Many engineers assume PHP is only suitable for simple web CRUD apps. At ScraperScoop, our core high-speed ingestion engine processes over 100 million structured data records every 24 hours using Core PHP 8.3, custom multi-curl workers, and highly optimized MySQL 8.0 partitioned tables.
1. Asynchronous Multi-cURL & Fiber Concurrency
By utilizing PHP 8.3 Fibers alongside `curl_multi_init()`, we achieve non-blocking concurrent HTTP requests across thousands of proxy nodes simultaneously with minimal RAM footprint (~25MB per worker process).
2. High-Speed MySQL Batch Inserts (`LOAD DATA LOCAL INFILE`)
Standard `INSERT INTO` statements bottleneck around 3,000 queries per second. By writing normalized CSV buffers in memory and executing `LOAD DATA LOCAL INFILE` or multi-row PDO prepared statements with `innodb_flush_log_at_trx_commit = 2`, ingestion throughput exceeds 85,000 rows per second.
3. Schema Partitioning by RANGE and HASH
To prevent index degradation on multi-terabyte tables, our dataset tables are automatically partitioned by date ranges (`RANGE COLUMNS(created_at)`), allowing instant archiving and lightning-fast analytical queries.