) => values

  • Receives array of keys
  • Must return array of values in same order
  • Can return null/undefined for missing keys

options (optional):

  • maxBatchSize: Maximum keys per batch (default: 100)
  • batchScheduleMs: Delay to collect batch (default: 0, immediate)
  • cache: Enable caching (default: true)
  • cacheKeyFn: Custom cache key function

Methods

  • load(key): Load a single key (returns Promise)
  • loadMany(keys): Load multiple keys (returns Promise<Array>)
  • prime(key, value): Manually prime cache
  • clear(key): Clear cache for key
  • clearAll(): Clear entire cache

Usage Examples

Database Batching

const userLoader = new DataLoader(async (ids) => {
  const rows = await db.query(
    'SELECT * FROM users WHERE id IN (?)',
    [ids]
  );
  return ids.map(id => rows.find(r => r.id === id) || null);
});

// Concurrent loads are automatically batched
const [user1, user2, user3] = await Promise.all([
  userLoader.load(1),
  userLoader.load(2),
  userLoader.load(3)
]);

API Batching

const apiLoader = new DataLoader(async (urls) => {
  const responses = await Promise.all(
    urls.map(url => fetch(url).then(r => r.json()))
  );
  return responses;
});

// Batch multiple API calls
const [data1, data2] = await Promise.all([
  apiLoader.load('https://api.example.com/users/1'),
  apiLoader.load('https://api.example.com/users/2')
]);

Nested Batching (GraphQL-style)

const postLoader = new DataLoader(async (userIds) => {
  const posts = await db.query(
    'SELECT * FROM posts WHERE user_id IN (?)',
    [userIds]
  );
  return userIds.map(id => posts.filter(p => p.user_id === id));
});

const commentLoader = new DataLoader(async (postIds) => {
  const comments = await db.query(
    'SELECT * FROM comments WHERE post_id IN (?)',
    [postIds.flat()]
  );
  return postIds.map(ids => comments.filter(c => ids.includes(c.post_id)));
});

// Resolve nested data efficiently
const users = await userLoader.loadMany(userIds);
for (const user of users) {
  user.posts = await postLoader.load(user.id);
  for (const post of user.posts) {
    post.comments = await commentLoader.load(post.id);
  }
}

Performance Comparison

ScenarioWithout DataLoaderWith DataLoader
Load 100 users101 queries1 query
Load 100 users + posts201 queries2 queries
Load 100 users + posts + comments301 queries3 queries

Best Practices

  1. Create loaders per request: Don't share loaders across requests to avoid cache pollution
  2. Batch size matters: Tune maxBatchSize based on your database/API limits
  3. Handle errors gracefully: Return null/undefined for missing keys, don't throw
  4. Use with Promise.all: Concurrent loads trigger batching
  5. Clear cache when needed: Use clear() for mutations that affect cached data

Files

  • dataloader.js - Core DataLoader implementation
  • examples/ - Usage examples for different scenarios
  • benchmarks/ - Performance comparison scripts

Installation

This skill is self-contained. Import the DataLoader:

const DataLoader = require('./batch-processing/dataloader.js');

When to Use

✅ Multiple database queries in a loop ✅ Fetching related data for multiple items ✅ API calls that can be batched ✅ GraphQL resolvers ✅ Any N+1 query pattern

❌ Single queries ❌ Real-time streaming data ❌ When order matters and can't be preserved

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

71.54%
按下载量换算2,395

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

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权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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