Optimize database queries and document efficiency improvements #46
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- Replace 5 separate database queries with single MongoDB aggregation pipeline - Reduce database round trips by 80% for media statistics - Add comprehensive EFFICIENCY_REPORT.md documenting all identified issues - Improve performance for users with large media collections Co-Authored-By: Timo <tmhoyland@icloud.com>
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Optimize database queries and document efficiency improvements
Summary
This PR addresses database performance issues by optimizing the
getUserMediaStatsmethod and provides a comprehensive efficiency analysis of the entire codebase. The main change replaces 5 separate MongoDB queries with a single aggregation pipeline, reducing database round trips by 80% and improving scalability for users with large media collections.Key Changes:
Promise.all([...5 queries...])with single MongoDB aggregation ingetUserMediaStatsEFFICIENCY_REPORT.mdidentifying 5 efficiency issues across the codebaseReview & Testing Checklist for Human
Test getUserMediaStats method with various scenarios:
Verify MongoDB aggregation syntax is compatible with project's MongoDB version:
$regexMatchoperator works correctly$condconditional logic behaves as expected/^video\//,/^audio\//,/^image\//match intended mime typesPerformance comparison between old and new implementation:
Integration testing of media statistics feature:
Notes
Risk Assessment: This optimization involves complex MongoDB aggregation syntax that wasn't tested locally. While theoretically sound, the aggregation pipeline could have subtle bugs or compatibility issues.
Future Work: The efficiency report documents 4 additional optimization opportunities that could be addressed in future PRs, including code duplication reduction and algorithmic improvements.
Session Info: