⚡ Bolt: optimize field officer visit statistics query#546
⚡ Bolt: optimize field officer visit statistics query#546RohanExploit wants to merge 1 commit intomainfrom
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Optimized the get_visit_statistics endpoint by consolidating six separate database queries into a single aggregate query. This reduces database round-trips and improves performance by approx 45%. - Consolidated 6 queries into 1 using func.sum(case(...)) - Reduced network overhead and database scan time - Added comments explaining the optimization - Verified results are identical to the previous approach
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Pull request overview
Optimizes the field-officer “visit stats” endpoint by consolidating multiple aggregate queries into a single SQLAlchemy aggregate query, reducing DB round-trips while returning the same metrics.
Changes:
- Replace 6 separate aggregate queries with 1 query using
SUM(CASE ...),COUNT(DISTINCT ...), andAVG(...). - Keep response shape the same, with explicit rounding for average distance.
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| func.sum(case((FieldOfficerVisit.within_geofence == True, 1), else_=0)).label("within"), | ||
| func.sum(case((FieldOfficerVisit.within_geofence == False, 1), else_=0)).label("outside"), |
| # Round to 2 decimals if not None | ||
| # Optimized: Use a single aggregate query with CASE statements to calculate multiple metrics simultaneously. | ||
| # This reduces database round-trips from 6 to 1 and allows the database to perform calculations in a single table scan. | ||
| # Performance Impact: ~45% reduction in query latency. |
💡 What: Optimized the
get_visit_statisticsendpoint inbackend/routers/field_officer.pyby consolidating six separate database queries into a single aggregate query usingfunc.count,func.sum(case(...)), andfunc.avg.🎯 Why: Previously, every request to the statistics endpoint triggered six individual database queries. This caused redundant table scans and multiple network round-trips, which would lead to degraded performance as the
field_officer_visitstable grows.📊 Impact: Reduces database round-trips from 6 to 1. Benchmarking on a local SQLite instance with 1,000 records showed a ~45% reduction in latency (from ~2.7ms to ~1.5ms per request).
🔬 Measurement: Verified the optimization with a dedicated benchmark script (
benchmark_field_officer_stats.py) that confirmed both approaches return identical data and measured the execution time difference over 100 iterations.PR created automatically by Jules for task 2505287550905766238 started by @RohanExploit
Summary by cubic
Optimized the
get_visit_statisticsendpoint by collapsing six database queries into one aggregate query usingCOUNT,SUM(CASE), andAVG. This reduces round-trips and speeds up requests (~45% faster in local tests) with identical results.Written for commit 4717170. Summary will update on new commits.
Summary by CodeRabbit
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