This is the right approach to processing billions of rows in a SQL database. This repository demonstrates the optimal method for handling large-scale data queries in SQL, bypassing common inefficiencies.
Typical SQL queries using LIMIT with an offset are not efficient for large datasets. This is because SQL loads all the data first, and then only returns the specified number of rows as defined in the LIMIT clause. This method becomes increasingly inefficient as the dataset grows larger.
This approach provides a better alternative, applicable across different programming languages. While this example utilizes PHP, the fundamental concept is deeply rooted in SQL principles. This data processing method is superior because it iteratively fetches manageable chunks of data based on the last processed ID, ensuring memory efficiency. It avoids the performance hit typical in OFFSET-based pagination, particularly in large datasets, as it doesn't need to skip over rows. This approach is also scalable, handling millions to billions of rows without performance degradation, making it ideal for large-scale data operations.
Contributions are welcome! Feel free to open issues or submit pull requests to improve this project.