0031-laravel-data-chunking-large-datasets

What problem does it solve?

Large Eloquent queries can exhaust memory and degrade performance when you load entire tables at once, especially during exports, migrations, and batch jobs.

Core Features & Use Cases

• Efficient chunking with chunk(): Iterate through records in fixed-size batches for general processing.
• Safer updates with chunkById(): Reduce skipping/duplication risk when modifying rows during iteration by using an ordering column (including custom ID columns).
• Low-memory iteration with lazy() and cursor(): Use generator-backed iteration for forward-only processing and streaming-style workflows.
• Real-world use cases: Export large CSV files, send batch email campaigns, run data migrations, and clean up old records with throttling-friendly patterns.
• Performance guardrails: Select only needed columns, ensure indexes on filter fields, optionally disable Eloquent events, and consider bulk updates and queueing heavy work.

Quick Start

Ask the AI to rewrite your Laravel batch job to use chunkById() for updates and lazy()/cursor() for streaming reads so it can safely handle millions of rows with minimal memory usage.