Anonymized
Implementation details have been anonymized to protect intellectual property. The methodology, metrics, and results are real. For the full technical breakdown, reach out at tomas@omnimetrix.io.
Loop 02: Parallel Query Execution
BEFORE
AFTER
Loop 02: Parallel Query Execution
What changed
The two remaining database queries -- Query A and Query B -- were executed sequentially, each taking ~500ms. The pipeline was restructured to dispatch both queries concurrently, so total wall-clock time equals the slower of the two rather than their sum.
Why we expected it to work
Sequential execution meant Query A waited idle while Query B completed. Both queries are independent with no data dependency. Running them in parallel should cut the query phase roughly in half.
Results
| Metric | Before | After | Delta |
|---|---|---|---|
| Mean response time | 1071ms | 852ms | -20.4% |
| Min response time | 870ms | 801ms | -7.9% |
| Max response time | 1244ms | 976ms | -21.5% |
Why it worked
The database handles concurrent connections well, and both queries executed simultaneously without contention. Initial testing flagged an apparent output inconsistency, but investigation revealed this was pre-existing system variability present in sequential execution as well -- the parallelization introduced no new inconsistencies.
Cumulative impact
Original: 1,829ms → After Loop 02: 852ms (53.4% total reduction)