When querying a large dataset with complex relationships, what is a common approach to avoid performance issues?

Implementing pagination involves dividing large datasets into smaller, manageable chunks or pages, reducing the amount of data fetched in each query. This helps mitigate performance issues associated with querying large datasets. Using indexes can improve query performance by allowing for faster data retrieval based on specified columns. Denormalizing the database involves reducing the number of relationships and duplicating data to optimize query performance, but it may lead to data redundancy and maintenance challenges. Employing caching mechanisms such as in-memory caching or distributed caching helps store frequently accessed data in memory, reducing database round trips and improving query performance.