Faith & Code | Reflections by Errong

How to Optimize a Slow JPA Query Processing 40K+ IDs (Real Performance Tuning Guide) Handling large datasets efficiently is one of the most common challenges in backend engineering. In this post, I’ll walk through how a query processing 40,000+ IDs went from ~24 seconds down to a few seconds using practical optimization techniques. All domain-specific details have been intentionally removed to focus purely on reusable engineering patterns. 📉 The Problem A service fetches data using a JPA query with a large IN clause and joins between tables: SELECT new SomeDto( A.primaryId, A.field1, A.field2, B.field3, C.metric1, C.metric2 ) FROM EntityA A LEFT JOIN A.relatedEntity B LEFT JOIN EntityC C ON C.refId = A.primaryId WHERE A.primaryId IN :ids Even with chunking (~900 IDs per query), total execution time was around 24 seconds . 🚨 Root Causes Unoptimized JOIN conditions Missing database indexes Sequential query execution ORM (JPA) over...