Implementing Scalable Pagination and Sorting in JHipster Applications
Learn how JHipster implements Spring Data JPA pagination and sorting to prevent memory exhaustion and optimize database performance in REST APIs.
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Learn how JHipster implements Spring Data JPA pagination and sorting to prevent memory exhaustion and optimize database performance in REST APIs.
Offset pagination drifts and slows on large Codeac result sets. Using a stable cursor with Spring Data JPA gives consistent pages and index‑friendly queries, at the cost of custom controller code and no random page jumps.
Learn how Spring Data JPA's Slice interface removes the costly COUNT(*) query from pagination, speeding up large‑dataset access while preserving simple next‑page detection.
JHipster's generated pagination looks effortless until your dataset grows. Here is how Spring Data JPA translates Pageable into SQL, why deep offsets hurt performance, and how to verify the generated behavior.
Unbounded findAll() calls risk OOM as tables grow. Learn how Spring Data JPA Pageable bounds queries, why the default count query hurts, and when to switch to keyset pagination.
Learn how to replace Spring Data JPA’s Page with Slice to avoid costly count queries when paginating large datasets, and understand the trade‑offs involved.
Learn how JHipster‑generated Spring Boot apps use Pageable to push pagination into Hibernate, verify the SQL, and manage the extra COUNT query trade‑off.
Learn how to add robust Hibernate pagination to a Java project under Towergit control, verify its behavior, and recover from mistakes with a clear, step‑by‑step guide.
A Spring Data JPA Page that returns too few rows usually means the COUNT query was never generated or was derived incorrectly. Diagnose it with SQL logging and fix it with explicit countQuery, Slice, or a custom fragment.