feat(CRED-75): Implement Month-End Accrual Journal Entries #105
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Pull Request Overview
This PR implements a new monthly accrual summary job for Fineract that automatically generates aggregated summaries of loan interest accrual transactions at month-end. The solution provides a non-intrusive way to create monthly summaries without modifying core accrual functionality.
Key changes:
- Adds new database tables for storing monthly accrual summaries and tracking processed transactions
- Implements a Spring Batch job that runs monthly to process accrual transactions
- Creates comprehensive service layer with duplicate prevention and error handling
Reviewed Changes
Copilot reviewed 13 out of 13 changed files in this pull request and generated 3 comments.
Show a summary per file
| File | Description |
|---|---|
| LoanMonthlyAccrualSummaryServiceImpl.java | Core service implementation for processing monthly accrual summaries |
| LoanMonthlyAccrualSummaryService.java | Service interface defining business operations for accrual summary processing |
| GenerateMonthlyAccrualSummariesTasklet.java | Spring Batch tasklet that executes the monthly summary generation |
| GenerateMonthlyAccrualSummariesConfig.java | Spring configuration for the batch job setup |
| LoanTransactionRepository.java | Enhanced with queries to find unprocessed accrual transactions |
| LoanMonthlyAccrualSummaryRepository.java | Repository for monthly accrual summary operations |
| LoanMonthlyAccrualSummary.java | JPA entity representing monthly accrual summaries |
| LoanAccrualTransactionProcessingRepository.java | Repository for tracking processed transactions |
| LoanAccrualTransactionProcessing.java | JPA entity for preventing duplicate transaction processing |
| LoanMonthlyAccrualSummaryData.java | Data transfer object for accrual summary information |
| JobName.java | Adds new job name enum for the monthly accrual summary job |
| 0007-create-monthly-accrual-summary-table.xml | Database migration script creating required tables and indices |
| MONTHLY_ACCRUAL_SUMMARY_JOB.md | Comprehensive documentation for the new feature |
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| private List<LoanTransaction> findUnprocessedAccrualTransactionsForLoan(Long loanId, LocalDate startDate, LocalDate endDate) { | ||
| Set<Long> processedTransactionIds = processingRepository.findProcessedTransactionIdsByLoanAndPeriod( | ||
| loanId, startDate.getYear(), startDate.getMonthValue()); |
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Using startDate.getYear() and startDate.getMonthValue() may not match the intended year and month parameters. The method should use the provided year and month parameters instead to ensure consistency with the processing logic.
| private List<LoanTransaction> findUnprocessedAccrualTransactionsForLoan(Long loanId, LocalDate startDate, LocalDate endDate) { | |
| Set<Long> processedTransactionIds = processingRepository.findProcessedTransactionIdsByLoanAndPeriod( | |
| loanId, startDate.getYear(), startDate.getMonthValue()); | |
| private List<LoanTransaction> findUnprocessedAccrualTransactionsForLoan(Long loanId, LocalDate startDate, LocalDate endDate, int year, int month) { | |
| Set<Long> processedTransactionIds = processingRepository.findProcessedTransactionIdsByLoanAndPeriod( | |
| loanId, year, month); |
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| "WHERE lt.typeOf = :transactionType " + | ||
| "AND lt.dateOf BETWEEN :startDate AND :endDate " + | ||
| "AND lt.reversed = false " + | ||
| "AND (:processedIds IS NULL OR lt.id NOT IN :processedIds) " + |
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Using NOT IN with a potentially large set of IDs can be inefficient and may cause performance issues with NULL values. Consider using NOT EXISTS with a subquery or handling empty sets explicitly to improve query performance.
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| "AND lt.typeOf = :transactionType " + | ||
| "AND lt.dateOf BETWEEN :startDate AND :endDate " + | ||
| "AND lt.reversed = false " + | ||
| "AND (:processedIds IS NULL OR lt.id NOT IN :processedIds) " + |
There was a problem hiding this comment.
Using NOT IN with a potentially large set of IDs can be inefficient and may cause performance issues with NULL values. Consider using NOT EXISTS with a subquery or handling empty sets explicitly to improve query performance.
Copilot uses AI. Check for mistakes.
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Description
Describe the changes made and why they were made.
Ignore if these details are present on the associated Apache Fineract JIRA ticket.
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