⚡ Optimize N+1 persistence overhead in pharmacy cancel items

[ManupaKDU]

💡 What:
Refactored the logic inside pharmacyCancelReceivedItems and pharmacyCancelBillItems to utilize lists and batchCreate / batchEdit facade operations instead of calling single-entity create and edit in a tight loop.

🎯 Why:
Previously, executing create or edit per element inside a for-loop generated a high number of independent flush/merge transactions directly hitting the database, leading to the severe N+1 performance bottleneck documented in the task.

📊 Measured Improvement:
Due to strict repository instructions ("never use mock data") and the inherent requirement of a JavaEE EJB container for these JPA persistence contexts, a dedicated automated test could not be supplied. However, analyzing the query paths logically:

• Before: n loop elements * (flush & clear) = ~2n separate statements/transactions hitting the database.
• After: The loop performs memory assignments, decoupling the entity state creation from persistence. At the end, batchEdit aggregates items into chunks of 25, resulting in just ~1-2 flushes per list. This drastically solves the N+1 latency issue.

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PR created automatically by Jules for task 9955850649640611356 started by @manupawickramasinghe

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