⚡ Bolt: [performance improvement] O(1) job event sequence generation - #162
⚡ Bolt: [performance improvement] O(1) job event sequence generation#162crabcanon wants to merge 3 commits into
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Replaces the O(N) memory allocation pattern (`list_for_job(job_id, limit=1000)[-1]`) with an optimized O(1) SQL aggregation (`get_max_sequence_no`) across all job control services, significantly reducing database bandwidth and memory consumption when assigning event sequence numbers. Co-authored-by: crabcanon <3458947+crabcanon@users.noreply.github.com>
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Replaces the O(N) memory allocation pattern (`list_for_job(job_id, limit=1000)[-1]`) with an optimized O(1) SQL aggregation (`get_max_sequence_no`) across all job control services, significantly reducing database bandwidth and memory consumption when assigning event sequence numbers. Co-authored-by: crabcanon <3458947+crabcanon@users.noreply.github.com>
Replaces the O(N) memory allocation pattern (`list_for_job(job_id, limit=1000)[-1]`) with an optimized O(1) SQL aggregation (`get_max_sequence_no`) across all job control services, significantly reducing database bandwidth and memory consumption when assigning event sequence numbers. Co-authored-by: crabcanon <3458947+crabcanon@users.noreply.github.com>
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💡 What: Replaced
list_for_jobarray slicing with a newget_max_sequence_noaggregate method inJobEventRepositoryacross multiple job controllers.🎯 Why: Resolves a major N+1 style inefficiency where up to 1000 event records were fetched from the database and loaded into memory solely to compute the next sequence number
+1.📊 Impact: Guarantees O(1) memory and bandwidth utilization during event sequence assignment regardless of event volume per job.
🔬 Measurement: Check Python profiles during heavy event emission; memory allocation per event should decrease significantly. Tests verify equivalent behavior.
PR created automatically by Jules for task 1460180389087522672 started by @crabcanon